Quantitative Evaluation of the Whole Petroleum System: Hydrocarbon Thresholds and Their Application [1st ed. 2023] 9819903246, 9789819903245

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Xiongqi Pang

Quantitative Evaluation of the Whole Petroleum System Hydrocarbon Thresholds and Their Application

Quantitative Evaluation of the Whole Petroleum System

Xiongqi Pang

Quantitative Evaluation of the Whole Petroleum System Hydrocarbon Thresholds and Their Application

Xiongqi Pang College of Geosciences China University of Petroleum Beijing, China

ISBN 978-981-99-0324-5 ISBN 978-981-99-0325-2 (eBook) https://doi.org/10.1007/978-981-99-0325-2 Jointly published with Science Press The print edition is not for sale in China (Mainland). Customers from China (Mainland) please order the print book from: Science Press. ISBN of the Co-Publisher’s edition: 978-981-99-0324-5 © Science Press 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Foreword by Chengzao Jia

In the past 20 years, the exploration and development of unconventional oil and gas have made a series of significant progress, gradually replaced conventional oil and gas resources and developed into the main form of global oil and gas resources. Their biggest feature is that the formation and distribution of unconventional oil and gas are not controlled by buoyancy-driven and traps, which has made a major breakthrough to the classical petroleum geology theory, mainly manifested in six aspects. First, the large-scale continuous distribution of unconventional oil and gas breaks through the traditional concept of conventional oil and gas controlled by buoyance-driven and geological traps. Second, unconventional oil and gas exist in nano-scale pore-throat systems, which breaks through the concept of high porosity and high permeability of conventional reservoirs. Third, unconventional oil and gas accumulation has a selfsealing mechanism, which breaks through the concept that conventional oil and gas accumulation is controlled by the sealing of cap beds. Fourth, unconventional oil and gas migration and accumulation are dominated by non-buoyancy-driven and closely distributed near to or within source rocks, which breaks through the concept that conventional oil and gas migration and accumulation are dominated by buoyancydriven and separated from source rocks. Fifth, unconventional oil and gas development is mainly limited to “sweet spot layers” and “sweet spot areas,” which breaks through the concept of conventional oil and gas development involving the whole trap. Sixth, unconventional oil and gas are enriched in multi-phase forms such as molecular binding, molecular dissolution, and molecular adsorption, which breaks through the concept that conventional oil and gas mainly exist in free states. All these indicate that the theory of “from source to trap petroleum system” needs to be refined and developed. Many scholars have noticed relevant problems and put forward some new concepts in practice to try to make up for this deficiency, such as the total petroleum system, composite petroleum system, total composite petroleum system, and so on; however, it is still difficult to solve the practical problem that they are not fully adapted to guide unconventional oil and gas exploration and development. As a result, some of the world’s most difficult questions have long been unanswered, such as what are the differences and connections between conventional and unconventional oil and gas? What is the maximum depth of each type of oil and v

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gas resource? What are the patterns of formation and distribution of conventional and unconventional oil and gas reservoirs? How much oil and gas do we have on Earth? and so on. Although unconventional oil and gas resources have many completely different geological characteristics and distribution characteristics from conventional oil and gas resources, they also have many identical and similar geological characteristics and distribution characteristics, including the degradation of sedimentary organic matter, enrichment in strata of the same age, associated with each other and positive correlation, and the basic law of orderly distribution in petroliferous basins. This suggests that there is no scientific basis for dividing conventional and unconventional oil and gas resources into two distinct systems or grouping them into two distinct resource sequences. Therefore, petroleum geology should be based on the whole petroleum system model and should not be limited to the view of “from source rock to trap” but should be studied from the perspective of “source rock—reservoir— dynamic coupling and ordered accumulation,” including the long-distance migration of conventional oil and gas, the short-distance migration of unconventional oil and gas, and the non-migration or micro-migration of shale oil and gas. The core implication is to study conventional and unconventional oil and gas in the same system as a whole. In 2017, I proposed the concept of whole petroleum system (WPS) and published relevant papers in 2019 and 2023, defining the WPS as a natural system that encompasses all the oil and gas originated from organic matter in source rocks, the conventional and unconventional reservoirs and resources, the geological elements and processes involving in the formation, evolution, and distribution of these oil and gas, reservoirs, and resources. Core elements of WPS theory include: The WPS forms three hydrodynamic fields and two kinds of accumulation due to the difference of reservoir density. It includes conventional and unconventional oil and gas, orderly distribution of shale oil/gas-tight oil/gas and conventional oil/gas in the WPS, hydrocarbon migration and accumulation process in the WPS under the control of basin geodynamics and sedimentary system, self-sealing accumulation mechanism of unconventional oil and gas, self-sealing removal of oil and gas and artificial fracturing development mechanism, etc. The theory of the WPS is a great progress in the research of petroleum geology. Prof. Xiongqi Pang and Prof. Yan Song, as the main members of the team, have made important contributions in the theoretical research. In the past 20 years, the research team led by Prof. Xiongqi Pang has been engaged in the research on the correlation and difference between conventional and unconventional oil and gas in petroliferous basins from the perspective of the WPS, supported by the National Key Planning Research Project (973), the National Natural Science Key Foundation Project, and the National Petroleum Company Major Applied Basic Research Project. Three dynamic boundaries were discovered, including the Buoyance-driven Hydrocarbon Accumulation Depth (BHAD), the Hydrocarbon Accumulation Depth Limit (HADL), and the Active Source-rock Depth Limit (ASDL), and three Hydrocarbon Dynamic Fields (HDF), including freeHDF, confined-HDF, and bound-HDF, and a unified model of three dynamic boundaries and three dynamic fields jointly controlling the formation and distribution of

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conventional oil and gas, tight oil and gas, and shale oil and gas was established. New methods and technologies for classification of oil and gas reservoirs and quantitative prediction and evaluation of three types of oil and gas resources are developed. These results have been published in the leading and TOP journals. The book Quantitative Evaluation of the Whole Petroleum System summarizes the research work of Prof. Xiongqi Pang and his team on oil and gas accumulation in the past ten years, which has formed distinctive systematic innovation results and created conditions and opened up new ways to solve the current global problems in the field of oil and gas. It is expected that the publication of this monograph will attract more scholars to participate in the study of the whole petroleum system and play a guiding and promoting role in solving the worldwide problems facing the oil and gas field, promoting the process of oil and gas exploration under complex geological conditions, and cultivating more high-level talents.

Beijing, China

Chengzao Jia

Chengzao Jia mainly engaged in petroleum geology and exploration research. He is an academician of the Chinese Academy of Sciences, Chief Technical Engineer of the National Major Special Project of “13th Five-Year Plan” for petroleum science and technology, and the director of the Academic Committee of the State Key Laboratory of Petroleum Resources and Prospecting. He once served as the chief geologist of PetroChina, the president of China Petroleum Exploration and Development Research Institute, and the president of the Chinese Petroleum Society.

Foreword by Prof. Steve Larter

The source to trap petroleum system paradigm (Magoon & Dow, 1994) expounded the relationships between petroleum generation, expulsion, migration, accumulation, redistribution, and in-reservoir alteration and evolution processes. Building up on advances in the understanding of petroleum generation, primary and secondary petroleum migration, it has laid a solid theoretical foundation for modern petroleum geology and petroleum system understandings. In the last several decades, however, a lot of more unconventional oil and gas resources have been investigated, including producible resources from mature and over-mature source rocks and discovery and production of petroleum from reservoirs at great depths. The Chinese petroleum industry and its academic research partners in particular have pushed the limits of the types of reservoirs being investigated both in terms of exploration and production opportunities and also in terms of trying to understand fundamental processes at the limits of petroleum system boundaries. The book authored by Prof. Xiongqi Pang in the School of Earth Sciences, China University of Petroleum (Beijing), describes the results of several large studies operated under the Chinese National High-tech R&D Program (863 Project) and the Chinese National Key Basic Research and Development Program (973 Project) in 1986 and 1997 respectively, with the sponsorship of the Chinese Ministry of Science and Technology over the period 2006–2016. This monograph: Quantitative Evaluation of the Whole Petroleum System—Hydrocarbon Thresholds and Their Application collects the research results of Prof. Xiongqi Pang’s research team over the past ten years, analyzing the genetic characteristics of conventional and unconventional petroleum systems in six representative petroliferous basins in China and comparing them with those of petroliferous basins in North America. While the language and terminology are in place complex, there is new insight into petroleum system processes, and the book provides readers access to a large amount of collated

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data on Chinese basins and Chinese petroleum systems. It summarizes the perspectives of one of the larger research groups in China working on petroleum system studies.

Calgary, Canada

Prof. Steve Larter

Prof. Steve Larter has been engaged in oil and gas geochemistry and clean development and utilization of fossil energy for a long time. He is the fellow of Britain Royal Society, fellow of Canadian Academy of Science, and foreign member of the Norwegian Academy of Science and Letters.

Foreword by Zhangxing Chen

With the increasing difficulty of conventional oil and gas exploration and the decreasing oil and gas reserves discovered every year, human beings are facing the great pressure of energy shortage after entering the new century. Therefore, the Journal of Science listed the new energy replacing oil and gas as one of the 125 major challenges facing human beings in the twenty-first century. However, with the continuous strengthening of oil and gas exploration and the expansion of exploration scope, more and more oil and gas have been discovered in the exploration exclusion zone that classic petroleum geology theory thinks it is impossible to form oil and gas resources, including tight deep-basin oil and gas, coal seam oil and gas, shale oil and gas, heavy oil bitumen, gas hydrate, and so on. It is estimated that the potential resources of unconventional oil and gas exceed the conventional oil and gas by 5–10 times. The theory of the from source to trap petroleum system meets a series of challenges in guiding oil and gas exploration practices, including: What are the differences and correlations between conventional and unconventional oil and gas? How much oil and gas are there on the Earth? Where does their remaining potential lie? In the face of these worldwide issues, the research group led by Prof. Pang Xiongqi of China University of Petroleum (Beijing) has been continuously researching related problems in the past 20 years with the support of the National Key Basic Research Program (973). The monograph Quantitative Evaluation of the Whole Petroleum System mainly summarizes the main achievements they have made in the past ten years. The whole petroleum system (WPS) refers to the natural system formed by the interrelated source rocks in the petroliferous basins, including all oil and gas, oil and gas reservoirs, oil and gas resources, their formation and evolution process and distribution characteristics; the WPS is not only the geological unit of the formation, evolution, and adjustment of conventional and unconventional oil and gas reservoirs but also the material balance system of oil and gas generation, migration, accumulation, dispersion, and remained resources. The research content covers the all factors of oil and gas accumulation, the whole process of formation and evolution, the complete series of oil and gas resource distribution, and the full range of resources prediction and evaluation. The monograph Quantitative Evaluation of the Whole Petroleum xi

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System systematically introduces the research achievements in the following three aspects: First, ten critical geological conditions or oil and gas thresholds in the process of oil and gas generation, expulsion, migration, and accumulation were found, including the three dynamic boundaries of Buoyance-driven Hydrocarbon Accumulation Depth, Hydrocarbon Accumulation Depth Limit, Active Source-rock Depth Limit, three migration-accumulation thresholds of Hydrocarbon Expulsion Threshold, Hydrocarbon Accumulation Threshold, Hydrocarbon Reservoir Scale Threshold, and four hydrocarbon distribution thresholds of source-rock-controlled distribution threshold, depositional-face-controlled distribution threshold, potentialcontrolled distribution threshold, and cap-rock-controlled distribution threshold. Secondly, the correlation of these hydrocarbon thresholds influences the evolution process of the WPS and the formation mechanism of oil and gas reservoirs; the Hydrocarbon Dynamic Fields (HDF) of free-HDF, confined-HDF, and bound-HDF control the formation and distribution of oil and gas reservoirs; the unified genetic model for the formation and distribution of conventional and unconventional oil and gas reservoirs was established; new methods for prediction of shale oil and gas, tight oil and gas and conventional oil and gas is proposed and relative new technologies for quantitative evaluation of these reservoirs are developed. Thirdly, new theories, methods and technologies are applied to study global problems in the field of petroleum geology and exploration, and some new understandings are obtained: conventional and unconventional oil and gas reservoirs are not only different but also related, and a unified genetic classification scheme is proposed and all reservoirs are divided into three categories, six subcategories and 15 kinds; global oil and gas resource potential is not evaluated to be less than 25 trillion tons of oil equivalent, and the remained potential is mainly distributed in fine-grained source rocks, deep buried reservoirs, and future high-tech conditions, with the maximum buried depth between 3000 m and 13,000 m, increasing with decreasing heat flows; gas hydrates are unlikely to become a major source of energy for mankind in the future. The Quantitative Evaluation of the Whole Petroleum System is based on the drilling results of 80,762 target reservoir layers from 12,237 exploration wells of six representative basins in Tarim, Junggar, Sichuan, Ordos, Bohai Bay, and Songliao, as well as the study of geological characteristics and statistical analysis of discovered oil and gas reservoirs. The results are compared with the drilling results of major petroliferous basins in North America and the distribution characteristics of 52,926 proven oil and gas reservoirs in 1186 basins around the world. In this process, a large number of geological and geochemical analyses, key geological parameter tests, physical experiments, and numerical simulations of hydrocarbon accumulation were also carried out, highlighting the research characteristics of quantitative analysis of the WPS and the universal significance of understanding the results. This monograph focuses on the study of critical geological conditions or oil and gas thresholds in the process of oil and gas generation, expulsion, migration, and accumulation, including determining the discrimination criteria and change characteristics of hydrocarbon thresholds, revealing the main controlling factors and genetic mechanism of oil and gas thresholds, establishing the joint controlling model of oil and gas thresholds on reservoirs, and developing key application technologies. In the process of practical

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application of relevant theories, methods, and technologies, the current issues in oil and gas exploration and development are discussed and answered, and the system innovation results with distinctive characteristics are formed. The key contents and relevant understandings of each chapter of this monograph have been published in mainstream and TOP journals of high level in the fields of hydrocarbon, energy, and geoscience in the past five years, reflecting the pioneering research results and the high attention it has received. The WPS is a new concept which improves and develops the classical oil and gas system theory, which not only has important guiding significance in oil and gas exploration but also has important influence on global oil and gas resource evaluation and future efficient development and utilization. We expect that the publication of the book Quantitative Evaluation of the Whole Petroleum System will accelerate the rapid development and improvement of the WPS theory and the cultivation of highlevel talents and make new contributions to relieving the pressure of energy shortage in the current world.

Calgary, Canada

Zhangxing Chen

Zhangxing Chen mainly engaged in reservoir engineering and numerical simulation basic theory research and industrial application. He is also a national professor at the University of Calgary and a fellow of the Royal Canadian Academy of Sciences and the Royal Canadian Academy of Engineering. He is also a foreign academician of the Chinese Academy of Engineering and distinguished professor at China University of Petroleum (Beijing).

Preface by the Author

Petroleum system (Dow, 1974; Magoon & Dow, 1994) concepts and theories have been widely accepted and applied in the oil and gas industry since they were proposed and established, because they summarized the theoretical research results obtained by human beings in the process of exploring the formation mechanism and distribution law of oil and gas resources for more than 100 years, including the dominance of buoyancy in petroleum migration (White, 1885), traps control hydrocarbon accumulation (Orton, 1889; McCollough, 1934; Levorsen, 1956), petroleum formation from sedimentary organic matter (Lomonocov, 1763; Tissot and Welte, 1978), hydrocarbon distribution controlled by source rocks (Hu et al., 1962; Tissot, 1971), and so on, comprehensively and systematically elaborated the evolution process of hydrocarbon accumulation from source to trap, which laid the theoretical foundation of modern petroleum geology. The theory of petroleum system has been perfected and developed continuously in practical application. After that, some scholars have proposed new concepts and models such as total petroleum system (Magoon and Schmoker, 2000), composite petroleum system (Zhao et al., 2000), composite total petroleum system (Wandrey and Law, 2004), and petroleum accumulation system (Jin et al., 2003); they are used to solve the challenges and problems encountered in its guiding petroleum exploration, provide new theoretical and method guidance for the prediction and evaluation of favorable areas under complex geological conditions, greatly promoted the continuous expansion of petroleum exploration and the development of petroleum industry in their practice. In the new century, oil and gas exploration has gradually entered the exploration stage dominated by tight oil and gas and shale oil and gas. Although the theory of petroleum system has been improved and developed in this process, it still cannot guide the exploration and development of unconventional oil and gas resources effectively, and it cannot explain the geological characteristics, genetic mechanism, and resources distribution of the combined symbiosis of various oil and gas reservoirs with different characteristics. Jia et al. (2017, 2019, 2023) systematically and deeply analyzed the differences and correlations between the formation and distribution of conventional and unconventional oil and gas reservoirs in representative basins in xv

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China and compared them with the actual exploration conditions in major petroliferous basins in North America, and then the whole petroleum system is proposed, and the basic and special orderly distribution patterns for conventional and unconventional oil and gas reservoirs are established, providing new theoretical and methodological guidance for joint evaluation and integrated exploration of different types of oil and gas reservoirs and resources. Quantitative Evaluation of the Whole Petroleum System summarizes the innovative results of our research on the differences, correlations, and joint distribution of conventional and unconventional oil and gas resources in the past 20 years. It forms a systematic system of theories and methods for quantitative evaluation of whole petroleum system. In practical application, it provides a response to the key issues of current industry concern and a new understanding. Firstly, it is found that there are three dynamic boundaries in the whole petroleum system, including the Buoyancy-driven Hydrocarbon Accumulation Depth (BHAD), the Hydrocarbon Accumulation Depth Limit (HADL), and the Active Source-rock Depth Limit (ASDL), which provides a scientific standard for the classification and discrimination of conventional oil and gas, tight oil and gas, shale oil and gas, and provides a scientific basis for predicting their maximum burial depth under actual geological conditions. Secondly, it is found that there are three Hydrocarbon Dynamic Fields (HDF), such as the free-HDF, confined-HDF, and bound-HDF in the whole petroleum system, and then their classification and discrimination criteria are proposed, revealing the genetic mechanism and distribution pattern of the three dynamic fields forming conventional, tight and shale oil and gas resources, respectively, which provides scientific basis and theoretical guidance for the joint evaluation of conventional and unconventional oil and gas resources. Thirdly, the conceptual model of the whole petroleum system and the Hydrocarbon Dynamic Field controlling oil and gas accumulation have been applied to the research and development of the key technologies of quantitative prediction and evaluation of conventional oil and gas reservoirs, tight oil and gas reservoirs, and shale oil and gas reservoirs. The case studies are listed to demonstrate the ability, effectiveness, and reliability of the new theory, new method, and new technology to solve practical problems under complex geological conditions. Fourthly, the whole petroleum system is applied to the global joint assessment of conventional and unconventional oil and gas resources. For the first time, realistic, expected, and ultimate recoverable resources of conventional oil and gas, tight oil and gas, shale oil and gas at current, future 50% and 100% recovery rates were obtained at 25.8, 12.9, and 2.18 trillion tons of oil equivalent, respectively. Fifthly, the whole petroleum system is used to evaluate the global gas hydrate resource potential. Based on a new theoretical model and calculation method, it is estimated for the first time that the global natural gas hydrate resources range from 26 to 57 trillion cubic meters, which is less than 1.9% to 4.2% of the total conventional oil and gas resources. Therefore, it is concluded that natural gas hydrate cannot become the main energy resource for human development in the future.

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Quantitative Evaluation of the Whole Petroleum System consists of 12 chapters. Chapter 1 is the introduction, which introduces the problems of oil and gas exploration, the basic principles of solving these problems and the main achievements. In Chap. 2, a unified genetic classification of conventional and unconventional oil and gas reservoirs is conducted based on the whole petroleum system theory. Chapters 3–5 introduce the three hydrocarbon dynamic boundaries of BHAD, HADL, and ASDL in the whole petroleum system. Chapter 6 introduces the uniform genetic model of conventional and unconventional oil and gas reservoirs in the whole petroleum system. Chapters 7–10 introduce quantitative prediction and evaluation techniques and their application examples for conventional, tight, shale, and reformed oil and gas reservoirs in the whole petroleum system. Chapters 11 and 12 respectively introduce the global joint evaluation of 3-type and grade oil and gas resources and the global potential evaluation of gas hydrate resources and their new understandings. The Quantitative Evaluation of the Whole Petroleum System should be said to be the research result of our team. It includes major results of our six papers published in geoscience journals in the past ten years and the achievements and understandings of the scientific research projects just completed. The monograph is published in my personal name based on three considerations: first, the published papers are jointly completed by different research projects and scholars, and have been quoted in the monograph; Secondly, the content involved in the publication of these papers did not completely focus on the topic of quantitative evaluation of whole petroleum system but were deleted, revised, and improved in the monograph citation. Thirdly, the contents of the original papers are closely developed around the same theme in the process of writing monographs, and the logical correlation between them changes in chapter arrangement. In the formation of the monograph, I received careful guidance and help from Jia Chengzao, academician of Chinese Academy of Sciences and former Group leader of the 973 Project of the Ministry of Science and Technology; some of the research results were completed under his personal participation and guidance. Jin Zhijun, Dean of the School of Energy, Peking University and academician of the Chinese Academy of Sciences, gave specific guidance to the formation process of relevant achievements and new understandings. Hao Fang, President of China University of Petroleum (East China) and Academician of Chinese Academy of Sciences, has given much support and help to our research projects. Gao Deli, Director of the Academic Committee of China University of Petroleum (Beijing) and Academician of the Chinese Academy of Engineering, has provided specific guidance and financial support for the global and South China Sea gas hydrate resource evaluation. In the formation of the monographs, I also received specific help from Academicians Steve Larter from Britain and Chen Zhangxing from Canada, distinguished overseas scientists invited by China University of Petroleum (Beijing); Academicians Wang Tieguan of the Chinese Academy of Sciences, Academicians Qiu Zhongjian and Zhao Wenzhi of the Chinese Academy of Engineering, who have worked with us at the School of Earth Sciences of China University of Petroleum (Beijing); Academician Peng Pingan, Academician Zhu Rixiang of the Chinese Academy of Sciences, Academician Ma Yongshen, Academician Deng Yunhua, Academician Li Yang,

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Academician Li Gensheng of the Chinese Academy of Engineering, Academician Zhang Dongxiao of the America Academy of Engineering, Prof. Zhu Weilin of Tongji University, Prof. Xiao Lizhi of China University of Petroleum (Beijing), who are members of the Academic Committee of the State Key Laboratory of Petroleum Resources and Exploration of our university. I hereby express my heartfelt gratitude and respect to the experts and scholars listed above; without their help, the publication of this book would not have been possible. In addition, I would like to thank my research team and the graduate students who work with me day and night; a lot of meticulous and hard work is mainly dependent on their efforts to complete. We would like to express our gratitude to teachers Chen Junqing, Dr. Shi Kanyuan of our university and Ms. Wu Fanjie from Science Press for their hard work in the final publication of the book. The publication of our research work and achievement is the best memorial to the hard years and struggles that I, my colleagues, and students have gone through together, and it is also a reward to the tutors, leaders, and colleagues who have cared for and helped us with our research work for a long time. The Quantitative Evaluation of the Whole Petroleum System studies the difference and correlation between conventional and unconventional oil and gas reservoirs, as well as the geological characteristics, genetic mechanism, and distribution pattern of their joint symbiosis. Relevant achievements and new understandings have created conditions and opened up new ways for the development of new generation basin simulation technologies, for the joint evaluation of various oil and gas resources, and for the quantification, automation and Intelligent of oil and gas exploration decisionmaking. This book can be used not only as a scientific research tool for high-level researchers in petroleum geology and exploration but also as a teaching reference for high-level personnel training. Limited to our scientific research level and experience, mistakes and omissions in the book are inevitable, I am looking forward to readers’ criticism and correction.

Beijing, China

Xiongqi Pang

References Dow, W.G., 1974. Application of oil-correlation and source-rock data to exploration in Williston Basin. AAPG Bulletin. 58(7), 1253–1262. Hu, C.Y., 1962. A preliminary knowledge of hydrocarbon accumulation & its distributional regularity in Songliao Basin. Report Collection of Songliao Petroleum Exploration Technology Symposium. Jia Chengzao. On the breakthrough and significance of unconventional oil and gas to classical oil and gas geology theory [J]. Petroleum Exploration and Development, 2017, 44(1): 1–11. Jia Chengzao. Ordered accumulation characteristics and mechanism of conventional oil, tight oil, and shale oil sequences of Permian petroleum systems in Mahu sag, Junggar Basin[C]/ /Proceedings of the 17th National Organic Geochemistry Academic Conference. Fujian: Petroleum Geology Committee of Chinese Petroleum Society, 2019.

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Jia Chengzao, Pang Xiongqi, Song Yan. Whole petroleum system and ordered distribution pattern of conventional and unconventional oil and gas reservoirs[J]. Petroleum Science, 2023, 20(1): 1–19. Jin Zhijun, Zhang Yiwei, Wang Jie, et al. Oil and gas accumulation mechanism and distribution law[M]. Beijing: Petroleum Industry Press, 2003. Levorsen, A.I., 1956. Geology of petroleum. W. H. Freeman and Company, San Francisco. Magoon L B, Dow W G. The petroleum system: from source to trap[M]. Denver: American Association of Petroleum Geologists, 1994. Magoon, L.B., Schmoker, J.W., 2000. The total petroleum system: the natural fluid network that constrains the assessment unit. US Geological Survey World Petroleum Assessment. Mccollough E H. Structural influence on the accumulation of petroleum in California: Part IV. Relations of petroleum accumulation to structure. Problems of petroleum geology [M]. Tulsa, AAPG, 1934. Orton, E., 1889. The Trenton limestone as a source of petroleum and inflammable gas in Ohio and Indiana. U, S. Geol, Surv, Annu. Rep. 8, 475–662. Romonosov (Lomonosov), Translated by Ma Wanjun. On Stratigraphy. Beijing: Science Press, 1958, 1–1. Tissot B. P, 1971. New Data and Digital Simulation of Petroleum Generation and Migration Mechanisms and Their Applications in Exploration. Translated from the 8th World Petroleum Conference Papers. Tissot B P, Welte D H. Petroleum Formation and Occurrence [M]. New York: Springer-Verlag, 1978. Wandrey, C.J., Law, B.E., Shan, H.A., 2004. Patala-nammal composite total petroleum system, Kohat-Potwar geologic province, Pakistan. US Geological Survey Bulletin. 22(8), 1–20. White, I.C., 1885. The geology of natural gas. Science. 5(125), 521–522. Zhao, W.Z., He, D.F., 2000. Concept and its significance of composite petroleum systems in China. Petroleum Explorationist. 5(3), 1–11.

About the Author

Prof. Xiongqi Pang was born in 1961 in Hubei Province, China, received his Ph.D. degree from China University of Geosciences (Beijing) in 1991, and completed his post-doctoral research in University of South Carolina (USA) from 1994 to 1995. He is currently a leading professor at China University of Petroleum (Beijing) and deputy director of its Academic Committee. As the chief scientist of the National 973 Key Planning Research Project, he has been engaged in the research of hydrocarbon accumulation mechanism and distribution pattern in China’s superimposed basins for ten years (2006–2016). As the subject review expert and convenor of the National 863 High-Tech Project in the field of oil and gas, he has organized a series of major project approval and acceptance review (2012–2018) and served as the editor-in-chief of Petroleum Science for 14 years in a succession (2004–2018). He has revealed the difference and correlation between conventional and unconventional oil and gas reservoirs, and put forward a new quantitative evaluation method and technology for the whole petroleum system, published more than 120 papers (SCI) in the famous journals of petroleum, energy, and Earth science fields. He won one First-Level Prize and one Second-Level Prize of National Science and Technology Progress Award, 10 first prizes of provincial and ministerial level of Science and Technology Progress Award, 12 software copyrights, and 20 national invention patents. He also won the National Outstanding Teacher Award and enjoyed special government allowance. In 2017, he was awarded Li-Siguang Geological Science Research Award, the highest honor award in the field of geology in China. xxi

About This Book

This book introduces the method principle and key technology for Quantitative Evaluation of the Whole Petroleum System (WPS). It focuses on the correlation and difference between conventional and unconventional oil and gas reservoirs and resources, reveals the genetic mechanism and main controlling factors, establishes the unified genetic model, puts forward the prediction and evaluation method, and develops the application technology. The book mainly takes six representative basin studies in China as examples, with a large number of carefully compiled charts and results, has important guiding significance for conventional and unconventional oil and gas exploration and development in the world, and provides valuable new insights for petroleum geology lovers.

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Contents

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Introduction to Quantitative Evaluation of the Whole Petroleum System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Major Challenges Facing Oil and Gas Exploration . . . . . . . . . . . . 1.1.1 Progress in Oil and Gas Exploration and Research . . . . . 1.1.2 Breakthrough of Unconventional Oil and Gas Exploration to Classic Petroleum System . . . . . . . . . . . . . 1.1.3 Oil and Gas Exploration Practices Facing Significant Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Quantitative Evaluation Methods of the WPS . . . . . . . . . . . . . . . . . 1.2.1 Concept and Connotation of the WPS . . . . . . . . . . . . . . . . 1.2.2 Contents and Research Ideas of Quantitative Evaluation of the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Principle and Workflow of Quantitative Evaluation for the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Progress and Case Studies of Quantitative Evaluation on the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 There Are 3 Categories 10 Types of Hydrocarbon Thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Hydrocarbon Migration Thresholds Jointly Controlling Oil and Gas Resource . . . . . . . . . . . . . . . . . . . 1.3.3 Hydrocarbon Dynamic Fields Jointly Controlling Oil and Gas Resource Types . . . . . . . . . . . . . . . . . . . . . . . . 1.3.4 Hydrocarbon Distribution Thresholds Jointly Controlling Oil and Gas Enrichment . . . . . . . . . . . . . . . . . 1.3.5 Quantitative Evaluation of Total Oil and Gas Resources in the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Development Direction of the WPS . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.1 Research on the Difference and Correlation Between Conventional and Unconventional Oil and Gas Reservoirs in the WPS . . . . . . . . . . . . . . . . . . . . .

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Contents

1.4.2

Evaluation of Total Potential Oil/Gas Resources in the Global Petroleum System . . . . . . . . . . . . . . . . . . . . . 1.4.3 Development of Remained Oil and Gas Resources in Global Petroleum System . . . . . . . . . . . . . . . . . . . . . . . . 1.4.4 Development Prospecting of Natural Gas Hydrate in Global Petroleum Systems . . . . . . . . . . . . . . . . . . . . . . . 1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Unified Classification of Oil and Gas Reservoirs in the WPS . . . . . . . 2.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Research Method and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Research Sites and Data Collection . . . . . . . . . . . . . . . . . . 2.2.2 Research Contents and Workflow . . . . . . . . . . . . . . . . . . . 2.3 Correlations Between the Conventional and Unconventional Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Conventional and Unconventional Oil and Gas Both of Fossil Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Age Strata . . . . . . . . . . . . . . 2.3.3 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Basins . . . . . . . . . . . . . . . . . 2.3.4 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Layers . . . . . . . . . . . . . . . . . 2.3.5 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same PS . . . . . . . . . . . . . . . . . . . . . 2.3.6 All Conventional and Unconventional Oil and Gas Reservoirs Both in the Same WPS . . . . . . . . . . . . . . . . . . . 2.4 Differences Between the Conventional and Unconventional Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Conventional and Unconventional Oil and Gas Both Different in Compositions . . . . . . . . . . . . . . . . . . . . . 2.4.2 Conventional and Unconventional Oil and Gas Both Different in Source Rocks . . . . . . . . . . . . . . . . . . . . . 2.4.3 Conventional and Unconventional Oil and Gas Both Different in Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . 2.4.4 Conventional and Unconventional Oil and Gas Both Different in Tectonic Settings . . . . . . . . . . . . . . . . . . 2.4.5 Conventional and Unconventional Oil and Gas Reservoirs Both Different in Formation Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Unified Genetic Classification of Conventional and Unconventional Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . .

37 38 40 42 43 49 49 51 51 52 53 53 54 57 58 60 62 64 64 71 72 76

80 81

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2.5.1

The Unified Genetic Classification Scheme and Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.2 Identification Criteria for Conventional Trap Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.3 Identification Criteria for Unconventional Tight Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.4 Identification Criteria for Reformed Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Buoyancy-Driven Hydrocarbon Accumulation Depth in the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Buoyancy-Driven Hydrocarbon Migration and Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Definition of Buoyance-Driven Hydrocarbon Accumulation Depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Representative Basins Used to Study the BHAD . . . . . . . 3.3 Identification of Buoyancy-Driven Hydrocarbon Accumulation Depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Identifying BHAD by Distribution Characteristics of Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Identifying BHAD by Accumulation Characteristics of Oil and Gas Reservoirs . . . . . . . . . . . . 3.3.3 Identifying BHAD by Pressure Characteristics of Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.4 Identifying BHAD by Media Characteristics of Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Variation Features and Controlling Factors of the BHAD . . . . . . . 3.4.1 Variation of BHAD with the Lithology of Target Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.2 Variation of BHAD with Hydrocarbon Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.3 Variation of BHAD with Tectonic Movement . . . . . . . . . 3.4.4 Variation of BHAD with Underground Heat Flow . . . . . 3.5 Simulation Experiments on Dynamic Equilibrium of the BHAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 Physical Modelling Experiments on Dynamic Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.2 Numerical Simulation and Quantitative Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.1 Ubiquitous Presence of BHAD in Petroliferous Basins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

82 83 86 88 91 92 103 104 105 105 105 107 107 109 112 113 114 114 114 115 116 117 117 119 120 120

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3.6.2

Relationship Between the BHAD and Oil and Gas Accumulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.3 Resource Potentials of Oil and Gas Accumulations Constrained by BHAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

5

123 125 126 127

Hydrocarbon Accumulation Depth Limit in the WPS . . . . . . . . . . . . . 4.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Research Method and Identifying Criteria of the HADL . . . . . . . . 4.2.1 Geology of Research Basins . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Definition of HADL and Its Research Significance . . . . . 4.2.3 Identification of the HADL . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 The HADL Variation and Key Controlling Factors . . . . . . . . . . . . 4.3.1 HADL Variation Controlled by Oil and Gas . . . . . . . . . . 4.3.2 HADL Variation Controlled by Reservoir Layer Lithology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 HADL Variation Controlled by Reservoir Layer Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 HADL Variation Controlled by Geothermal Gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.5 HADL Variation Controlled by Other Geological Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Formation Mechanism of the HADL . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Depletion of Oil and Gas Generation Potential in Source Rocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Capillary Pressure Difference Termination Outsider and Insider the Reservoir . . . . . . . . . . . . . . . . . . . 4.4.3 Compaction Difference Termination Outsider and Insider the Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.4 Variation of Geothermal Gradients in Petroliferous Basins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Implication of the HADL for Potential Resource Prediction . . . . 4.5.1 Predicting Promising Areas for Oil and Gas Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5.2 Evaluating Oil and Gas Resource Potentials . . . . . . . . . . 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

131 131 132 132 133 134 137 141

Active Source-Rock Depth Limit in the WPS . . . . . . . . . . . . . . . . . . . . . 5.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 The Source of Materials and Research Methods . . . . . . . . . . . . . . . 5.2.1 Research Areas and Data Collection . . . . . . . . . . . . . . . . . 5.2.2 Formation Mechanism and Characterization of ASDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

159 159 160 160

142 143 143 143 146 146 147 148 149 150 151 152 154 155

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5.3

Identification of ASDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 The Identification of ASDL in the Junggar Basin . . . . . . 5.3.2 The Identification of ASDLs in Other Basins in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Major Factors Controlling on the ASDL . . . . . . . . . . . . . . . . . . . . . 5.4.1 The ASDL Variation with Organic Matter Types . . . . . . 5.4.2 The ASDL Variation with Heat Flows and Geothermal Gradients . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.3 The ASDL Variation with Tectonic Movement and Others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.4 Relationships Between the ASDL and the Heat Flow and Organic Matter Type . . . . . . . . . . . . . . . . . . . . . . 5.5 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 The ASDL Controlling on Vertical Distribution of Oil and Gas Reservoirs and HADL . . . . . . . . . . . . . . . . 5.5.2 The ASDL Controlling on Vertical Distribution of Liquid Oil and Natural Gas . . . . . . . . . . . . . . . . . . . . . . 5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

165 165

Unified Model for Oil and Gas Reservoirs Formation . . . . . . . . . . . . . 6.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Method and Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Unified Genetic Model for Conventional and Unconventional Oil and Gas Reservoirs in the WPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Concept of the Unified Model . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Identification and Prediction of Hydrocarbon Dynamic Boundaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Division and Identification of Three Hydrocarbon Dynamic Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4 The Characteristics of Oil and Gas Accumulations in the Unified Genetic Model . . . . . . . . . . . . . . . . . . . . . . . 6.4 Formation and Evolution Mechanism of the Unified Model . . . . . 6.4.1 Formation Mechanism of the Unified Genetic Model in a Petroliferous Basin . . . . . . . . . . . . . . . . . . . . . . 6.4.2 The Evolution of the Unified Genetic Model in a Petroliferous Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Application of the Unified Model for Oil and Gas Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.1 Evaluating Oil and Gas Resources by the Unified Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.2 Predicting the Distribution of Potential Resources by the Unified Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

183 184 185

6

169 170 170 171 172 173 175 175 177 179 180

186 186 188 191 193 195 195 197 199 199 202

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6.5.3

Quantifying Favorable Scope of Oil and Gas Reservoirs by the Unified Model . . . . . . . . . . . . . . . . . . . . 6.6 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.1 The Increase of Heat Flow Leading to Shallower Depth of the HDFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.2 Variation of Lithology Leading to Driving Forces Combination Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.3 Tectonic Movement Leading to Reformation of the HDFs and Reservoirs Type . . . . . . . . . . . . . . . . . . . 6.6.4 Application Range of the Unified Model . . . . . . . . . . . . . 6.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Evaluation of Conventional Oil and Gas Reservoirs . . . . . . . . . . . . . . 7.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Concept of Hydrocarbon Threshold and Its Significance . . . . . . . 7.2.1 Basic Concept of Hydrocarbon Threshold . . . . . . . . . . . . 7.2.2 Hydrocarbon Threshold Controlling on Reservoirs Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Joint Controlling Model of Multi-factors for Oil and Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.1 The Concept of Hydrocarbon Migration-Accumulation Threshold (HMAT) . . . . . . . . . 7.3.2 The Discrimination Criteria of Hydrocarbon Migration-Accumulation Threshold . . . . . . . . . . . . . . . . . 7.3.3 Joint Controlling Effect of HMAT on Reservoirs Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.4 Workflow of Oil and Gas Resource Assessment by Using HMAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.5 Application Examples of HMAT Controlling Reservoir Formation Model . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Prediction of Favorable Area for Oil and Gas Accumulation . . . . 7.4.1 The Concept of Hydrocarbon Distribution Threshold (HDT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.2 Mechanism of HDTs Joint Controlling Reservoir Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.3 Principle for Predicting Oil and Gas Reservoirs by Using HDTs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.4 Workflow of Favorable Area Prediction . . . . . . . . . . . . . . 7.4.5 Application Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Optimization of Drilling Targets for Oil and Gas . . . . . . . . . . . . . . 7.5.1 The Concept of Hydrocarbon Accumulation Threshold (HAT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.2 Quantitative Model of HATs Joint Controlling Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

203 205 206 206 209 211 212 213 217 217 219 219 220 222 222 222 223 225 225 226 226 227 229 230 231 232 232 233

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7.5.3

Application of HATs Joint Controlling Oil and Gas Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 7.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 8

Prediction and Evaluation of Tight Oil and Gas Reservoirs . . . . . . . . 8.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Method and Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Identification and Classification of Driving Forces and Their Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Workflow of Multi-forces Evaluation . . . . . . . . . . . . . . . . 8.3 Evaluating Contributions of Driving Forces by Statistics . . . . . . . 8.3.1 Data Sources and Research Principle . . . . . . . . . . . . . . . . 8.3.2 Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Evaluation Contributions of Driving Forces by Simulation . . . . . 8.4.1 Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 Simulation for Hydrocarbon Expulsion from Source Rocks in Different Phases . . . . . . . . . . . . . . 8.4.3 Simulation of Relative Contributions for 9 Driving Forces to Oil/Gas Expulsion . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Confirming Contribution of the CPD by Physical Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.1 Principle and Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2 Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.3 Dynamic Model for Oil and Gas Accumulation in Deep Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6.1 The CPD is the Most Important Driving Force for Tight Reservoirs Formation . . . . . . . . . . . . . . . . . . . . . 8.6.2 Special Conditions for Abnormal Oil and Gas Accumulation in Deep Reservoirs . . . . . . . . . . . . . . . . . . . 8.6.3 Tectonic Movements and Reservoirs Reformations . . . . 8.6.4 The Abnormal Low Saturation of Oil and Gas in Shallow Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6.5 The Critical Minimum Driving Force for Oil and Gas Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6.6 The Most Favorable Depth Range for Oil and Gas Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6.7 The Maximum Depth for Oil and Gas Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

239 240 242 242 245 246 246 246 248 248 249 254 260 260 261 262 271 271 271 272 273 273 273 274 274 275

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Contents

Evaluation of Unconventional Shale Oil and Gas Resource . . . . . . . . 9.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1.1 Shale Oil Exploration Showing Broad Development Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1.2 Continental Shale Oil Widely Distributed but Controlling Factors Very Complex . . . . . . . . . . . . . . . 9.1.3 Evaluating Quantitatively the Movability of Continental Shale Oil Difficult . . . . . . . . . . . . . . . . . . . 9.1.4 There Lacking Mature Technology for Evaluation of Continental Shale Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Principle and Workflow of Shale Oil and Gas Evaluation . . . . . . . 9.2.1 Main Contents and Technical Ideas . . . . . . . . . . . . . . . . . . 9.2.2 Key Study Area Selection and Regional Geological Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.3 Samples and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Sedimentary Lithofacies and Types of Shale Rocks . . . . . . . . . . . . 9.3.1 Mineral Composition Characteristics of Shale . . . . . . . . . 9.3.2 Bedding Structure Characteristics of Shale . . . . . . . . . . . 9.3.3 Characteristics of Shale Sedimentary Lithofacies . . . . . . 9.4 Variation and Controlling Factors of Retained Oil in Shale . . . . . 9.4.1 The Retained Oil Amount in Shale is Controlled by Lithofaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.2 The Retained Hydrocarbon Amount in Shale is Controlled by Pore Structure . . . . . . . . . . . . . . . . . . . . . 9.4.3 The Retained Hydrocarbon Controlled by Surrounding Rock Conditions . . . . . . . . . . . . . . . . . . . . 9.4.4 The Retained Hydrocarbon Amount in Shale Controlled by Burial Depth . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Mobility of Shale Oil and Its Genetic Mechanism . . . . . . . . . . . . . 9.5.1 The Principle of Physical Experiment on Shale Oil Mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5.2 Porosity and Permeability Controlling on the Movable Oil Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5.3 The Type and Content of Clay Minerals Control the Percentage of Movable Oil . . . . . . . . . . . . . . . . . . . . . . 9.5.4 Oil Viscosity Controlling on Shale Movable Oil Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5.5 Kerogen Content Controlling on the Percentage of Movable Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 Prediction and Evaluation of Shale Oil Resources . . . . . . . . . . . . . 9.6.1 Principle of Evaluation for Potential Recoverable Resources of Shale Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6.2 Key Parameters of Recoverable Oil and Gas Resources Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

279 279 279 280 281 282 282 283 284 285 285 285 286 289 291 291 294 301 305 308 309 312 313 314 315 316 316 317

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9.6.3

Prediction and Evaluation of Recoverable Shale Oil Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320 9.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324 10 Evaluation of Reformed and Destroyed Oil and Gas Reservoirs . . . . 10.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Geological Setting and Evaluation Method . . . . . . . . . . . . . . . . . . . 10.3 Relationship Between Tectonic Events and Oil/Gas Destruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.1 Reformed Oil and Gas Reservoirs Due to Multi-stage Tectonic Events . . . . . . . . . . . . . . . . . . . . . . 10.3.2 Key Geological Factors Controlling Oil and Gas Destruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.3 Superposition of Multistage Tectonic Events . . . . . . . . . . 10.4 Evaluation of Destroyed and Remained Oil and Gas Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4.1 Conceptual Geological Evaluation Model . . . . . . . . . . . . 10.4.2 Mathematical Model for Quantitative Evaluation . . . . . . 10.4.3 Acquisition of Geological Parameters . . . . . . . . . . . . . . . . 10.5 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5.1 Evaluation of Absolutely Destroyed Hydrocarbons Amount . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5.2 Evaluation of Relatively Destroyed Hydrocarbons Amount . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

333 334 335

11 Evaluation of the Global Oil and Gas Resources . . . . . . . . . . . . . . . . . . 11.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Identification and Distribution of Oil and Gas Resource Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2.1 Identification of Oil and Gas Resource Types . . . . . . . . . 11.2.2 Dynamic Boundaries for Oil and Gas Resources Distribution in the Underground . . . . . . . . . . . . . . . . . . . . 11.2.3 The Unified Model for the Distribution of Different Oil and Gas Resources . . . . . . . . . . . . . . . . . . 11.3 Evaluation Methods of Oil and Gas Resources . . . . . . . . . . . . . . . . 11.3.1 Estimation of the 3-Type and 3-Level Resources Based on Mass Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3.2 Acquisition and Validation of Five Essential Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3.3 Characterization of Essential Parameters . . . . . . . . . . . . . 11.4 Evaluation Results of the Global Oil and Gas Resources . . . . . . . 11.4.1 Characterization of Hydrocarbon Resources . . . . . . . . . .

369 369

337 337 341 345 347 347 349 351 356 356 357 363 364

373 373 374 376 376 376 378 389 390 390

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11.4.2 The Global Ultimate Hydrocarbons Resources and Their Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4.3 Distribution of Potential Hydrocarbon Resources . . . . . . 11.5 Mass Balance of Hydrocarbons in Different Forms . . . . . . . . . . . . 11.5.1 Quantitative Characterization of Evaluated Results . . . . 11.5.2 Reliability of Evaluated Results . . . . . . . . . . . . . . . . . . . . . 11.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.1 Introduction and Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Evaluation of the NGH Resource by Mass-Balanced Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2.1 Geological Model for NGH Formation and Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2.2 Mass-Balanced Model and Equations for NGH Resource Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2.3 Simulation Results and Variation Scope of NGH Resource . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 Evaluation of the NGH Resource by Drilling Analogy Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3.1 Principle for Drilling Analogy Method . . . . . . . . . . . . . . . 12.3.2 Two Case Studies in the World . . . . . . . . . . . . . . . . . . . . . . 12.4 Evaluation of the NGH Resource by Trend Analysis Method . . . 12.4.1 Principle by Trend Analysis Approach . . . . . . . . . . . . . . . 12.4.2 Results of Resource Estimates . . . . . . . . . . . . . . . . . . . . . . 12.5 Comparison of NGH Resource Estimates from Three Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5.1 Estimated Results from Three Approaches . . . . . . . . . . . 12.5.2 Implications to Future Oil and Gas Energy Supply . . . . . 12.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

390 393 400 400 401 405 406 413 414 427 427 431 437 439 439 440 443 443 444 446 446 447 448 449

Chapter 1

Introduction to Quantitative Evaluation of the Whole Petroleum System

New Understanding: (1) The study of total oil and gas system opens up a new way to improve and develop the theory of oil and gas geology. The theory of oil and gas system from source rock to trap lays the theoretical foundation of modern oil and gas geology and plays an important guiding role in conventional oil and gas exploration, but it is not suitable for unconventional oil and gas exploration. The whole petroleum system research covers “the whole elements of oil and gas accumulation, the whole process of interaction, the whole sequence of resource development and the all-round prediction and evaluation”, which provides a new theoretical guidance for the comprehensive exploration and development of oil and gas resources under complex conditions. (2) There are 3 types and 10 oil–gas thresholds in the evolution of the whole petroleum system. They include the Hydrocarbon Expulsion Threshold, Hydrocarbon Accumulation Threshold, and Reservoir Scale Threshold in the process of oil and gas migration and accumulation, the Buoyancydriven Hydrocarbon Accumulation Depth, the Hydrocarbon Accumulation Depth Limit, the Hydrocarbon Accumulation Threshold, and the distribution threshold of oil and gas reservoir controlled by the four factors of source facies potential cap. Oil and gas threshold is the critical condition corresponding to the sudden change of oil and gas geological conditions. The correlation determines the formation, distribution and resource potential of oil and gas reservoirs. (3) Based on the correlation between oil and gas thresholds, the quantitative evaluation of the whole petroleum system can be realized. Through the establishment of oil and gas migration and accumulation threshold joint control resource development model, the prediction and evaluation technology of oil and gas resources is developed; By establishing the distribution model of oil and gas reservoirs controlled by power conversion threshold, the prediction and evaluation technology of conventional oil and gas, tight oil and gas and shale oil and gas distribution is developed; By establishing the threshold combination of functional elements distribution to control the enrichment mode of oil and gas reservoirs, the key technologies for the prediction and evaluation of favorable reservoir forming zones and drilling targets are developed. (4) The preliminary results of quantitative evaluation of the whole petroleum system show that deep © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_1

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and unconventional oil and gas resources are the future development direction. The whole petroleum system can form 3 categories, 6 subtypes, 15 kinds and 49 oil and gas reservoirs, which are mainly distributed in the stratigraphic field between 4500 and 13,000 m; The ultimate potential of global oil and gas resources is about 25 trillion tons, and 90% of the remaining resources are distributed in deep and unconventional dense media. If they are all adopted, they can be used for human sustainable development for more than 200 years. (5) Global natural gas hydrate resources cannot become the main energy for human development in the foreseeable future. Their resource potential is less than 5% of the total conventional oil and gas resources, and their scale is limited; Large scale commercial utilization may take place after 2035– 2050, which is too late; Large scale mining is easy to cause geological disasters and environmental pollution, and lacks its own advantages in competition with tight oil and gas, shale oil and gas and other renewable energy sources.

1.1 Major Challenges Facing Oil and Gas Exploration 1.1.1 Progress in Oil and Gas Exploration and Research Since the discovery and use of petroleum in 1080, people have been continuously studying the mechanism of petroleum accumulation and distribution, and using the relevant research results to guide exploration and improve exploration results. The continuous discovery and application of oil and gas resources has brought about industrial civilization and social prosperity, which can be roughly divided into five stages according to different oil and gas exploration theories (Fig. 1.1). (1) Exploration stage by oil and gas seepage (1080 ~ 1861). Several historic events occurred during this period: oil and natural gas were first discovered and exploited in 1080 (Du 2017). In 1854, Francis Brewer, a doctor, bought the west Bard farm where the oil was growing, and founded the world’s first oil company with his partners— Pennsylvania Rock Oil Company, and drilled to 21 m depth on August 27, 1859, when the oil was pump out with steam power. Although the oil industry regards the Drake well as the world’s first oil well and the beginning of the modern oil industry, there are gas Wells and oil Wells in China, Russia, Romania, and other countries earlier than the Drake Well. For example, China drilled more than 1000 m of deep Wells in the world in 1835 (Wu 1999). Oil and gas seedlings are the direct evidence that oil and gas were spilled to the surface during the formation and evolution of oil and gas reservoirs, and they provide direct clues for searching oil and gas reservoirs. (2) Exploration stage by trap structures (1861 ~ 1934). Several important events of historical significance took place in this stage: for the first time, oil and gas reservoirs were found to be distributed in structural high points, and the theory of anticline controlling oil/gas reservoirs was put forward (None 1936); For the first time, the mechanism of anticline accumulating oil/gas is revealed from the principle

1.1 Major Challenges Facing Oil and Gas Exploration

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Fig. 1.1 Progress and stage division of global oil/gas exploration and comparison of annual oil and gas discovery and output in different stages

of dynamics, and the theory of buoyancy accumulating oil/gas is put forward (White 1885); The forming conditions of oil and gas reservoirs are systematically analyzed for the first time and the geological model for trap controlling oil/gas accumulation is put forward (Mccollough 1934). In the same year, Wilson proposed a trap classification scheme (Wilson 1934), it includes different types of structural reservoirs, stratigraphic or lithologic reservoirs, composite reservoirs and so on, which is similar to the later more complete Levorsen classification (Levorsen 1941). The theory of trap controlling oil/gas provides scientific basis for oil and gas exploration and improves the exploration effect. However, the theory of trap controlling oil/gas does not consider the key conditions such as the source of oil and gas, so it meets many challenges and difficulties in guiding oil and gas exploration. (3) Exploration stage by conventional petroleum system theory (1934 ~ 1992). Several important events of historical significance took place in this stage: the theory of organic origin of petroleum was put forward systematically for the first time (Hunt 1979). A relatively complete hydrocarbon generation model of kerogen was established for the first time (Tissot and Welte 1978). The concept of oil-bearing system is put forward for the first time (Dow 1972), and the accumulation mode of petroleum system was established (Magoon and Dow 1992). The theory of petroleum system, combining the buoyancy-driving theory, trap controlling theory, organic origin theory and source controlling theory, describes the characteristics, dynamic mechanism and distribution of hydrocarbon accumulation process from source rock to trap after

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hydrocarbon generation in a relatively complete way, laying the theoretical foundation of modern petroleum geology and providing theoretical guidance for efficient and rapid exploration and discovery of oil and gas resources. However, the petroleum system theory about oil/gas migration from source rock to trap cannot explain the formation and distribution of unconventional oil and gas resources, and it faces new challenges in the process of deepening oil and gas exploration. (4) Exploration stage by non-buoyance-driven oil/gas accumulation theory (1992 ~ 2022). In this stage, oil and gas exploration has undergone a revolutionary change: after the former Soviet union scholars evaluated the global hydrate resource potential (Trofimuk et al. 1973), the United States has successfully achieved commercial trial production of coalbed methane (Yang 2003), Canadian researchers discover tight deep basin gas reservoir in Albert Basin (Master 1979), large-scale development of Barnet shale gas has been realized in the United States (Li et al. 2011). There is a growing awareness of the existence of unconventional oil and gas resources on Earth that are not controlled by buoyancy, several events of historical significance occurred in the large-scale development of unconventional oil and gas resources: the concept of continuous unconventional tight oil and gas reservoirs was put forward for the first time (Schmoker 1995a), initial unification of unconventional oil and gas concepts and terminology. The Alm Coulee field was discovered in the first horizontal drilling in the mid-Bakken Shale (IEA 2010), the first multi-stage horizontal fracturing in the Bakken produced 1.1 million tons (IEA 2007), shale oil and gas production of USA surpassed conventional oil and gas production in 2017 for the first time (IEA 2018). The development of unconventional oil and gas is a long and slow process (Fig. 1.2), can be divided into discovery, technological breakthrough, rapid development of the three different stages (Fig. 1.2a), shale oil and gas production in nearly 20 years is increased by more than 20 times (Fig. 1.2b), but shrinking in the number of Wells in the process, single well yield showed a trend of increasing the total, reflecting the great promoting effect of scientific and technological progress on the production of unconventional oil and gas resources (Fig. 1.2c).

1.1.2 Breakthrough of Unconventional Oil and Gas Exploration to Classic Petroleum System The discovery and large-scale exploitation of unconventional oil and gas have made a breakthrough in conventional oil and gas exploration theory (Jia 2017), which has expanded the field of oil and gas exploration and increased the amount of oil and gas resources by 2–5 times, showing broad development prospects. (1) Basic concepts of unconventional oil and gas exploration and unconventional reservoirs. Unconventional oil and gas exploration refers to the exploration of oil and gas in the fields that are considered impossible by classical oil and gas geological theory. Unconventional reservoirs generally refer to those that have different

1.1 Major Challenges Facing Oil and Gas Exploration

5

Fig. 1.2 Comparison of production of Shale oil exploration and development stages and different regions in the United States (EIA 2020)

characteristics from conventional reservoirs and require special measures to achieve industrial productivity (Zou et al. 2012), they include tight and deep basin reservoirs (Master 1979), central basin reservoirs (Rose et al. 1986), synclinal hydrocarbon reservoirs (Wu et al. 2015), tight reservoirs (Spencer and Charles 1985), source-rock contacting reservoirs (Zhang 2006), shale reservoirs (Claypooll 1998), heavy oil and bitumen reservoirs (Rubinstein et al. 1977; Richard et al., 2007), coal seam reservoirs (Rightmire and Eddy 1984), natural gas hydrate (NGH) (Collett 2002), and so on. These plays have three characteristics compared to conventional plays. First, they have very low production capacity and often require special process measures to obtain commercial production; Second, their medium conditions are usually very dense, and it is necessary to take fracturing and other modification measures to release and exploit the oil and gas inside; Thirdly, their distribution in nature is completely different from that of conventional oil and gas reservoirs, which are not controlled by trap structures. Based on these characteristics, some scholars give them a name that is easy to understand and remember—continuous reservoir (Schmoker et al. 1995b). (2) Unconventional oil/gas exploration has made a great breakthrough to conventional oil and gas exploration theory. The breakthrough is shown in many different aspects, such as occurrence characteristics, formation conditions and genetic mechanism (Zou et al. 2013; Jia et al. 2021; Pang et al. 2021a). The distribution of conventional and unconventional reservoirs shows 21-point differences in at least four aspects, as detailed in Table 1.1. First, there are differences in occurrence characteristics: Conventional oil and gas reservoirs usually have the occurrence characteristics of “four high and one separation”, that is, high point convergence, high caprock, high pore enrichment, high pressure accumulation, and the separation of source from reservoir; Unconventional tight oil and gas reservoirs have the occurrence characteristics of “four low and one close contact”, that is, low sag convergence, low position

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inversion, low pore accumulation, low pressure stability, and close contact of source and reservoirs; Unconventional tight shale oil and gas reservoirs are characterized by integration of source and reservoir, extensive density, continuous distribution, low permeability and low yield. Conventional plays can produce naturally oil/gas under normal geological conditions, while unconventional plays often require treatment such as acidification and fracturing to get commercial oil/gas production. Second, there are differences in formation conditions: The formation conditions of conventional oil and gas reservoirs can be summarized into six aspects as generation, storage, cap-sealing, transport, trap, and preservation. The same six factors also affect the formation of unconventional reservoirs, but their importance is very different, and some are not indispensable. For example, the cap-sealing plays an essential role in the formation of unconventional reservoirs, but it is not always essential for the formation of deep basins oil/gas reservoirs; Migration is essential for conventional hydrocarbon accumulation, but it is not always essential for the formation of shale reservoirs; Traps are also essential for conventional hydrocarbon accumulation, but it is not necessarily for tight and shale oil/gas reservoirs formation. Third, there are differences in formation mechanisms: The formation of conventional reservoirs is dominated by buoyancy, while the formation of unconventional reservoirs is dominated by non-buoyancy; Different type of unconventional reservoirs have different non-buoyancy, heavy oil and asphalts are self-sealing due to molecular viscous force, shale oil/gas and coal gas are self-sealing due to molecular adsorption force, and tight oil/gas are self-sealing due to molecular interfacial tension. Conventional reservoirs formed in the early stage can be transformed into dense conventional reservoirs due to compaction in the later stage; The tight oil and gas reservoirs can be transformed into conventional oil and gas reservoirs by fractures or reformation after structure movement. Fourth, there are differences in distribution rules: Conventional oil and gas reservoirs can be distributed in either structurally stable or structurally unstable basins, while unconventional oil and gas reservoirs are mainly distributed in structurally stable basins; Conventional oil and gas reservoirs are mainly distributed in shallow reservoirs with high porosity and high permeability, while unconventional oil and gas reservoirs are mainly distributed in deep or very dense reservoirs; Conventional plays are usually located far from the source rocks, while unconventional plays are located close to or within the source rocks. Conventional oil and gas reservoirs are mainly distributed in normal temperature–pressure strata and reduction environment, while unconventional oil and gas reservoirs are mainly distributed in abnormal conditions such as high pressure-low temperature, high pressure-high temperature, and extreme oxidation environment.

1.1 Major Challenges Facing Oil and Gas Exploration

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Table 1.1 Comparison of geological characteristics, environmental conditions and dynamic mechanism of conventional and unconventional oil and gas reservoirs in the whole petroleum system Content Geologic feature

Formation condition

Dynamic mechanism

Distribution model

Conventional reservoirs

Unconventional reservoirs

Relation to structure

Distributed in the high point of the structure

Distributed in the lower part of the structure

Relation to cap rock

Cannot be formed with no caprock

Reservoirs can be formed with no caprock

Relation to pressure

Characterized by high pressure

Negative pressure is beneficial

Relation to porosity and permeability

Characterized by high porosity/ permeability

Characterized by low porosity/low permeability

Relation to source rock

The source/reservoir Source/reservoir are usually usually contacted separated

Generation

Formed before the reservoir became density

Formed after the reservoir became density

Reservoir layer

Distributed in high porosity/ permeability

Distributed in low porosity/permeability

Cap rock

Plays a decisive role Plays no decisive role in reservoir in reservoir formation formation

Migration

Long distance from source to reservoirs

Short distance from source to reservoirs

Traps

Control oil/gas accumulation

Did not control oil/gas accumulation

Preservation

Cap rock and trap preserve oil/gas

Density media and cap rock preserve oil/gas

Buoyance

Always play dominant role

Sometimes important

Fluid pressure

Sometimes play dominant role

Do not important

Water dynamics

Sometimes play dominant role

Do not important

Capillary pressure difference

Sometimes play dominant role

Very important

Inter molecular force

Sometimes play dominant role

Always play dominant role

Structure movement intensity

Tectonic variation is The structure is flat and present but not stable intense (continued)

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Table 1.1 (continued) Content

Conventional reservoirs

Unconventional reservoirs

Porosity and permeability condition

High porosity and permeability are favorable

Low porosity and permeability are favorable

Burial depth

Usually buried at a shallow depth

Usually buried deeply

Distance to source kitchen

Long distance

Short distance

Environment of T & P Normal Abnormal environment environment of T & of T & P P

1.1.3 Oil and Gas Exploration Practices Facing Significant Challenges Currently guiding unconventional oil and gas exploration based on conventional oil and gas geology theory is faced with a series of problems, mainly involving four fields. Solving these problems can not only improve and develop the theory of oil and gas accumulation, promote the current process of oil and gas exploration, and improve the effect of oil and gas resources exploration, but also answer the worldwide problems that have puzzled mankind for a long time in the field of oil and gas. (1) The relationship between conventional and unconventional oil and gas reservoirs is unclear, and there is no unified genetic model and classification scheme. The formation conditions, dynamic mechanism, main controlling factors and distribution law of conventional oil and gas reservoirs have been revealed through human efforts for more than 100 years since 1885, and also the types, formation conditions, accumulation mechanism and distribution characteristics of unconventional oil and gas reservoirs have been gradually revealed since the discovery of tight deep basin oil and gas reservoirs in 1978. However, what differences and correlations exist between the two and what causes such differences and correlations are not yet clear. In fact, some different unconventional plays have yet to be defined in the same term, and some different names are given to the same type of reservoirs. In this case, it is of great practical significance to clarify the difference and correlation between conventional and unconventional oil and gas reservoirs and reveal their genetic mechanism, to propose a unified genetic classification scheme, deepen academic exchanges and promote efficient exploration of different types of oil and gas resources. (2) The boundary of formation and distribution for conventional and unconventional oil and gas reservoirs is not clear, and the discriminant criteria are still not established. Although both conventional and unconventional hydrocarbon resources are derived from the same effective source rocks in petroliferous basins,

1.1 Major Challenges Facing Oil and Gas Exploration

9

their formation conditions, main controlling factors, dynamic mechanism and distribution characteristics are quite different, human beings have not been able to elucidate their genetic mechanism and internal law. For example, why do conventional oil and gas resources often form at shallower depths than tight oil and gas? Why are unconventional reservoirs mainly formed in tight media with porosity of less than 10% and permeability of less than 1 md? Is there a maximum burial depth for different types of oil and gas resources and what factors control them? What is the potential of oil and gas resources on earth? These results indicate that it is of great theoretical significance to further understand the potential of oil and gas resources and predict the distribution of remaining resources by clarifying the differences among oil and gas resources, defining their boundaries and scope, revealing the enrichment conditions and dynamic mechanisms of oil and gas accumulation in different fields, and establishing quantitative models. (3) The main factors controlling on the formation and distribution of conventional and unconventional oil and gas reservoirs are unknown. Conventional and unconventional oil and gas are not only controlled by the same source rocks in terms of origin, but also correlated, even superimposed, compounded, and transformed into each other in terms of accumulation mechanism and spatial and temporal distribution. Therefore, prediction and evaluation are very difficult, and there is no reliable and effective mature method and technology up to now. For example, the formation and distribution of conventional oil and gas resources are controlled by four factors: source rock, reservoir, low-potential area, and cap rock, while the formation and distribution of unconventional tight oil and gas reservoirs are controlled by four factors: source rock, reservoir, lower limit of buoyancy and structural stability area. They share some formation conditions and completely different dominant factors. Unconventional tight oil and gas reservoirs are formed and distributed close to source rocks, and the difference of capillary force between source and reservoir plays a key role in hydrocarbon accumulation, while unconventional shale oil and gas reservoirs are formed and distributed in source rocks, and adsorption and capillary force are very important for hydrocarbon self-sealing. Therefore, it is of great practical significance to reveal the main controlling factors of the formation and distribution of various oil and gas resources, establish quantitative models, and development technologies for predicting and evaluating the potential of remaining resources under increasingly complex conditions for efficient exploration of oil and gas resources. (4) The distribution of conventional and unconventional oil and gas resources and residual potential is unclear, and it is difficult to predict the development direction. How much oil and gas are there on earth? The answer given by different scholars at different times may be completely different in the face of this long-standing scientific problem. During the recession, when the supply of oil and gas exceeded demand, people were optimistic about the prospects of oil and gas resources; When the supply of oil and gas is in short supply during the economic boom, people are pessimistic about the prospect of oil and gas resources, and even appear the theory of oil and gas exhaustion. Why are there more and more estimates of the remaining oil and gas resources in the world even more and more oil/gas have

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been proved and produced? Why are the results of global nature gas hydrate resource estimates less and less when human beings have high expectations on them? All these indicate that, from the perspective of whole petroleum system, we should study and reveal the correlation and difference between conventional and unconventional oil and gas, objectively and scientifically evaluate the resource potential of different oil/ gas resources in the world under current and future technological conditions. It is of great and far-reaching practical significance for mankind to deepen the understanding of the formation and distribution of fossil energy, the distribution field of residual potential and the direction of future development.

1.2 Quantitative Evaluation Methods of the WPS 1.2.1 Concept and Connotation of the WPS (1) The formation and distribution of oil and gas reservoirs are controlled by various geological conditions. Oil and gas accumulation is a complex process controlled by various geological conditions, which has been known for a long time. First of all, it is realized that accumulation of oil and gas in the underground is controlled by buoyancy and the theory of buoyancy-driving oil/gas accumulation was put forward (White 1885). Dominated by buoyancy, oil and gas always tend to migrate from deep to shallow of the basin, from the central deep depression to the marginal slope area, the transport system consists of highly permeable layers, fault zones, unconformities and micro-fractures, and the surrounding of dominant path is most conducive to oil and gas migration and accumulation. Secondly, it is realized that the formation and distribution of oil and gas reservoirs are controlled by trap structure and the theory of trap controlling reservoirs was put forward (Levorsen 1956). Hydrocarbon migrates under buoyancy-driving and accumulates after entering traps, the earlier the trap is formed and the closer it is to the migration path, the greater the probability of hydrocarbon accumulation, the larger the trap size and the better the protected conditions during evolution, the more oil and gas accumulation. After that, it is realized that most of the oil and gas in petroliferous basins come from the degradation of sedimentary organic matter and the theory of organic generating hydrocarbons was put forward (Brooks 1935; Durand 1980). The larger of the thickness and area of organic-bearing source rock, the higher of the abundance of organic matter, the better of the type of parent material, the more of oil and gas generated and discharged during the evolution process, the more the oil and gas resources accumulated in the trap structure. Finally, it is realized that the formation and distribution of oil and gas reservoirs are controlled by source rocks rich in organic matter and the theory of source kitchen controlling reservoirs was put forward (Tissot and Welte 1978). Source kitchen refers to the intensity center of hydrocarbon generation and expulsion in source rock, the higher the intensity of hydrocarbon generation, the

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more of trap structures and the closer of the target layer to the center, the better the oil and gas exploration prospect in the study area. (2) The concept of petroleum system characterizes the combination of multiple factors to form majorly conventional oil/gas reservoirs, it is difficult to be used for all oil and gas reservoirs. Firstly, the concept of petroleum system has undergone a complicated research process. The concept of oil-bearing system was first proposed (Oil system) at a meeting of AAPG held in Denver, USA in 1972 and published in AAPG journal in 1974 (Dow 1974), it is mainly used to characterize the relationship between source rock, reservoir, and cap rock in the Williston Basin (Fig. 1.3a). The concept of Petroleum system was published in the journal of Petroleum Geology (JPG) in 1984 and 1992 (Perrondon and Masse 1984; Perrondon 1992), it refers to “a series of orderly combination of geological phenomena, starting from hydrocarbon generation, then migration, and finally hydrocarbon accumulation in traps, which are closely related to the dynamic processes of sedimentary basins determined by global plate tectonics”. The current accepted concept of petroleum systems was published in the AAPG Memoir 60 or in the monograph of the petroleum system—from source rock to trap (Magoon and Dow 1994), it is clearly defined as a natural system of effective hydrocarbon sources and associated reservoirs, all of which have been preserved to date, and the geological elements and processes necessary for their formation. Magoon and Dow not only gave the definition of oil and gas system, but also proposed scientific research methods: to determine the relationship between source rock and reservoir through oil-source correlation, and on this basis, to characterize the relationship between them with “four diagrams and one table”, thus guiding oil and gas exploration. Four diagrams refer to “burial history curve at critical moments”, “Regional distribution map of petroleum system”, “Profile characteristic map of Petroleum System”, and “Event correlation map of petroleum system”, as shown in Fig. 1.3. The first table refers to “statistical table of distribution of source rocks and their related oil and gas reservoirs”. Secondly, the concept of petroleum system plays an important role in guiding conventional oil and gas exploration practice and is constantly improved and developed, and its geological meaning is also constantly expanded and extended. Related terms and concepts derived from petroleum systems include composite petroleum systems (He et al. 2000), total petroleum system (Magoon and Schmoker 2000), Reformed and combined total petroleum system (Zhao et al. 2001), hydrocarbon accumulation system (Jin et al. 2003), composite total petroleum system (Wandrey et al. 2004), source rock petroleum system (Tang et al. 2021), and so on. The total petroleum system is defined as a lenticular accumulation of source rocks that are or have been producing hydrocarbons, the sum of all discovered and undiscovered related oil and gas (oil and gas traces, oil and gas seepages, oil and gas reservoirs), as well as all geological elements (source rocks, reservoir layers, surrounding strata, and cap-sealing) and processes (generation, expulsion, migration, and accumulation) that are essential to hydrocarbon accumulation. Both petroleum system and composite petroleum system only include discovered oil and gas reservoirs, oil and

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Fig. 1.3 Initial conceptual models and research contents of oil system and petroleum system. a Oil system division diagram of source rock, reservoir and evaporite cap (Dow 1972); b petroleum system and its research methods (Magoon and Dow 1994)

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gas seedlings and oil and gas displays, while the total petroleum system expands the original concept to include the undiscovered oil and gas reservoirs, oil and gas seedlings and oil and gas displays, to improve the scientific nature and the exploration guidance of potential oil and gas resources. Composite total petroleum system is a term used by USGS researchers in a USGS report to describe several oil and gas systems in the same study area, where there are multiple sets of superimposed source rocks, reservoirs and extensive fault systems leading to the mixing of hydrocarbons of different origin. To facilitate the operation, the Eocene-Miocene composite total petroleum system combined by seral petroleum systems was evaluated. In fact, there are many other terms and concepts related to petroleum systems, being related to each other, or complement each other. Thirdly, petroleum system concept has played an important role in explaining the characteristics of oil and gas accumulation and distribution under the complicated oil and gas geological conditions in China, but there are still many problems (Li et al. 2000; Liu et al. 2008; Tang et al. 2021; Wei et al. 2020). The petroleum system emphasizes a set of independent effective source rock and the oil and gas reservoirs formed by them, so it is not suitable for the overlapping basins with multiple source rocks and multiple stages of oil/gas accumulation in China. Besides, the petroleum system emphasizes the study of oil and gas source and divides the petroleum system with the effective source rock as the center, so it is difficult to apply in the basins or research areas with immature exploration or unknown source rocks. In addition, in the study of hydrocarbon migration from source rock to accumulation in traps, although the total hydrocarbon system considers shale oil/gas, coal bed oil/gas and other unconventional oil/gas, but does not explain the correlation and difference between conventional oil/gas in traps and unconventional oil/gas outside traps, so it is difficult to guide unconventional oil and gas exploration. After discussing the problems existing in the concept and application of petroleum system in detail, some scholars put forward a new concept of hydrocarbon accumulation system based on the system theory (Jin et al. 2003). The structural characteristics of hydrocarbon accumulation system are studied and the classification method and naming principle are put forward. According to application examples, the research method of hydrocarbon accumulation system and the work flow of guiding oil and gas exploration are formed, and the Petroleum System Maturity Index (PSMI) is put forward, it creates conditions for the development of petroleum system from qualitative analysis to quantitative evaluation, it was also applied to quantitative evaluation of oil and gas resources by scholars and affirmed by the industry (Pang et al. 2007; Jiang et al. 2018; Chen et al. 2020). The large-scale exploration and development of unconventional oil and gas is a major breakthrough in conventional oil and gas geology theory (Jia 2017). The total petroleum system extends the concept of the classical petroleum system to include aal potential undiscovered conventional plays and some unconventional oil and gas reservoirs, but does not address the intrinsic relationship between conventional and unconventional oil and gas resources within petroliferous basins.

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(3) The concept and research significance of the whole petroleum system. The concept of whole petroleum system is improved and developed on the concepts of petroleum system, total petroleum system, and so on. It is suitable for studying the formation and distribution of both conventional and unconventional oil and gas reservoirs, providing a new theoretical guidance for oil and gas exploration and development under complex geological conditions. Concept of the Whole Petroleum System. Jia believes (2017, 2019, 2021): “the future oil and gas geology should be a new complete theory model of oil and gas system, it is not limited to ‘from source rock to trap’ perspective, but from the ‘sourcereservoir coupling, orderly gathered’ new angle of view, including long distance migration and accumulation of hydrocarbons, short distance migration and accumulation of hydrocarbons, as well as close range occluded hydrocarbons migration and accumulation, such as conventional and unconventional oil and gas resources formation and distribution. The Whole Petroleum System (WPS) is defined (Jia et al. 2023) as “a natural system that encompasses all the oil and gas originated from organic matter in source rocks, the conventional and unconventional reservoirs and resources, the geological elements and processes involving in the formation, evolution, and distribution of these oil and gas, reservoirs, and resources”. By studying the differences and correlations between conventional and unconventional oil and gas reservoirs in six representative basins in China and eight major petroliferous basins in the United States, Jia et al. (2023) established the basic concept of oil and gas accumulation in the WPS and the basic model of orderly distribution of different oil and gas reservoirs as shown in the Fig. 1.4 and the special model of orderly distribution of different oil and gas reservoirs under complex geological conditions as shown in the Fig. 1.5. Studies have shown that the WPS includes the whole process of hydrocarbon generation and evolution, the conventional oil and gas migration, accumulation and adjustment, the unconventional oil and gas in-situ migration, accumulation, and adjustment. It is a natural geological system consisting of various oil and gas reservoirs formed by the interaction of essential factors; including all oil and gas reservoirs and resources formed and destroyed in the course of geological history, discovered and undiscovered in exploration; covering all the elements for hydrocarbon accumulation, the whole process of elements interaction, the whole series of oil and gas resources distribution, and the all-round research and evaluation. It includes not only the migration of oil and gas from source rock to trap to form conventional reservoirs, but also the migration from source rock to non-trap to form unconventional reservoirs, as well as the superposition, recombination, and conversion of the two oil and gas reservoirs during and after their formation. Difference and correlation between the concept of whole petroleum system and total petroleum system. Total petroleum system sometime is translated to “whole petroleum system” in Chinese. For the convenience of discussion, the whole petroleum system in this paper is expressed as WPS, which has three significant conceptual differences from TPS. One is that the effective source rocks in the WPS can be either a set of independent effective source rocks or several sets of source rocks

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Fig. 1.4 The basic ordered distribution pattern of conventional and unconventional oil and gas reservoirs in the WPS, expressed in form of “Shale\Tight–Conventional–Abnormal” or “S/T-C-A”. Shale and S refer to shale oil and gas reservoirs; Tight and T refer to tight oil and gas reservoirs; Conventional and C refer to conventional oil and gas reservoirs; Abnormal and A refer to abnormal oil and gas reservoirs, such as heavy oil & asphalt, natural gas hydrate, etc.; “\” refer to close connection or interbeded of shale oil and gas reservoirs and tight oil and gas reservoirs; “–” refer to separation of oil and gas reservoirs from their source rocks

which are related to each other in origin. Another is that all oil and gas reservoirs formed by effective source rocks are included in the WPS, including all conventional and unconventional oil and gas reservoirs discovered and undiscovered, as well as those formed and damaged in the past. Besides, the WPS includes not only the source rock-oil reservoir—surrounding rock assemblage under current geological conditions, but also the source rock-oil reservoir—surrounding rock assemblage and its evolution in geological history. It is important to note that TPS emphasizes the concept of quantity, especially the sum of the discovered (conventional) and undiscovered (conventional) components, however, WPS especially emphasize the spatio-temporal distribution and all elements integrity of hydrocarbon accumulation. Figure 1.6 shows the conceptual model of the whole petroleum system and their spatial and quantitative relationships. Study on WPS is of great significance to the exploration and development of oil and gas resources in complicated geological conditions. Mainly in three aspects: Study the correlation between different types of oil and gas resources in the WPS and its evolution characteristics, is conducive to further analyze the mechanism of conventional and unconventional reservoirs and their distribution, to establish the unified model and classification scheme, thus to improve and develop the oil and gas geological theory, to provide new theoretical guidance for the oil and gas exploration under the complex geological conditions. The Research on the differences and formation and evolution characteristics of different types of oil and gas reservoirs in

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Fig. 1.5 The special ordered distribution pattern of conventional and unconventional oil and gas reservoirs in the WPS of petroliferous basins. A-Special ordered distribution pattern of oil and gas reservoirs with tight oil/gas reservoirs separated from shale oil and gas reservoirs in the Permian WPS of Junggar Basin; B-Special ordered distribution pattern of oil and gas reservoirs with two directions ordered distribution of “S\T-C” in the WPS of Chang 7 member of Triassic in Ordos basin; C-Special ordered distribution pattern with lateral direction of oil and gas reservoirs distribution in Cretaceous WPS in Songliao Basin

Fig. 1.6 Conceptual model of the whole petroleum system and their spatial and quantitative relationships. a Spatial correlation of various oil and gas reservoirs in the WPS; b the correlation between the total amount of oil and gas generated in the source rocks and all kinds of oil and gas resources in the WPS

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the WPS is helpful to reveal the genetic characteristics, dynamic mechanism, main controlling factors and distribution law of different types of oil and gas reservoirs, thus to determine the boundary conditions and domain scope of their formation and distribution, including determining their maximum burial depth and developing prediction and evaluation technology, to provides new technical support for oil and gas exploration under complex geological conditions. The study on the mass balance of oil/gas accumulation and dispersion and on the characteristics of formation and evolution of various types of oil and gas resources in the WPS is helpful to predict and evaluate the total amount of global oil and gas generation, total loss, total accumulation, total resource, and residual potential distribution under different technical conditions, thus pointing out the direction of future oil and gas exploration and development.

1.2.2 Contents and Research Ideas of Quantitative Evaluation of the WPS (1) The basic content of the quantitative evaluation of the WPS. It mainly includes four challenges and 11 key scientific issues in current oil and gas exploration (Table 1.2). They involve the correlation and difference between conventional and unconventional oil and gas reservoirs, the genetic classification of these reservoirs, the formation conditions, dynamic mechanism, distribution and internal relationship of them, the development and practical application of key technologies and software for their prediction and evaluation, the distribution characteristics and development direction of global total and residual oil and gas resources. (2) The basic idea of quantitative evaluation of the whole petroleum system. The quantitative evaluation of the WPS involves a wide range of contents, faces many challenges. The basic idea of this paper is to carry out research in three different ways, and finally reach a consensus through comprehensive analysis. The first way is to continuously study the geological and evolutionary characteristics of the WPS based on the three-level project funding. The three levels of research topics refer to the research topics at the national level, the research topics at the level of the three oil companies and the research topics at the level of the oil companies. The research topics at different levels solve the key different level problems. In the past 20 years, we have organized and undertaken 10 projects at the national level, including the Overseas Study Fund for Cross-century Academic Leaders, the “973” Program of The National Key Basic Research Program, and the key and general projects of the National Natural Science Foundation of China; At the level of oil companies, we have organized and undertaken 16 research projects including major application basic research projects and youth innovation Fund projects of Petrochina, Sinopec and CNOOC; At the level of oilfield companies, we have organized and undertaken 31 research projects from the Daqing oilfield, Tarim oilfield, Xinjiang

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Table 1.2 The challenges in conventional and unconventional oil and gas exploration in the WPS Aspect of issues

Major challenges in conventional and unconventional oil and gas exploration

I. Characteristic difference and formation mechanism

1. What are the differences and correlations between unconventional and conventional reservoirs? 2. What are geological characteristics and unified genetic classification scheme for conventional and unconventional oil and gas reservoirs?

II. Domain boundary accumulation law

3. Is the bottom limit of buoyancy reservoir formation and the maximum burial depth of conventional reservoirs? 4. What are the critical conditions for the formation and distribution of tight oil and gas reservoirs and the maximum burial depth? 5. What are the critical conditions for the formation and distribution of shale oil and gas reservoirs and the maximum burial depth? 6. What is the spatio-temporal correlation between conventional and unconventional oil and gas?

III. Prediction method key technology

7. What are key factors, basic models, prediction and evaluation methods and techniques for the formation and distribution of conventional oil and gas reservoirs? 8. What are key factors, basic models, prediction and evaluation methods and techniques for formation and distribution of tight oil and gas reservoirs? 9. What are key factors, basic models, prediction and evaluation methods and techniques for the formation and distribution of shale oil and gas reservoirs? 10. What are key factors, basic models, prediction and evaluation methods and techniques of hydrocarbon amount destroyed by structure after hydrocarbon accumulation period?

IV. resources potential development direction

11. What are total amount, residual potential distribution and future development direction of different types of oil and gas resources in the world?

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oilfield, Qinghai oilfield, Southwest oil and gas field, Tuha oilfield, Liaohe oilfield and Jidong Oilfield of Petrochina, from the Shengli Oilfield, Zhongyuan Oilfield, Jiangsu oilfield, Jianghan oilfield, Northwest oil and gas field, Southwest oil and gas field of Sinopec, Tianjin oil and gas field, Shenzhen oil and gas field of Cnooc, from the Madagascar oil and Gas fields, Nanha oil and gas fields and other oil/gas field of the overseas enterprises. These topics not only provide sufficient funds for our scientific research, but also provide abundant first-hand information data about scientific issues and the breakthrough points for our study of the whole petroleum system. Second, the differences and correlations between conventional and unconventional reservoirs are studied based on the combination of three aspects. The combination of the three aspects respectively refers to the combination of domestic research and foreign research, indoor research and outdoor research, theoretical research, and application research. In the process of combining domestic research with foreign research, in addition to undertaking some domestic projects of foreign companies or overseas projects of domestic enterprise, we also focus on investigating and summarizing the difference and correlation between conventional and unconventional oil and gas geological characteristics of north American oil-bearing basins. The difference and correlation of geological characteristics of 52,926 oil and gas reservoirs in 1186 basins around the world (IHS 2010) are statistically analyzed, the common characteristics of oil and gas reservoirs discovered in foreign petroleum basins were compared with the drilling results of 12,237 exploration Wells and 80,762 oil and gas reservoirs in 6 representative basins in China, to find out their differences and correlations and reveal the causes. In the process of combining indoor and outdoor research, we have carried out extensive investigations and studies, built the “One-dimensional physical simulation experiment device for hydrocarbon generation and migration”, “Hydrocarbon migration and water–rock interaction twodimensional physical simulation experimental device”, “ Two dimensional physical simulation experiment device for structural change and oil and gas reservoir reformation”, “Three-dimensional physical simulation experimental device for lenticular sandstone reservoir formation”, “Physical simulation experiment device for lower limit and critical conditions of buoyancy-driving oil/gas accumulation” etc. (Zeng and Jin 2000). In addition, a series of high-precision testing instruments related to oil and gas accumulation research and a batch of oil and gas exploration application software were acquired, and the national key laboratory of Oil and Gas Resources and Prospecting was established, which created conditions for solving related scientific problems. In the process of combination of theoretical research and applied research, we reveal the differences between conventional reservoirs and unconventional reservoirs and relevance, determine the main controlling factors and intrinsic dynamic mechanism between the various factors, to establish the oil/gas accumulation model jointly controlled by “Multi-forces/Multi-times/Multi-elements” and developing the prediction and evaluation technology for the conventional and unconventional oil/ gas reservoirs.

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Third, the differences and correlations between conventional and unconventional reservoirs are analyzed based on drilling data and statistical simulation techniques. In this study, 6 representative basins, namely Tarim and Junggar in western China, Sichuan and Ordos in central China, and Bohai Bay and Songliao in eastern China, are selected as key analysis objects (Fig. 1.7), there are four fundamental reasons for selecting these six hydrocarbon basins. First, both conventional and unconventional reservoirs are widely developed and most explored; Second, proved reserves and predicted resources are large, accounting for 76.9% of China’s proved oil and gas reserves and 62.6% of the total resources, respectively; Thirdly, the geological conditions are representative of the petroliferous basins in China and the world. From western China to central China and then to eastern China, they are transformed from complex superimposed basins dominated by compression, to shear superimposed basins dominated by stretching, and then to single faulted basins dominated by stretching; From cold basin with low geothermal gradient to warm basin with high geothermal gradient, and then to hot basin with highest geothermal gradient; The deposition thickness changes from more than 10,000 m to 7000–8000 m, and then to 4000–5000 m; From carbonate—clastic rock—coal measure stratum combination sedimentary system to carbonate—coal measure stratum—clastic rock stratum, and then to clastic rock deposition; From Sinian to Neogene, the relatively complete petroliferous strata were transformed to the middle Cenozoic. The petroleum geological characteristics of these basins have been described in other literature (Ministry of Natural Resources of the People’s Republic of China 2016).

Fig. 1.7 Distribution characteristics of 19 major petroliferous basins and 6 representative basins (color filling) in China. a–c show the comparison of prospective resources, proved reserves and basin area of 10 basins. The six representative basins include Tarim and Junggar in the west, Sichuan and Ordos in the middle, and Bohai Bay and Songliao in the east. The data are mainly from relevant literatures (Ministry of Natural Resources of the People’s Republic of China 2016)

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1.2.3 Principle and Workflow of Quantitative Evaluation for the WPS In the past 20 years, we have found that there are 10 hydrocarbon thresholds in petroliferous basins, they represent the critical geological conditions in the process of hydrocarbon generation, migration, accumulation in the whole petroleum system. Based on the correlation study of reservoir controlling characteristics and mechanisms of different types of oil/gas threshold, the differences and correlations between the formation and distribution of conventional and unconventional oil and gas reservoirs are revealed, and the model for hydrocarbon thresholds joint controlling reservoirs formation is established, which opens up a new way for quantitative prediction and evaluation of the whole petroleum system. (1) Based on the concept of hydrocarbon threshold, the mechanism and characteristics of hydrocarbon migration and accumulation in the WPS are analyzed. Hydrocarbon Threshold refers to the critical geological conditions encountered during hydrocarbon generation, expulsion, migration, accumulation, and enrichment. For example, hydrocarbon generation thresholds refer to critical geological conditions for thermal degradation of large amounts of hydrocarbon generation by organic parent material (kerogen) within the source rock. They usually correspond to Ro ≈ 0.5% and vary with the type of parent material; Hydrocarbon expulsion threshold refers to the critical condition that the source rocks begin to expel a large amount of oil and gas in a free state during thermal evolution, the concept was first put forward to explain the thermal degradation and hydrocarbon expulsion characteristics of coal under physical simulation experimental conditions (Pang et al. 1985), later, it was published in the study of hydrocarbon expulsion characteristics from the source rock in Hailaer Basin of China and evaluation of its validity (Pang et al. 1992), relevant researches are introduced in detail in two monographs, “Research and Application of Hydrocarbon Expulsion Threshold “ and “Research and Application of Hydrocarbon Expulsion Threshold of Coal Measure Source Rocks” (Pang 1995, 2001). Hydrocarbon thresholds are currently divided into three broad categories (Fig. 1.8). The first type is related to hydrocarbon generation and expulsion, Fig. 1.8a1 shows the hydrocarbon generation threshold of the three parent materials in the source rock, Fig. 1.8a2 shows the hydrocarbon expulsion threshold of source rocks in Tarim Basin. The second type is related to hydrocarbon migration and accumulation, Fig. 1.8b1 shows the threshold of hydrocarbon accumulation in the process of hydrocarbon migration (Yan et al. 2012). Figure 1.8b2 shows the hydrocarbon accumulation threshold in sandstone reservoir (a) and shale reservoir (b). The third type is related to the distribution characteristics of oil and gas. Figure 1.8c1 is the vertical distribution threshold of oil and gas in sandstone reservoirs of Bohai Bay Basin, and Fig. 1.8c2 is the plane distribution threshold of oil and gas in sandstone reservoirs of West Siberia Basin (Ronov 1958). In fact, the formation of oil and gas reservoirs under actual geological conditions has encountered many more critical conditions than those listed in Fig. 1.8, and the situation is more complex. The classification of hydrocarbon threshold varies with different research purposes, they are

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Fig. 1.8 Conceptual model and classification of hydrocarbon thresholds in the formation and distribution of hydrocarbon reservoirs in the whole petroleum system

the concentrated embodiment of geological conditions changing from quantitative to qualitative in the process of hydrocarbon generation, expulsion, migration, and accumulation. Identifying the existence of hydrocarbon threshold, revealing their genetic mechanism and studying their correlation play a key role in explaining the distribution of hydrocarbon reservoirs and resources in the whole petroleum system and achieving quantitative evaluation. (2) The formation and distribution characteristics of oil and gas reservoirs in the WPS are studied according to hydrocarbon threshold control function. Generally, five methods are used to study hydrocarbon threshold controlling effects (Fig. 1.9), including case analysis, statistical analysis, physical simulation experiment, numerical simulation calculation and practical application test. These five methods are not only independent, but also related to each other and mutually verified, so each of them is logically indispensable. For case analysis, its biggest advantage is confirming the existence of oil and gas thresholds (Fig. 1.9a), it is intuitive and credible, while its disadvantage is that it cannot be confirmed whether the results have universal significance in the WPS, let alone the variation characteristics and distributions of such oil and gas thresholds. For statistical analysis, the identified hydrocarbon thresholds are confirmed by statistical analysis of the results from different case study in the WPS (Fig. 1.9b), its biggest advantage is that the wide existence of hydrocarbon threshold can been confirmed, and the characteristics and main controlling factors of hydrocarbon threshold change with different geological conditions can be displayed, its disadvantage is that the genesis mechanism of hydrocarbon threshold cannot be revealed. For physical simulation experiment, it was carried out to reveal the genesis mechanism of hydrocarbon threshold, and the formation conditions, main

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controlling factors and variation characteristics of hydrocarbon threshold were deeply understood from the results of physical simulation experiment. For example, through physical simulation experiments, we can clearly understand why dispersed oil and gas can accumulate in coarse-grained sandstone but not in fine-grained sandstone (Fig. 1.9c), thus revealing the mechanism of capillary force difference controlling oil and gas migration, accumulation, and accumulation in the deep and tight media. For numerical simulation, it can amplify the results of physical simulation experiments, the correlation between simulation results and each key parameter and its variation characteristics could be discussed in detail, apply them to predict and evaluate the formation and distribution of oil and gas reservoirs in large scale environments under geological conditions (Fig. 1.9d). For practical application test, the final results of the oil and gas threshold study are used to direct oil and gas exploration such as deploying scientific exploration Wells and determining the position of drilling wells (Fig. 1.9e); the theoretical model can also be tested for confirming its reliability in two aspects based on earlier oil and gas exploration results: One is the proportion of oil and gas reservoirs that have actually been discovered or successfully drilled in theoretically predicted favorable areas where the probability of oil/gas accumulation is more than 50%; The second is the ratio of the targets number with no oil/gas reservoirs proved or the ratio of failed Wells in the unfavorable area with theoretical accumulation probability less than 50%. (3) Study the formation and distribution of oil and gas reservoirs in the WPS according to the geological model of hydrocarbon thresholds joint controlling oil/gas reservoirs. Combined model of hydrocarbon thresholds joint controlling oil/gas reservoirs means that the correlation of multiple hydrocarbon thresholds in time and space controls the formation and distribution of hydrocarbon reservoirs in the WPS. The combination of hydrocarbon generation threshold, hydrocarbon expulsion threshold, hydrocarbon accumulation threshold and reservoir size scale threshold determines the distribution of total hydrocarbon resources and residual

Fig. 1.9 Five basic methods and techniques for quantitative evaluation of the Whole Petroleum System

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potential of the WPS; The boundaries and variation of different dynamic fields determines the zoning, zonation and evolution of oil and gas reservoirs in time and space; The spatial and temporal combination of the hydrocarbon thresholds controlled by key factors such as source, reservoir, cap, migration, accumulation and protection determines the degree and spatial distribution of hydrocarbon enrichment. A variety of methods and technologies are adopted to study the effect of combined hydrocarbon threshold controlling in the WPS. Figure 1.10 shows the thresholds of nature gas hydrate formation and distribution and its favorable fields under the combined action of high-pressure and low-temperature: The distribution of NGH in permafrost regions is controlled by a combination of minimum pressure thresholds (red line) and maximum temperature thresholds (blue line) as in Fig. 1.10a; The distribution of NGH in Marine is controlled by the combination of minimum pressure threshold (red line) and maximum temperature threshold (blue line) as in Fig. 1.10b. It can be seen that the red area surrounded by high pressure threshold and low temperature threshold is conducive to the formation and distribution of NGH reservoirs, this is a simple example of the joint controlling for gas hydrate formation and distribution of its pressure threshold and temperature threshold. Under the actual geological conditions, the formation and distribution of oil and gas reservoirs may be formed by the combination, enclosure, superposition, and composition of multiple hydrocarbon thresholds. For example, the formation and distribution of conventional oil and gas reservoirs are controlled by several factors such as generation condition, reservoir condition, cap sealing condition, migration condition, trapping condition and preservation condition, and their formation and distribution thresholds are controlled by the comprehensive effects of these six factors or conditions. It is of great practical significance to study the correlation among these hydrocarbon thresholds controlled by different factors for understanding oil/gas reservoirs formation and distribution. (4) Realizing quantitative evaluation of oil and gas resource potential of the WPS based on hydrocarbon thresholds joint controlling model. The quantitative

Fig. 1.10 Formation and distribution of gas hydrate controlled by combination of high pressure and low temperature threshold in the whole petroleum system (Chong et al. 2016)

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evaluation of whole petroleum system is divided into five stages (Fig. 1.11). In the first stage, the geological data and oil and gas drilling results of the study area were collected extensively to establish the oil and gas threshold discrimination standard; In the second stage, the proved oil and gas reservoirs are analyzed, and the characteristics of all proved oil and gas reservoirs are statistically analyzed to clarify the difference and correlation between conventional oil and gas reservoirs and unconventional oil and gas reservoirs. The differences and correlations include the internal characteristics of fluid and medium, vertical and plane distribution characteristics, oil and gas source characteristics, driving force and oil and gas accumulation period characteristics, oil and gas reservoir adjustment and reconstruction characteristics; The third stage identifies different hydrocarbon thresholds, reveals their main controlling factors and formation mechanism, and quantitatively characterizes the changes of these thresholds with the main controlling factors; The fourth stage studies the correlation of oil and gas thresholds and establishes the reservoir distribution model controlled by each different hydrocarbon threshold; In the fifth stage, the theoretical genetic model for the formation and distribution of conventional and unconventional oil and gas reservoirs jointly controlled by all different hydrocarbon thresholds is established, the new model is applied to develop new technology to predict and evaluate oil and gas reservoirs, and the reliability of the new technology is tested through practical application.

Fig. 1.11 Quantitative evaluation principle and workflow of the whole petroleum system based on studying oil and gas thresholds controlled by different geological factors

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1.3 Progress and Case Studies of Quantitative Evaluation on the WPS 1.3.1 There Are 3 Categories 10 Types of Hydrocarbon Thresholds By analyzing the geological characteristics of conventional and unconventional oil and gas reservoirs in six representative basins in China, study the results of physical simulation experiments and numerical simulation studies, and comparing the differences between conventional and unconventional oil and gas reservoirs that have been discovered in North America and the world, we found that there are three types of 10 hydrocarbon thresholds in WPS (Fig. 1.12), including 3 hydrocarbon accumulation and dispersion equilibrium thresholds, 3 hydrocarbon migration and distribution dynamic thresholds, and 4 temporal and spatial enrichment thresholds. Their association, enclosure and combination in time and space determine the formation and distribution of oil and gas reservoirs. (1) Hydrocarbon threshold about accumulation and dispersion equilibrium was found, opening a new way for quantitative evaluation of hydrocarbon resources. There are three thresholds for hydrocarbon accumulation and dispersion equilibrium (Pang et al. 2005a, 2014a), including the Hydrocarbon Expulsion Threshold (HET), Hydrocarbon Accumulation Threshold (HAT), Reservoir Scale Threshold (RST). After entering the HET, the source rock is identified as an effective source rock and the criterion is proposed, that is, the amount of hydrocarbon generation (Qp ) is equal to or greater than the total amount of retained oil and gas (Qr ) in the source rock, which is expressed as Qp ≥ Qr ; After entering the HAT, the hydrocarbon accumulation system is identified as effective and the criterion is put forward, that is, the hydrocarbon expulsion amount (Qe ) of the source rock in the system is equal to or greater than the loss (Ql ) in the migration process, which is expressed as Qe ≥ Ql ; After entering the RST, the hydrocarbon accumulation in the trap is determined as the

Fig. 1.12 Correlation and difference of proved 10 hydrocarbon thresholds, their classification and effects on oil/gas reservoirs formation and distribution in the whole petroleum system

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effective resource and the criterion is proposed, that is, the accumulated hydrocarbon amount (Qa ) is equal to or greater than the minimum commercial reservoir size (Qcm ), which is expressed as Qa ≥ Qcm . (2) Dynamic boundary of hydrocarbon migration and accumulation was found, providing a basis for the prediction and evaluation of different types of oil and gas reservoirs. There are 3 hydrocarbon migration and accumulation dynamic boundaries: One is the Buoyancy-driven Hydrocarbon Accumulation Depth (BHAD) (Pang et al. 2021a), it is the critical condition for the transition of driving force from buoyancy dominant to non-buoyancy dominant in hydrocarbon migration and accumulation with the increase of burial depth; The second is the Hydrocarbon Accumulation Depth Limit (HADL) (Pang et al. 2022), it is the critical conditions corresponding to the disappearance of hydrocarbon-driving force with the increase of burial depth; The third is the Active Source-rock Depth Limit (ASDL) (Pang et al. 2020), it is the critical conditions corresponding to the disappearance of hydrocarbon generation and expulsion potential of source rock with the increase of burial depth. These three hydrocarbon thresholds or dynamic boundaries control the maximum burial depth and variation characteristics of the formation and distribution of conventional oil/gas reservoirs, unconventional tight oil/gas reservoirs, and unconventional shale oil/gas reservoirs in the WPS, respectively. (3) The reservoir controlling threshold of the four functional elements is found, creating conditions for quantitative prediction and evaluation of the spatial and temporal distribution of oil and gas reservoirs. The controlling effects of the four functional elements on oil/gas reservoirs formation has been elaborated in relevant monographs (Pang 2014b), including the Source-rock Controlling HydrocarbonReservoirs Threshold, the Depositional-facies Controlling Hydrocarbon-Reservoirs Threshold, the Cap-rock Controlling Hydrocarbon-Reservoirs Threshold, the LowPotential Controlling Hydrocarbon-Reservoirs Threshold. The distribution threshold here refers to the Boundary, Area and Probability of oil and gas reservoir formation and distribution under the joint controlling of four functional elements. The 4 essential factors of the Source-rock, Depositional-facies, Cap-rock and Low-Potential are called functional elements because they are “indispensable, independent and quantitatively characterized” for the formation and distribution of oil and gas reservoirs. The fundamental purpose of revealing the correlation among the four functional factors controlling the hydrocarbon threshold is to achieve the quantitative prediction and evaluation of hydrocarbon reservoir formation and distribution under current conditions.

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1.3.2 Hydrocarbon Migration Thresholds Jointly Controlling Oil and Gas Resource It is found that three hydrocarbon migration thresholds jointly control the formation and distribution of hydrocarbon resources in the hydrocarbon accumulation system (Fig. 1.13), hydrocarbon accumulation system (Jin et al. 2003, 2022) is relatively independent and smallest oil–gas migration and accumulation units in the WPS. In general, the oil and gas generated by source rocks cannot migrate to one accumulation systems to another one accumulation systems. The accumulation and dispersion of oil and gas follow the principle of material balance: the total generated oil and gas amount is equal to the total amount of retained oil and gas in the source rock, dispersed oil and gas amount in the system, existing accumulated oil and gas, and the earlier destroyed oil and gas amount, therefore, the total amount of hydrocarbon resources can be obtained by subtracting the amount of retained hydrocarbon in source rocks, lost hydrocarbon by migration, worthless hydrocarbon accumulation and that destroyed by structural changes, it is the remaining resource potential to subtract the proven oil and gas reserves from the total amount of oil and gas resources, the detailed discussion of related issues is referred to the relevant monograph (Pang 2014a). (1) Total amount of hydrocarbon generation in source rocks. The amount of hydrocarbons generated from source rocks is called original hydrocarbon amount, which determines the resource potential of conventional, tight and shale oil and gas in the WPS (Fig. 1.13a). The total generated hydrocarbon amount of source rock is the sum of retained hydrocarbon and expelled hydrocarbon in source rock numerically, which can be obtained by physical simulation experiments (Zhou and Liu 2011) or by simulating the degradation kinetics of organic parent material (Qian et al. 1998). The amount of hydrocarbon retained in source rock can be calculated by the measured

Fig. 1.13 Material balance model of hydrocarbon generation, drainage, migration and accumulation in the whole petroleum system and reservoir size sequence (Pang 2014c)

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pyrolysis parameter “S1 ” of rock sample or the asphalt “A” obtained by chloroform extraction, but the light hydrocarbon compensation correction should be considered. (2) The hydrocarbons amount discharged from source rock. The amount of hydrocarbons discharged from source rocks refers to the amount of hydrocarbon provided by source rocks in various phase forms during the evolution process. In addition to the reduction of hydrocarbon generation and retention, they can also be obtained through physical simulation experiments (Hou and Lin 1991) and research on the variation characteristics of hydrocarbon generation potential with increasing burial depth of source rocks (Pang et al. 2005b; Zhu et al. 2008). The amount of hydrocarbons generated by the source rock reaches or begins to exceed the amount of retained hydrocarbon of various forms and then enters the hydrocarbon expulsion threshold; the amount of hydrocarbon discharged reaches the accumulation threshold after satisfying the loss of hydrocarbon during migration. Oil and gas can be discharged from the source rock in the form of diffusion, water soluble, oil soluble (gas) and free phase, and the free phase hydrocarbon has the greatest significance for oil and gas migration and accumulation. (3) Accumulated oil and gas amount. It refers to the amount of hydrocarbons finally accumulated in the trap, which was discharged from source rock, meeting various forms of loss in the process of migration and exceeding the commercial reservoir scale to form effective resource. The reservoir scale threshold is different under different geological conditions (Fig. 1.13b). The threshold for oil and gas exploration in China’s surrounding Marine environment exceeds 2 million tons, over 1 million tons in superimposed basins of western China, about 500,000 tons in mature exploration areas of eastern China. (4) The worthless accumulated hydrocarbons amount. It refers to the accumulated hydrocarbon amount in reservoirs which is smaller than the reservoir scale threshold. Figure 1.13c shows the geological characteristics associated or co-existing with reservoirs of different sizes under natural conditions. Canadian scientists establish a reservoir scale sequence model (Li et al. 1985), This model has been modified and perfected in practical application (Jin 1995), The parameters in this model can be modified according to the actual situation to achieve the maximum agreement between the theoretical prediction and the actual situation (Jiang, et al. 2009), USGS usually adopts this method in the evaluation of global oil and gas resources. Figure 1.11c shows that the reservoir scale sequence model can not only be applied to predict the size and number of potential effective reservoirs in practice, but also predict and evaluate the amount of non-valuable hydrocarbon amount accumulated in reservoirs whose size is smaller than that of commercial reservoirs. (5) Destroyed hydrocarbon quantity by tectonic movement. The hydrocarbon amount destroyed by tectonic movement refers to the hydrocarbon amount destroyed by tectonic movement after hydrocarbon accumulation period in the WPS. It is controlled by many factors, such as the hydrocarbon amount accumulated in the early period, the number of tectonic changes in the later period, the intensity of tectonic changes, the sequence of tectonic changes with different intensities and the sealing

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capacity of cap rocks on formed reservoirs. The results show that the superposition of stronger tectonic movements destroys hydrocarbon reservoirs, the superposition of weaker tectonic movements protects hydrocarbon reservoirs, and the superposition of stronger and weaker tectonic movements reform hydrocarbon reservoirs. Based on this principle, the amount of hydrocarbons destroyed and remained can be predicted and evaluated quantitatively (Pang et al. 2014c, 2018).

1.3.3 Hydrocarbon Dynamic Fields Jointly Controlling Oil and Gas Resource Types The type of oil and gas reservoir will also change when the migration and accumulation force of oil and gas changes. According to three hydrocarbon dynamic thresholds of BHAD, HADL and ASDL, the favorable area for hydrocarbon migration and accumulation are divided into three Hydrocarbon Dynamic Fields (HDF), named as free-HDF, confined-HDF and bound-HDF, and the unified model of hydrocarbon dynamic thresholds and fields join controlling oil/gas reservoirs were established (Fig. 1.14a). (1) High porosity and high permeability free dynamic field controls the formation and distribution of conventional oil and gas reservoirs. The area with high porosity and permeability between the BHAD and the ground surface constitutes a free-HDF which controls the formation and distribution of conventional oil and gas resources. After the oil and gas are discharged from the source rock stratum, they are mainly transported and accumulated in the high porosity and high permeability reservoir, which is dominated by buoyancy. The formation and distribution of oil and gas reservoirs are controlled by trap structures. They usually show the

Fig. 1.14 Hydrocarbon resource distribution pattern in dynamic fields of the whole petroleum system with dynamic boundaries (Pang et al. 2021b)

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basic characteristics of “high point convergence, high level capping, high porosity enrichment, high pressure reservoir formation and source reservoir separation”. The oil and gas reservoirs do not need to take any measures, and are expected to obtain high productivity. The burial depth is shallow. (2) The confined-HDF of low porosity and low permeability controls the formation and distribution of tight oil and gas reservoirs. The tight reservoir field communicated between the BHAD and the HADL constitutes a confined-HDF, which controls the formation and distribution of tight oil and gas reservoirs. After the oil and gas are discharged from the source rock stratum, they are mainly transported and accumulated in the low porosity and low permeability reservoir, which is dominated by non-buoyancy. The formation and distribution of oil and gas reservoirs are not controlled by trap structures. They usually show the basic characteristics of “low depression convergence, low inversion, low porosity enrichment, low pressure stability and tight source reservoir”. The oil and gas reservoirs need to take any measures such as acid fracturing to obtain commercial production capacity. This kind of oil and gas reservoir has a large burial depth. (3) The bound-HDF of low porosity and ultra-low permeability controls the formation and distribution of shale oil and gas reservoirs. The area with ultratight reservoir within source rocks between Hydrocarbon Expulsion Threshold and ASDL constitutes the bound-HDF, which controls the formation and distribution of shale oil and gas resources. After the generation of oil and gas, some of them are retained in the source rock by adsorption and capillary force to form shale oil and gas resources. They are also dominated by non-buoyancy. The formation and distribution of oil and gas reservoirs are not controlled by trap structures. They usually show the basic characteristics of “integration of source and reservoir, general compactness, wide distribution, low permeability and low production”, any measures such as fracturing can be taken to obtain oil and gas production capacity. The burial depth of this kind of oil and gas reservoir varies greatly: it is usually shale oil when the degree of thermal evolution is low and shale gas when the degree of thermal evolution is high. The maximum burial depth corresponding to the BHAD, HADL and ASDL varies with different geological characteristics, such as the formation age, geothermal gradient, lithology, organic parent material type and hydrocarbon composition, which affects the boundary range and domain size of three hydrocarbon dynamic field (Fig. 1.14b). Three different dynamic fields control the formation and distribution of three different types of oil and gas resources, but in actual geological conditions, free-HDF may also have locally distributed Confined hydrocarbon dynamic zone (C-HDZ), resulting in locally distributed tight unconventional oil and gas reservoirs; of course, local free dynamic zones (F-HDZ) may also exist in the confined hydrocarbon dynamic field, thus forming local conventional oil and gas reservoirs or sweet spots of unconventional reservoirs. These have been discussed in detail in the relevant literature (Pang et al. 2021b).

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1.3.4 Hydrocarbon Distribution Thresholds Jointly Controlling Oil and Gas Enrichment Classical oil and gas exploration theory summarizes the forming conditions and distribution characteristics of oil and gas reservoirs from six aspects: source-rock, reservoir-layer, capp-rock, migration, trap and preservation. However, these factors are not independent of each other and cannot be fully quantitatively characterized, so they are not essential to the formation of unconventional oil and gas reservoirs. Through the analysis of a large number of examples, it is found that the formation and distribution of oil and gas reservoirs are controlled by functional elements. According to the combination characteristics of functional elements, the enrichment model of oil and gas reservoirs is established, which provides theoretical guidance for distribution prediction. (1) Basic concepts of functional elements. Functional elements refer to the key geological elements that are indispensable, independent and quantitatively characterized in the process of oil and gas accumulation. They are: hydrocarbon source stove (S), which provides material basis for oil and gas accumulation; Reservoir facies (D) provides reservoir space for oil and gas accumulation; Low potential area (P) provides migration and accumulation power for oil and gas accumulation; Cap rock © in area provides protection for oil and gas accumulation. Each element has a hydrocarbon threshold that controls the formation and distribution of oil and gas reservoirs under actual geological conditions; Based on the correlation of these thresholds, a spatial–temporal distribution model of hydrocarbon accumulation and reservoirs formation was established (Fig. 1.15a). (2) Connotation of reservoir forming mode of combination of functional elements. It includes three levels. First, vertically, the four functional elements determine the most favorable reservoir forming horizon according to the orderly combination of source reservoir low potential cap (S\D\P\C) from bottom to top; Second, the geological history period determines the reservoir forming period according to

Fig. 1.15 Combination of hydrocarbon threshold for 4 functional elements in the WPS controls the formation, distribution, and enrichment of different types of oil and gas reservoirs

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the effective combination of four functional elements in the same geological period (T) (Sa = Da = Pt = Ct); Third, the superimposed area of hydrocarbon thresholds controlled by four factors on the plane determines the boundary, range and probability that are most favorable for hydrocarbon accumulation and enrichment. The statistical results show that more than 86% of proven oil and gas reservoirs are distributed in the overlap area of four functional elements, 14% in the overlap area of three functional elements, and no oil and gas reservoirs are distributed in the overlap area with only two element or one elements. (3) The reservoir forming mode of the combination of functional elements changes with the different dynamic field of the target layer. During the evolution of WPS, the oil and gas dynamic fields in the same target layer evolve with different burial depth conditions, and thus the types of reservoirs formation by combination of functional elements are different (Fig. 1.15b): During the burial process, it experienced the early F-HDF stage (B1) and formed conventional oil and gas reservoirs, the middle C-HDF stage (B2) and formed deep basin tight oil and gas reservoirs, and the late B-HDF stage (B3) and formed shale oil and gas reservoirs. At present, we can see the superposition and compound results of different types of reservoirs formed in different dynamic field stages (Fig. 1.15c). The conventional reservoirs formed in the early are mainly distributed in block 1 and 3 (blue), and the range is represented by T-CDPS; Tight deep basin oil and gas reservoirs are mainly distributed in block 2 and 3 (green), and the range is T-WLDS; The early and late two-stage superimposed zones form extensive overlapping continuous reservoirs, which are distributed in zones 1 + 2 + 3 (blue + green), using T-CDPS + WLDS; In the late stage, B-HDF (bottom of B3) is mainly developed, which is not conducive to the formation and distribution of oil and gas reservoirs.

1.3.5 Quantitative Evaluation of Total Oil and Gas Resources in the WPS The theory and technology of thresholds controlling hydrocarbon reservoirs have made remarkable achievements in popularization and application in our research. More than 160 SCI papers have been published, 23 invention patents and 12 software Copyrights have been authorized by the state. Five monographs on hydrocarbon thresholds were published, including Hydrocarbon Thresholds Research and Application (Pang 1995), Hydrocarbon Thresholds Research and Application of Coal Measure Source Rock (Pang 2001), Hydrocarbon Migration and Accumulation Thresholds and Resource Potential Evaluation (Pang 2014a), Thresholds of Hydrocarbon Distribution and Prediction of Hydrocarbon Accumulation Zones (Pang 2014b), Thresholds of Hydrocarbon Enrichment and Optimization of Drilling Targets (Pang 2014c); Six monographs on hydrocarbon threshold discrimination

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and prediction technology have also been published, including Reservoirs Reconstruction and Quantity Simulation of Hydrocarbon Amount destroyed by Structural Movement (Pang 2014d), Hydrocarbon Accumulation Mechanism and Quantitative Simulation of Typical Superimposed Basins in China (Pang et al. 2007), Quantitative Simulation of Hydrocarbon Accumulation (Pang et al. 2005a), Numerical Simulation of Geohistory, Thermal History, Hydrocarbon Generation, Retention and Expulsion History and Quantitative Evaluation of Source Rocks in Petroliferous Basins (Pang 1993), Comprehensive Quantitative Evaluation of Cap Rocks Sealing properties to Hydrocarbon (Pang et al. 1993); Two textbook were published for undergraduates and postgraduates, including Quantitative Simulation of Hydrocarbon Accumulation (Pang et al. 2005a) and Quantitative Simulation of Geological Processes (Pang 2003). The theoretical study and related technologies development have been extended to some actual basins for concretization, and relevant monographs have been published, including Petroleum Geology and Exploration in Onshore of Madagascar (Pang et al. 2016a), Genesis Mechanism and Prediction Method of Superimposed Continuous hydrocarbon Reservoirs: A case study of Marsel exploration area in Southern Kazakhstan (Pang et al. 2016b), Oil and Gas Reservoirs Formation and Distribution in Liaohe Depression (Meng et al. 2016), Oil and Gas Reservoirs Formation and Distribution Prediction in Bohai Basin (Wang et al. 2016), Oil and Gas Reservoirs Formation, Evolution and Distribution Prediction in Tarim Basin (Yang and Pang 2006), Formation Mechanism and Prediction Method of Tight Sandstone Gas Reservoir in Kuqa Depression (Jiang et al. 2015), Formation Mechanism and Prediction Method of Tight Sandstone Gas Reservoir: A case study of western Sichuan Depression (Yang and Pang 2012), Theory and Practice of Hydrocarbon Potential Resource Exploration in Mature Continental Basins—A case study of Bamianhe area (Xu et al. 2006), Formation of Subtle Hydrocarbon Reservoirs in Continental Faulted Basins—A case study of Jiyang Depression (Li and Pang 2004). The relevant theories and technologies have been applied in 26 exploration areas in 16 basins around the world, and have played an important guiding role in the deployment of 560 exploration Wells, adding 4.3 billion tons of oil equivalent reserves, and increasing the success rate of exploration Wells by 20%. More and more scholars have recognized the research work importance of quantitative evaluation of the whole petroleum system based on hydrocarbon thresholds. Through investigation and retrieval, it is found that not only we ourselves are studying the hydrocarbon threshold’s controlling function on reservoirs formation, but more and more scientists have joined in this research (Fig. 1.16a). Our academic research papers are not only published in the major oil and gas journals (AAPG Bulletin, Marine and Petroleum Geology, Journal of Petroleum Science and Engineering), more and more of them have been also published in the world famous mainstream journals in the fields of fossil energy, energy, earth science (Fig. 1.16b). It shows the importance and development prospect of relevant research.

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Fig. 1.16 Hydrocarbon threshold research in whole petroleum system and distribution of major papers in different journals. a Number of our research papers and variation characteristics about oil and gas threshold research; b distribution of papers related to oil and gas threshold studies (FI > 3.0)

1.4 Development Direction of the WPS Based on the oil and gas threshold study, we can realize the quantitative analysis of the whole petroleum system; Through the quantitative analysis of the whole petroleum system, we can achieve the quantitative prediction and evaluation of conventional, tight and shale oil and gas resources. In addition, we also explore some of the world’s problems based on relevant research results and give our new understanding, then to point out the direction of future development.

1.4.1 Research on the Difference and Correlation Between Conventional and Unconventional Oil and Gas Reservoirs in the WPS How many types of oil and gas reservoirs are present in the whole petroleum system? This problem has been perplexing oil and gas geologists and explorers for a long time, thus affecting the results of oil and gas exploration. At present, most scholars at home and abroad regard conventional and unconventional oil and gas as two different types of oil and gas resources for research, exploration and production, and some countries give financial subsidies to the exploitation of unconventional oil and gas resources. In fact, conventional and unconventional plays are not completely independent and cannot be studied as separate and distinct oil and gas systems. They are both products of the evolution of the WPS. In this system, studies on the mechanism of conventional oil and gas accumulation (from source rock to trap), tight oil and gas accumulation (from source rock to non-trap), and shale oil and gas accumulation within source rock were further carried out, and then, the possible types of oil and gas reservoirs in the whole petroleum system can be inferred (Fig. 1.17). There are 3 categories 6 subcategories and 15 types of oil and gas reservoirs in the WPS according to

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Fig. 1.17 Difference and correlation between conventional and unconventional oil/gas reservoirs and genetic classification (Pang et al. 2021c)

the spatio-temporal combination of different functional elements and hydrocarbon thresholds (Pang et al. 2021c). (1) The first category (I) is the conventional reservoirs accumulated dominantly driven by buoyancy and distributed in F-HDF. They have the basic characteristics of high point convergence, high cap rock sealing, high pore enrichment, high pressure accumulation and source-reservoir separation. Firstly, according to the genetic mechanism and morphological characteristics of traps, conventional oil and gas reservoirs are further divided into structural oil and gas reservoirs and lithologic stratigraphic or subtle oil and gas reservoirs; Then, according to the genetic characteristics of traps, they are divided into five types: anticline oil and gas reservoir, fault block oil and gas reservoir, stratigraphic oil and gas reservoir, lithologic oil and gas reservoir and special closed oil and gas reservoir; Finally, it can be further subdivided according to the trap morphological characteristics or styles. (2) The second category is formed dominated by non-buoyance or intermolecular force in C-HDF and B-HDF. It has the basic characteristics of low sag convergence, low position inversion, low pore accumulation, low pressure stability, close proximity to source, continuous accumulation, wide distribution, low reservoir and low production. Firstly, tight oil and gas reservoirs can be divided into two subcategories: tight unconventional oil and gas reservoirs outside the source and tight oil and gas reservoirs inside the source according to the relationship between tight oil and gas reservoirs and source rocks; Then, according to the genetic mechanism of tight reservoir, it can be divided into five types: tight conventional oil and gas reservoir, tight deep basin oil and gas reservoir, tight superimposed continuous oil and gas reservoir, coalbed oil and gas reservoir and shale oil and gas reservoir; Finally, it can be subdivided according to the morphological style of tight oil and gas reservoir distribution.

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(3) The third category of reservoirs is dominated by the stress and distributed in the reformed hydrocarbon dynamic field (R-HDF). They show basic geological characteristics of medium alteration, porosity/permeability anomaly, component alteration, oil/gas anomaly, occurrence alteration, temperature/pressure anomaly, and so on. Firstly, according to the reformed content, the reformed oil and gas reservoirs are divided into two subcategories: medium reformed oil and gas reservoirs and component reformed oil and gas reservoirs; Then, according to their genetic mechanism, they are divided into five types: fault reformed oil and gas reservoir, unconformity reformed oil and gas reservoir, fault unconformity combined reformed oil and gas reservoir, biodegradation reformed heavy oil Liqing, thermal cracking reformed dry gas reservoir and so on. Finally, it can be further subdivided according to the shape or style after transformation.

1.4.2 Evaluation of Total Potential Oil/Gas Resources in the Global Petroleum System How much oil and gas are there on earth? This problem has long puzzled oil and gas geologists and oil and gas explorers, and thus affects the global energy transition and strategic decisions. To solve this problem, it is necessary to integrate all the petroleum systems in the sedimentary basins above the Earth into a larger global petroleum system. The global petroleum s system here is defined as the sum of oil and gas reservoirs formed in the global sedimentary basins, their associated controlling factors, migration driving forces and accumulation processes, their formation and distribution are controlled by paleoclimate, palaeogeography, paleo-environment changes and coupling, and the interaction of atmosphere, hydrosphere and lithosphere, so it is difficult to study. Although the USGS, IEA, EIA, BP and other agencies regularly or irregularly release the estimate results of global oil and gas resource (USGS 2021; EIA 2021; BP 2020), however, these are only recoverable resources with current technology, not the total potential oil and gas resources with current and future technology, so the published estimate results change from year to year, and increase as science and technology continue to advance. Since 2000, total global oil and gas resources have increased from 8300.5 × 108 t oil equivalent to 258,300 × 108 t oil equivalent, a total increase of 31 times (Zhou 2010). Based on the oil and gas threshold control model, this book quantitatively evaluates the global oil and gas resources of three types (conventional type, tight type, shale type) and three levels (current recovery, current ~ 50%, 50 ~ 100%). The results show that the total amount of oil and gas generated in the world is 141.84 × 1012 t oil equivalent, of which 74.3% are dispersed or destroyed, 7.7% are accumulated but immovable, and 18% are accumulated to constitute the total potential resources: Current resources are about 1.4%, replacement 7.6%, prospective 9.0%. The total global oil and gas resources are about 23.84 × 1012 t oil equivalent (Fig. 1.18a), if

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Fig. 1.18 The global total residual potential of oil and gas resources can support sustainable development of human society for 3000 years if all of them developed in current production rate

100% of the remaining realistic, replacement and prospective resources are recovered, they will support 202, 1482 and 3019 years of sustainable development based on the current consumption level. Of the remaining oil and gas resource potential, conventional oil and gas, tight oil and gas, shale oil and gas account for 8.8%, 48.7% and 42.5% respectively (Fig. 1.18b). There is no shortage of oil and gas resources on earth, but we lack reliable technologies to extract them efficiently, quickly, safely and green.

1.4.3 Development of Remained Oil and Gas Resources in Global Petroleum System Where is the potential oil and gas going in the future? At the turn of the century, Science magazine listed the replacement of oil and gas as one of the 125 biggest challenges facing humanity in the twenty-first century (Kennedy and Norman 2005). Based on the quantitative evaluation results of the global petroleum system, we found that unconventional and deep oil and gas are the main direction of future development. (1) The remaining oil and gas resources are mainly distributed in unconventional tight media. In the global realistic oil and gas resources (Fig. 1.19a), conventional oil and gas is the most abundant (9555 × 108 t), followed by tight oil and gas (7109.6 × 108 t) and shale oil and gas (5113.9 × 108 t). Their proved rates are about 48.1%, 2.4% and 0.7%, respectively; The realistic remaining resources from high to low are tight oil and gas (6939 × 108 t), shale oil and gas (5080 × 108 t) and conventional oil and gas (4963 × 108 t). The realistic remaining recoverable unconventional oil and gas resources (tight + shale) are 2.42 times larger than conventional oil and gas,

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Fig. 1.19 Global (a) and Chinese (b) realistic oil and gas resource, composition and distribution characteristics based on hydrocarbon threshold study and whole petroleum system evaluation

accounting for 71% of the total realistic remaining resources, while conventional oil and gas resources are only about 29%. Therefore, this evaluation shows that the future development direction of oil and gas resources is the unconventional oil and gas resources. (2) The remaining oil and gas resources are mainly distributed in deep and ultra deep areas. The world’s proven oil and gas (Fig. 1.19b) are mainly distributed in shallow and middle-depth formations with small burial depths: More than 87% of the discovered 52,926 oil and gas reservoirs are distributed over 4000 m; More than 90% of the proven oil reserves (168.6 × 108 t) in six representative petroleum basins in China are distributed in formations less than 3000 m deep, more than 65% of the proven gas reserves (92.8 × 108 t oil equivalent) are found at depths ranging from 2000 to 5000 m. The number and reserves of oil and gas reservoirs found in the middle and shallow layers are far more than 50%, and the actual amount of hydrocarbon generated and discharged from the source rock is far less than 50%, indicating that the development potential is limited. However, although the number of oil and gas reservoirs and oil and gas reserves found in deep and ultra deep (> 4500 m) fields are few, the oil and gas generated and discharged from the source rock in this field is far more than 50%. These show that the remaining resource reserves to be further proved in the deep layer are much higher than those in the medium and shallow layer, which is the main direction of future development. (3) The remaining oil and gas resources are mainly distributed in areas that can be touched by high and new technologies in the future. In the past 200 years, mankind has commercially extracted 0.4 × 104 t oil and gas equivalent from the earth; Under the existing technical conditions, the average recovery factor is about 8.4%. If these technologies can be fully applied without considering the commercial effect, the maximum oil and gas equivalent they can produce can reach 2.18 × 104 t; If the technical level of human oil and gas exploitation can make the recovery rate reach 50%, the oil and gas equivalent that can be recovered can reach 12.93 × 104

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t; If the technical level of human oil and gas exploitation can make the recovery rate reach 100%, the oil and gas equivalent that can be recovered can reach 25.84 × 104 t. These reflect the direct corresponding relationship between the technical level and the recoverable gas resources: the higher the technical level, the more oil and gas will be produced; Otherwise, the opposite is true (Fig. 1.19c). Oil and gas resources are non renewable resources. With our continuous exploitation, their surplus will only be less and less; With the increasingly complex geological conditions, the difficulty of oil and gas exploitation is increasing. With the increase of cost reduction and unbearable, mankind will turn to other renewable energy sources, and it is impossible to produce 100% of the oil and gas; In addition, mankind may find chemical raw materials or other more valuable uses for oil in the future, and the technology of oil and gas exploration and exploitation will continue to develop.

1.4.4 Development Prospecting of Natural Gas Hydrate in Global Petroleum Systems Can nature gas hydrate constitute the main energy source of global development in the future? Since 1973, the former Soviet Union scholars first evaluated the global hydrate resource potential as high as 3 × 1018 m3 (Trofimuk et al. 1973), human beings have high hopes for this high-density, low-carbon and clean energy, which is regarded as a new energy to replace conventional oil and gas to solve future energy shortages (Arthur 2011; Wadham et al. 2012). Since the turn of the century, The United States (Booth et al. 1996), Japan (Konno et al. 2017), Canada (Hancock et al. 2005), India (Sain and Gipta 2012), Korea (Ning et al. 2012) and China (Yang et al. 2015) launched research projects on natural gas hydrate, and the number of hydrate papers published each year is also increasing rapidly. So far, at least 29 groups of scientists have evaluated the potential of global hydrate resources, and the evaluation results of different scholars vary widely, with the biggest difference being more than 15,000 times (Fig. 1.20). Based on the three methods of oil and gas threshold reservoir control model, we quantitatively evaluated that the change of global natural gas hydrate resources is (15 ~ 63) × 1012 m3 , accounting for 1.6 ~ 6.4% of the total global conventional oil and gas resources, with an average of less than 5%. Therefore, it is considered that they are unlikely to constitute the main energy in the future. Refer to relevant literature for detailed discussion (Pang et al. 2021d). (1) The NGH potential resources amount obtained by mass balance method is less than 5% of conventional oil and gas resources. By analyzing the geological and geochemical characteristics of 13 hydrate reservoirs discovered worldwide, it is found that methane gas in NGH comes from the degradation of sedimentary organic matter, just like conventional and unconventional oil and gas. Through geological analogy, it is found that the formation conditions of natural gas hydrate are the same as those of conventional oil and gas reservoirs. Except that the hydrate is formed

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Fig. 1.20 Estimated global NGH resources by trend analysis and compared with other results. a Historical global estimates of NGH potential resources are added to the figure, which show the overall trend of resource decline over time, superimposed with the fitted statistical trend, uncertainty range of predicted resource estimation and statistical trend analysis based on prediction future estimation and model value of NGH in situ in 2020 and 2050 (a1, a2). The model value of NGH in situ resource estimated by volume method is represented by red star (b), and the mean RIP value estimated by mass balance method is represented by pink dot (c). The predicted historical resource distribution of NGH resource of GIP in Shenhu area of south China Sea from 1999 to 2017 is plotted, and the brown dotted line (d) shows the learning curve. b The proportion of global recoverable NGH resources to the total amount of four conventional oil and gas resources is shown in the pie chart on the upper right

in the phase equilibrium environment of high pressure and low temperature, other formation conditions such as oil and gas source, reservoir, migration and accumulation and preservation are the same as those of conventional oil and gas reservoirs, It is recognized that the distribution of natural gas and oil is dominated by conventional buoyancy, which is a special form of natural gas and oil. Finally, based on the principle of material balance, the quantitative relationship model and material balance equation between hydrate resources and normal oil and gas resources and heavy oil asphalt resources are established. When the geological parameters such as conventional oil and gas resources (oil and gas in the trap) and heavy oil asphalt resources (oil and gas in the reformed trap) are known, Natural gas hydrate resources (oil and gas volume in special traps) are derived between (11 ~ 46) × 1012 m3 , about 1.9 ~ 4.2% of the total global conventional oil and gas resources. (2) Based on the previous 29 groups of evaluation results and trend analysis method, it is predicted that the global hydrate resources are less than 5% of conventional resources. The evaluation results of the decreasing potential of global hydrate resources reflect that with the accumulation of geological survey data and

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the deepening of understanding, the evaluation results are more and more close to reality. A large number of survey results found that hydrate could not form in shallow water with burial depth less than 500 m, resulting in the reduction of 81% of the favorable distribution area determined earlier; The new understanding that all natural gas in hydrate comes from sedimentary organic matter leads to the further reduction of the previously determined favorable distribution area and is limited in the sedimentary basin; The new understanding of the genetic mechanism of high pressure and low temperature of natural gas hydrates shows that they can only be formed and distributed in deep marine environment, polar ice sheet area of the earth and plateau permafrost. The recognition of these two aspects has led to the reduction of the favorable distribution area confirmed earlier by 50%; It is found that most natural gas hydrates are dispersed in shallow source rocks, the hydrate saturation is less than 10%, and the natural gas hydrate that can constitute effective resources is less than 12%; In addition, hydrate cannot be commercially exploited under the existing technical conditions. The simulation experiment shows that the commercial recovery of hydrate in the future will not exceed 30%. These show that it is feasible and effective to predict the potential commercially exploitable hydrate resources based on the global hydrate resources and their change trend obtained by 29 groups of scientists earlier. According to the change trend, the corresponding recoverable hydrate resources in 2050 are determined to be between (41 ~ 91) × 1012 m3 , about 3.2 ~ 6.4% of the total global conventional oil and gas resources. (3) Based on volume method and geological analogy method, the predicted global hydrate resources are less than 5% of conventional oil and gas resources. After a detailed analysis of the geological and geochemical characteristics of natural gas hydrate reservoirs in Shenhu exploration area in the South China Sea with a large number of exploration wells, a high degree of exploration and the longest trial production of vertical and horizontal wells, we compared the relevant research results and parameters to all sedimentary basins in the world, With the help of volume method and Monte Carlo simulation technology, the recoverable resources of global natural gas hydrate are quantitatively evaluated (22 ~ 63) × 1012 m3 , about 1.6 ~ 4.4% of the total global conventional oil and gas resources.

1.5 Summary Human commercial exploration, development and utilization of oil have been going on for more than 150 years, which can be roughly divided into four stages: exploration by oil and gas seepage, exploration by trap structure, exploration by conventional oil/gas theory and exploration of unconventional oil/gas theory. At present, the theory of petroleum system has encountered great challenges in guiding practice and needs to be improved and developed. The concept of whole petroleum system provides a new idea for oil and gas exploration and development under complex geological conditions, and it is of great practical significance to petroleum study

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and exploration: It is beneficial to establish a unified genetic model of conventional and unconventional reservoirs and promote the development of petroleum geology theory; It is also beneficial to reveal multi-source, multi-dynamic and multi-element combination of reservoir formation to develop new technology for prediction and evaluation of diversity oil and gas resources distribution; It is helpful to study the law of hydrocarbon generation, expulsion, migration, accumulation and dispersion based on the mass balance, objectively and scientifically evaluate the total resource amount and potential distribution of oil and gas, and direct future development. Supported by the National Key Basic Research Program of China (973) and other projects, the quantitative evaluation method of the whole petroleum system has been formed through nearly 20 years of efforts. Based on the analysis of drilling results of 80,762 oil and gas reservoirs in 12,237 exploration Wells in six representative basins in China, the comparative analysis of conventional and unconventional oil and gas reservoirs in five oil and gas basins in North America, and the statistical analysis of the differences of 52,926 proven oil and gas reservoirs in 1186 basins worldwide, it is found that there are ten hydrocarbon thresholds in the whole petroleum system, and three correlative models of controlling oil/gas reservoirs formation have been established: The first model is about hydrocarbon migration and a new resource evaluation method is put forward; The second is about oil/gas accumulation and a new method for identifying resource type is proposed; The third about oil/gas distribution and a new technique for predicting favorable areas/zones has been developed. The application results of the new theory and new technology show that the conventional and unconventional reservoirs could be divided into 3 category 15 types and 49 styles, which are mainly distributed in the formation areas ranging from depth of 4500– 13,000 m; The global oil/gas resource potential is about 2.5 trillion tons, and 90% of the remaining resources are distributed in deep and tight media, which can sustain human development for more than 200 years if all been developed; The potential resource of natural gas hydrate account for less than 5% of the total conventional oil/gas, so it is unlikely to become the main energy source for human development in the future. It has also been applied to 16 exploration areas in 8 basins, and has played an important guiding role in the deployment of 560 exploration Wells for oil companies, adding 4.3 billion tons of oil equivalent reserves, and the success rate of exploration Wells has increased by more than 20% on average, illustrating the significance of quantitative study of whole petroleum system.

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Chapter 2

Unified Classification of Oil and Gas Reservoirs in the WPS

New Understanding: There are a lot of correlations between conventional and unconventional oil and gas reservoirs, such as their oil and gas come from the same source rocks, the oil and gas reservoirs are distributed in geological strata with the same ages, coexisting in the same petroliferous basins, confined in the same hydrocarbon accumulation systems, and enriched with oil and gas in the same reservoir layers. There are also a lot of differences between conventional and unconventional oil and gas reservoirs, such as the differences in hydrocarbon compositions, reservoir lithology and qualities, spatial relations to source rocks, distributions in geological settings, and reservoir formation mechanisms. By studying the mechanisms underlying these correlation and differences, a unified genetic classification scheme is proposed to address these major correlations and differences between the conventional and unconventional oil and gas reservoirs, and then all of the oil and gas reservoirs are classified into 3 categories, 6 subcategories, 15 types and 49 styles.

2.1 Introduction and Issue The exploration and exploitation of tight oil and gas reservoirs and shale oil and gas reservoirs in North America since the 1980s have been considered as the most important event in the history of petroleum geology (Masters 1979; Zagorski 1988; Law 2002), which has changed the market structure of global oil/gas supply and deepen our understanding on the formation and distribution of oil and gas reservoirs. The global oil and gas exploration and exploitation has expanded from anticlinal traps to continuous accumulations in deep basin centers and almost to any place where oil and gas reservoirs were once considered impossible to form and distribute (Masters 1979; Selley 1998; Law and Curtis 2002). These unconventional oil/gas resources, including tight oil/gas resources (Rose et al. 1986; Holditch 2006; Ghanizadeh et al. 2015), coal-bed methane resources (Rightmire et al. 1984; Gunter et al. 1997; Moore 2012), shale oil/gas resources (Claypool 1998; Curtis 2002), heavy oil or oil sands © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_2

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resources (Rubinstein et al. 1977; Richard et al. 2007), greatly contributed to the growth of global petroleum reserves and production in recent 20 years. Besides, the discovery and exploration of gas hydrate, which is considered as a kind of prospective fuel resource by many scholars (Kim et al. 1987; Collett 1993; Clennell et al. 1999), also promotes the exploration and development of oil and gas resources. The resource potential of unconventional oil and gas is estimated to be 4–8 times of conventional oil and gas. It is of importance and significance to propose a unified genetic classification scheme of oil and gas reservoirs for better understanding of differences and correlations between conventional and unconventional oil and gas accumulations, and further improving both theoretical and practical of petroleum industry. The past and current classifications of oil and gas reservoirs have only considered the differences and correlations among conventional oil and gas reservoirs. The early theory about oil and gas accumulations in traps as a function of buoyancy (White 1885; Hubbert 1953) contributed to many successful hydrocarbon explorations for conventional resources. Levorsen (1956) proposed the first classification of oil and gas reservoirs based on different types of traps, emphasizing the control of buoyancy and trap structures on the formation and occurrence of oil and gas accumulations. Later, it was amended and improved to include nonstructural traps. Halbouty (1972) considered a variety of nonstructural traps in his classification based on basic geological controls, such as lithology variation, strata pinch out, unconformities, and paleo-geomorphology. In the 1980s, advances in organic geochemistry added another dimension to the classification of oil and gas reservoirs, bringing in the concepts of “source-controlled hydrocarbon distributions” (Tissot and Welte 1978) and “petroleum system” (Magoon and Dow 1994). Cap rock properties and sealing forms were also taken into account in the classification of traps and oil and gas reservoirs (Milton and Bertram 1992). Beaumont et al. (1999) classified oil and gas reservoirs into sedimentary trap reservoirs, diagenetic trap reservoirs, fluid trap reservoirs, etc. All these classifications assume buoyancy as the major driving force for oil and gas migration and accumulation, they are not suitable for unconventional oil and gas accumulations for which the buoyancy is not the major driving force and reservoirs distribution is also not controlled by traps (Galley 1958; Kinnison 1971; Keller and Thomaidis 1971). There are confusions when using the conceptual terms of conventional and unconventional oil and gas reservoirs if the differences and correlations between them are not clearly understood. The term “unconventional oil and gas reservoirs” generally refers to those hydrocarbon accumulations differing from conventional ones, and it is not a formal scientific term with a clear and precise definition. Its application in literature can be confusing. For example, bitumen is called as a unconventional hydrocarbon resource (Hein 2017), but its reservoir formation and distribution are related to buoyancy and traps. Gas hydrate is also considered as an unconventional resource, while its formation and distribution are also related to buoyancy and a special type of trap with “high pressure and low temperature” (Collett 1993; Clennell et al. 1999). Deep-basin oil/gas reservoir (Masters 1979) refer to oil and gas accumulations in tight sandstone strata located in deep center of a basin, and it was

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titled with other names by different scholars in studying different oil and gas reservoirs, including syncline reservoir (Wu et al. 2015), basin-centered reservoirs (Rose et al. 1986), source-contacting reservoirs, tight reservoirs (Spencer 1985), continuous reservoirs (Schmoker and Oscarson 1995), etc. It is inappropriate to name all oil and gas reservoirs controlled by non-buoyancy forces as unconventional oil and gas reservoirs. The potential resource of conventional oil and gas reservoirs around the world is much smaller than that of the unconventional oil and gas reservoirs. For instance, 92% oil and gas reserves of Tarim Basin in China discovered since 2010 are from unconventional oil and gas reservoirs. In fact, in addition to buoyancy, other forces such as fluid pressure, oil/gas expansion force, hydro-dynamics, capillary pressure, molecular diffusion and some others also make contributions to oil and gas migration and accumulation. Therefore, it is very important to establish a unified genetic classification scheme for all oil and gas reservoirs to improve our understanding of differences and correlations among these various types of oil and gas reservoirs.

2.2 Research Method and Technology In this study, unconventional oil and gas reservoirs are defined as oil and gas accumulations not majorly controlled by buoyancy, and they have various occurrences in the nature according to their formation mechanisms. The differences and correlations between conventional and unconventional oil and gas reservoirs were elucidated by analyzed and studied all kinds of oil and gas reservoirs which are collected from different petroliferous basins with high exploration and exploitation level. Then, a unified genetic classification scheme is proposed, so as to provide theoretical basis for the prediction and evaluation of various oil and gas reservoirs in petroliferous basins.

2.2.1 Research Sites and Data Collection Six representative basins in China, including the Tarim Basin, Junggar Basin, Sichuan Basin, Ordos Basin, Bohai Bay Basin, Songliao Basin, were selected in this work (Fig. 2.1). Differences and correlations between discovered conventional and unconventional oil and gas reservoirs in these basins, and their genetic mechanisms, were studied. The fundamental reasons for selecting these basins to focus our research are as following reasons: Firstly, the conventional and unconventional oil and gas accumulations both are widely developed in them and have the highest oil and gas exploration degree in China. Secondly, they have the largest proved reserves (account for 76.9% of reserves in China), the greatest resource (account for 62.6% of resource in China), and the best prospect among all the petroliferous basins in China. Thirdly, their geological conditions are complex, and are representatives for all petroliferous

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Fig. 2.1 Distribution of major petroliferous basins in China, including the six representative basins selected in this study-the Tarim Basin, Junggar Basin, Sichuan Basin, Ordos Basin, Bohai Bay Basin and Songliao Basin, modified from literature (Pang et al. 2021a)

basins in China and the world. The geographical distribution, exploration profiles and geological characteristics of oil and gas in the six representative basins have been introduced in the relevant literature (Ministry of Natural Resources of the People’s Republic of China 2017). The drilling results of 12,237 exploration wells and 80,762 oil and gas reservoir layers in six representative basins were used to address the geological characteristics and distribution features of oil and gas reservoirs in these basins (Pang et al. 2020, 2021a). In addition, the progress of unconventional oil/gas exploration in North America in the past 30 years was investigated, and the distribution characteristics of 52,926 oil/gas reservoirs in 1186 basins around the world were analyzed as well (IHS 2010). In this way, the differences and correlations between conventional and unconventional oil and gas reservoirs, and their formation mechanisms were studied, and then a new concept of the whole petroleum system and a new unified classification scheme were put forward.

2.2.2 Research Contents and Workflow To analyze and study the geological and geochemical characteristics of various oil and gas reservoirs discovered worldwide to understand the correlations between conventional and unconventional oil and gas reservoirs. There are five aspects of main focuses, including characteristics of source rocks and their genetic relationships with the formation, distribution characteristics of conventional and unconventional oil and gas reservoirs in the same strata, same basin, same petroleum system, same reservoir layer. Based on the above work, the correlations of conventional and unconventional reservoirs are clarified.

2.3 Correlations Between the Conventional and Unconventional Oil …

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To analyze and study the geological and geochemical characteristics of various oil and gas reservoirs proved worldwide to understand the differences between conventional and unconventional reservoirs and resources. Main focuses include the dynamic mechanisms of the formation of conventional and unconventional reservoirs, the tectonic settings, lithology and reservoir properties of conventional and unconventional reservoirs, the relationships of conventional and unconventional reservoirs with source rocks, the hydrocarbon composition in conventional and unconventional reservoirs. By clarifying the correlations and differences, a unified genetic classification scheme for conventional and unconventional oil and gas reservoirs is proposed. Five steps taken to conduct research work. The first is to investigate the significant progress of conventional and unconventional oil and gas reservoirs exploration in North America in the past 30 years, and find out their differences and correlations in aspects of geological characteristics and formation conditions. The second is to analyze the oil/gas drilling results of six representative basins in China, to identify the conventional and unconventional oil and gas reservoirs, and to reveal the differences and correlations of their genetic mechanism and development patterns. The third is to illustrate differences and correlations between conventional and unconventional oil and gas reservoirs by taking six representative basins as examples, and the research results of reservoirs in other basins. The fourth is to study the inadaptability of previous classification schemes, and then put forward a new classification scheme that can be applied to both conventional and unconventional oil and gas reservoirs. The fifth is statistical analysis of the geological characteristics of oil and gas reservoirs discovered all over the world, classifying them with the new scheme, and testing the universal applicability of the new scheme.

2.3 Correlations Between the Conventional and Unconventional Oil and Gas Reservoirs Major correlations between the conventional and unconventional oil and gas reservoirs are summarized as follows.

2.3.1 Conventional and Unconventional Oil and Gas Both of Fossil Resources During the past several decades, petroleum geologists took great efforts on investigating the origin of hydrocarbons in the world (Tissot and Welte 1978). It is widely accepted that oil and gas in both conventional and unconventional reservoirs are formed by transformation of sedimentary organic matters in source rocks during

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burial and thermal maturation. Thus, these oil and gas share very similar compositions and stable carbon isotopic characteristics (Rowe and Muehlenbachs 1999; Dixit et al 2019). Figure 2.2 illustrates the stable carbon isotopes distributions in conventional and unconventional oil and gas formed from organic matters (δ13 C ≤ − 30‰), as well as the distributions in carbon compounds originated by inorganic reactions (δ13 C > − 30‰). Oil and gas formed from organic matters by biodegradation (δ13 C ≤ − 55‰) and by thermal degradation (δ13 C = − 55 to − 30‰) can also be identified by their stable carbon isotopes, implying that organic-rich source rocks make contributions to the formation of oil and gas reservoirs. Oil and gas expelled from source rocks are favorable for conventional and tight reservoir formation, while oil and gas retained in source rocks are favorable for shale oil and gas reservoir formation (Craig et al. 2018). The Upper Paleozoic Carboniferous and Permian coal-bearing black mudstones in the Ordos Basin in China has been considered as the most important natural gas source rocks in the basin, geochemical studies have proved that natural gases in conventional reservoirs, tight reservoirs and coal-bed reservoirs in the basin are all derived from these source rocks (Zou et al. 2013; Zhao et al. 2014). Hill et al. (2007) analyzed geochemical components of oil and gas in reservoir layers in the Fort Worth Basin in America and geochemical components of extracts from the Barnett Shale, and suggested that the Barnett Shale is the primary source rocks for the oil and gas system in the Fort Worth Basin. Although oil and gas may accumulate in either conventional or unconventional reservoirs, they are associated with the same original source rocks. The West Canadian Basin, a vast petroliferous sedimentary basin in Canada, contains one of the world’s largest reservoir of natural gas (Porter et al. 1982; Creaney et al. 1994), many types of oil and gas reservoirs, including conventional oil and gas, tight oil and gas, oil sand, coal-bed methane and shale oil and gas are discovered in it. The Duvernay Formation in the West Canadian Basin has long been identified as the original source rocks for the conventional oil and gas in the Leduc reefs surrounding it, and the formation is also an important play for shale gas production itself (Creaney et al. 1994; Osadetz et al. 2018).

2.3.2 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Age Strata Resource evaluation results for petroliferous basins in China show that the strata rich in conventional oil and gas tend to have more unconventional oil and gas reservoirs (Fig. 2.3a). The conventional oil and gas reservoirs widely exist in strata formed since the Sinian period. There is an overall decreasing trend with increasing age of strata, and Cenozoic and Cretaceous strata accumulate more conventional oil and gas resources compared to other older strata. Unconventional oil and gas resources are also discovered in these strata and are distributed in petroliferous basins of China, while resource abundance of different types of oil and gas resources vary greatly in strata with different geological ages and the total amount tends to decrease with

2.3 Correlations Between the Conventional and Unconventional Oil …

55

Fig. 2.2 Correlations of stable carbon isotope distribution in oil and gas from conventional and unconventional hydrocarbon resources and their identification of genetic mechanisms. The point A is approximately of − 30‰, and point B is about − 55‰

increasing of geological age. Cenozoic and Cretaceous strata own the most abundant unconventional oil and gas resources. For the Mesozoic and Cenozoic strata of younger strata, the conventional oil and gas resources is almost equivalent to or slightly larger than the unconventional resources. For strata older than Cenozoic, the unconventional oil and gas resources tend to be equivalent or larger than the conventional oil/gas resources. The resource ratio of unconventional to conventional generally increases with increasing formation age. Ratios of conventional to unconventional resources for Cenozoic and Cretaceous are 0.715 and 0.714, respectively, while in Devonian and Silurian, the ratios are 8.593 and 10.528, respectively. Therefore, it is inferred that the formation of conventional and unconventional reservoirs is correlated in geological ages.

56

2 Unified Classification of Oil and Gas Reservoirs in the WPS

Fig. 2.3 Correlations of reservoir ages and proved reserves for conventional and unconventional oil and gas resources. a Distribution of conventional and unconventional oil and gas resources in strata with different geological ages in China (data are from Center for Strategic Research of Oil/ gas Resources 2016; Jia et al. 2012; Pang et al. 2012a; Zheng et al. 2018). b Distribution of proved conventional and unconventional oil and gas reserves in strata with different geological ages in the world (Tian et al. 2014; Wang et al. 2017)

Figure 2.3b shows the distribution of oil and gas reserves in different geological strata for conventional and unconventional resources in the world, indicating that they are genetically related. The strata with more proved conventional reserves tend to have more proved unconventional reserves. Most of the proved conventional and unconventional oil and gas reserves in the world are found in Tertiary, Cretaceous and Jurassic. The amount of the discovered oil and gas resources in other strata are relatively small, showing a general decreasing trend with increasing geological age. For conventional oil and gas reserves, the percentage of gas reserve in the total reserves is higher in older strata. As for the distribution of unconventional oil and

2.3 Correlations Between the Conventional and Unconventional Oil …

57

gas reserves, the percentages of different types of oil and gas reserves vary greatly in different geological strata.

2.3.3 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Basins Conventional and unconventional oil and gas reservoirs generally occur in the same basins. Conventional oil and gas reservoirs tend to form in the shallow area of a petroliferous basin, while tight oil and gas reservoirs form in the deep area. Depth zones feasible for formation and distribution of unconventional oil and gas reservoir are much wider and larger than those for conventional oil and gas reservoirs. There are two reasons for them: one is that shale oil and gas reservoirs and coal-bed methane can exist in source rocks within a broad Ro range from 0.2 to 3.5%, and another is that conventional oil and gas reservoirs formed in area above the Buoyance-driven Hydrocarbon Accumulation Depth (BHAD, Pang et al. 2021a) can be transformed to unconventional oil and gas reservoirs by deeper burial depth. Figure 2.4a illustrates the distribution of conventional and unconventional oil and gas reservoirs in the Jungar Basin in Western China. Heavy oil reservoirs were formed in western margin of the basin with strong tectonic activities, which has an area of 11 × 103 km2 , a depth of less than 2500 m and proved reserve of 0.3 × 109 tons, and the destroyed hydrocarbon amount is estimated to be 0.05 × 109 tons. Two shale oil reservoirs were discovered in Permian Strata in the Jimusaer Sag and Mahu Sag in the basin, with daily productive yield of 116.8 tons and 38 tons, respectively. The distribution area of both reservoirs has been predicted to exceed 31 × 103 km2 , and proved reserve exceed 1.1 × 109 tons. Conventional oil and gas reservoirs were also discovered in traps in the Junggar Basin at depth less than 2800 m, with proved reserves of 2.2 × 109 tons. Figure 2.4b shows the distribution of conventional and unconventional oil reservoirs in the Songliao Basin in eastern China. Heavy oil reservoirs were discovered in the western slope of the basin with depth of less than 1500 m and an area of 5 × 103 km2 . Shale oil reservoirs are distributed in the Qingshankou source rocks, located in the Qijia-Gulong Depression and the Sanzhao Sag with a total area of 16 × 103 km2 and proved reserves of 1.4 × 109 tons. Tight oil reservoirs were formed in tight sandstones adjacent to the source rock layers, with a combined area of 13 × 103 km2 and proved reserves of 0.5 × 109 tons. Conventional oil reservoirs were found in the Daqing Anticline and other traps in the basin, having proved reserves of 5.8 × 109 tons. Figure 2.4c shows the relationships of the formation and distribution for the conventional and unconventional oil reservoirs in these petroliferous basins. In general, all kinds of oil and gas reservoirs in the basin are genetically related: conventional oil and gas reservoirs are formed and distributed in the shallow strata, tight oil and gas reservoirs are formed and distributed in the deep strata, heavy oil or bitumen are mainly distributed at shallow margins of the basin by uplift of other

58

2 Unified Classification of Oil and Gas Reservoirs in the WPS

Fig. 2.4 Correlations of formation and distributions between conventional and unconventional oil and gas reservoirs in a petroliferous basin. a Distribution of conventional and unconventional oil and gas reservoirs in the Junggar Basin, China (Zhang et al. 2014; Hu et al. 2018). b Distribution of conventional and unconventional oil and gas reservoirs in the Songliao Basin, China (Zhang et al. 1999; Feng et al. 2003; Li 2015). c A simplified model for the formation and distribution pattern of conventional and unconventional oil and gas reservoirs in a petroliferous basin

types of oil accumulations, and cracked gas reservoirs distributed in the deep strata with high temperature and pressure.

2.3.4 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same Layers Conventional and unconventional oil and gas reservoirs co-exist in the same reservoir layers. Figure 2.5 shows the coexistence of conventional oil and gas reservoirs and unconventional oil and gas reservoirs in the Putaohua Formation in the Songliao Basin, the largest petroliferous continental basin in the world. Conventional oil and gas reservoirs are formed in the highly porous and permeable sandstones at the top of the central uplift belt (Sun et al. 2007), oil and gas are derived from the underlying Qingshankou source rocks. The reservoir layers are sealed by the Nenjiang Formation at a depth of less than 2000 m (Qiang and McCabe 1998; Ryder et al. 2003). Unconventional oil reservoirs are discovered in the same sandstone layer with low-porosity and low-permeability in the deeper west of the central uplift belt in the basin, closing to the Qingshankou source rocks and not controlled by traps or cap

2.3 Correlations Between the Conventional and Unconventional Oil …

59

Fig. 2.5 Co-existing of conventional oil and gas reservoirs and unconventional oil and gas reservoirs in Cretaceous sandstone of the Putaohua Formation in the Songliao Basin within different depth ranges. Porosity data on the right are based on 14,853 samples from 401 wells. Each data point is the average porosity of the samples in a 250-m interval range (modified from Pang et al. 2021a)

rocks. The co-existence of both types of oil reservoirs in the same reservoir layer were also found in other basins. For example, the Silurian Clinton-Medina-Tuscarora sand body in the Appalachian Basin has decreasing porosity and permeability from the east to the center of the basin. The strata with high-porosity and high-permeability in the east are dominated by conventional oil and gas reservoirs and the sandstone layers with low porosity and low permeability in the basin center primarily develop tight oil and gas reservoirs (Ryder 1998; Law 2002). Thus, the tectonic settings of reservoir layers and their relationship with source rocks in a basin can be used to predict the distribution of different types of oil and gas accumulations. In some cases, transition of lithofacies also leads to change of oil and gas reservoirs type, e.g., a transition from sandstones to fine-grain rocks would favor unconventional shale oil and gas reservoirs over conventional reservoirs. The Halo light oil play in the Cretaceous Cardium reservoir in the West Canada Sedimentary Basin is one such example (Chen and Osadetz 2013; Clarkson and Perderson 2011). Conventional and unconventional oil and gas reservoirs can also co-exist within the same source rock, which act as a source rock and also a reservoir layer. Figure 2.6a shows the difference and correlation of porosity and permeability between conventional and unconventional oil and gas reservoirs, including conventional trap oil and gas reservoirs (I), unconventional tight oil and gas reservoirs (II), unconventional ultra-tight oil and gas reservoirs (III) and reformed oil and gas reservoirs (IV) dominantly by fractures (IV1 ) and by dissolution (IV2 ). Figure 2.6b illustrates coexistence of the reformed gas reservoirs, tight gas reservoirs and shale gas reservoirs within the Silurian Longmaxi Shale in the Sichuan Basin in China. The Silurian Longmaxi shale is an effective source rock in the Sichuan basin, and has a stable thickness of 15–30 m and TOC > 2%. Shale gas resources in the Longmaxi shale are abundant (Pu et al. 2010; Chen et al. 2014), and the technically recoverable shale gas reserve is reported as 3.71 × 1012 m3 (EIA 2013; Jiang et al. 2017). The area underwent differential tectonic deformations (Zeng et al. 2013; Chen et al. 2014), showing various gas enrichment characteristics with different ratios of conventional

60

2 Unified Classification of Oil and Gas Reservoirs in the WPS

Fig. 2.6 Relationship of porosity and permeability for different oil and gas reservoirs types. a Porosity and permeability of different types (colors) of oil and gas reservoirs. b Porosity and permeability of different reservoir types coexisting within the Silurian Longmaxi shale rock in the Sichuan Basin, China. I—conventional reservoirs with high porosity and high permeability, II— tight reservoirs with low porosity and low permeability; III—shale reservoirs with low porosity and very low permeability, IV1—reformed reservoirs by faults with low porosity and high permeability, dominantly by stress and fractures; IV2—reformed reservoirs by unconformity with high porosity and low permeability, dominantly by fluids and dissolution

to unconventional gas (Wu et al. 2011; He et al 2017). Similar examples can be found in other basins, e.g., the Marcellus shale in the Appalachian Basin, North American. Natural fractures in the shale enhance permeability and thereby result in high gas flow from the improved shale reservoir (Schmoker 1981; Davies 1989; Lee et al. 2011). Fractures are common in both conventional and unconventional reservoirs. There are 3483 known accumulations in fractured reservoirs worldwide, and 1826 of those are associated with shales, accounting for over 50% of the total number of oil and gas accumulations (IHS 2010; IEA 2016).

2.3.5 Conventional and Unconventional Oil and Gas Reservoirs Both in the Same PS A set of effective source rocks and the spatial assemblages of conventional oil and gas reservoirs derived from these source rocks are defined as a petroleum system (Magoon and Dow 1994), however, this concept can be extended to all kinds of reservoirs, where both conventional and unconventional oil and gas reservoirs coexist within a petroleum system. Figure 2.7 illustrates the distribution of conventional and unconventional oil and gas reservoirs in such a petroleum system, e.g., the Zhanhua

2.3 Correlations Between the Conventional and Unconventional Oil …

61

Sag petroleum system of the Bohai Bay Basin in China. Oil and gas in both conventional and unconventional reservoirs in this system are primarily sourced from the deep-buried Es3 -Es4 source rocks (Shi et al. 2005). The conventional oil and gas reservoirs, occurring at depth of less than 3230 m, are formed in sand reservoir layers with high porosity and high permeability covered by cap rocks. The unconventional oil and gas reservoirs are found in sand reservoir layers with low porosity and low permeability in area deeper than 3230 m, which are continuous and adjacent to the Es3 -Es4 source rocks (Liu et al. 2013). Other than the conventional and unconventional tight reservoirs, shale oil and gas reservoirs are also found in the source rocks of the Zhanhua Sag (Liu et al. 2013; Wang et al. 2015). They are controlled by the distribution of organic-rich fine-grained strata in the basin (Ma et al. 2016; Wang and Hu 2014). As another example, the San Juan Basin in America is a typical asymmetric structural depression (Gries 1985), where stratigraphic traps occur in the shallow Cretaceous Pictured Cliffs sandstone layers (Scott et al. 1991), the Dakota tight gas reservoirs occur in the deep part of the basin, and oil and gas flows were proved in fractures in the Mancos shale above the Dakota sandstones (Richard et al. 2007; Marsour 1986).

Fig. 2.7 Correlations of conventional and unconventional oil and gas reservoirs in the Zhanhua Sag petroleum system in Bohai Bay Basin in Eastern China. Conventional and unconventional oil and gas reservoirs co-exist in the same petroleum system, and distributed in the sandstones above the BHAD and below the BHAD, respectively. The shale oil and gas reservoirs are distributed within the source rocks (E3 s3 -E3 s4 ). Each porosity data point on the right is an average value of a 100-m interval data, and these data are from 16,454 samples of 489 exploration wells (modified from Pang et al. 2021a)

62

2 Unified Classification of Oil and Gas Reservoirs in the WPS

2.3.6 All Conventional and Unconventional Oil and Gas Reservoirs Both in the Same WPS The concept of whole petroleum system (WPS) is defined as a natural system that encompasses all the oil and gas originated from organic matter in source rocks, the conventional and unconventional reservoirs and resources, the geological elements and processes involving in the formation, evolution, and distribution of these oil and gas, reservoirs, and resources (Jia et al. 2023), the conceptual model is shown as in Fig. 2.8. This concept is the inheritance and development of the classical petroleum system concept (Magoon and Dow 1994), but it is fundamentally different from its core content of “from source rock to trap” in four aspects. First, the classical petroleum system only studies the oil and gas migration and accumulation driven dominantly by the buoyancy, while the WPS study them driven by various dynamic forces, including buoyancy and non-buoyancy. Second, the classical petroleum system analyzes and research majorly problems about the formation mechanism, distribution characteristics and enrichment laws of conventional oil and gas reservoirs, while the WPS analyze and research these problems not only dealing with conventional oil and gas reservoirs but also with unconventional oil and gas reservoirs. Third, the classical petroleum system analyzes and research the migration dynamics, accumulation characteristics and distribution law of oil and gas in the reservoir layers with high porosity and permeability, while the WPS involve these problems in all different reservoir layers with different porosity and permeability. Fourth, classical petroleum system analyzes and research the formation and distribution of conventional gas reservoirs in the Hydrocarbon Free Dynamic Field (F-HDF), while the WPS analyze and research these problems not only in F-HDF, but also in Confined Hydrocarbon Dynamic Field (C-HDF) and Bound Hydrocarbon Dynamic Field (B-HDF), as well as their spatial relationships with those reservoirs formed earlier in the F-HDF. Pang et al. (2020) proposed a general unified model to clarify the correlation and difference of oil/gas reservoirs formed in F-HDF and C-HDF. The WPS provide a new theoretical guidance and technique for the prediction of oil and gas reservoirs and their distribution in complex geological conditions (Fig. 2.9). First, the WPS provides theoretical guidance for comprehensively and systematically studies on hydrocarbon generation and expulsion from source rocks during the thermal maturation of organic matter in sedimentary basins. By determining the thresholds of hydrocarbon generation and expulsion from source rock (Pang et al. 2005), buoyancy-driven hydrocarbon accumulation depth (Pang et al. 2021b), active source-rock depth limit (Pang et al. 2020) and related geological parameters, the total generated hydrocarbon amount, including those remained in source rocks and expelled from source rocks early and late can be simulated with actual geological and geochemical data about source rocks (Fig. 2.9a). Secondly, the WPS provides theoretical guidance for comprehensively and systematically evaluating the potential of different types of oil and gas resources. The total amount of hydrocarbon generated from organic matter in sedimentary basin can be divided into four parts in the WPS, including the residual hydrocarbons in source rocks, the retained hydrocarbons on the

2.3 Correlations Between the Conventional and Unconventional Oil …

63

Fig. 2.8 Conceptual model of the whole petroleum system in a petroliferous basin used to characterizing the correlations and differences between source rocks and their generated/expelled hydrocarbons, reservoir layers and cap formations, conventional reservoirs and unconventional reservoirs, shallow reservoirs and deep reservoirs, tectonic settings and reservoirs types, as well as the classic petroleum system and the whole petroleum system

pathway, the accumulated hydrocarbons in reservoir layers and the lost hydrocarbons near surface. The accumulated hydrocarbons can be divided into two parts, the potential resources of enriched and movable hydrocarbons and the worthless dispersed and unmovable hydrocarbons. After the lost hydrocarbons are determined by different methods and techniques, the potential resources in the WPS, such as shale hydrocarbon resource (shale-HCR), tight hydrocarbon resource (tight-HCR), conventional hydrocarbon resource (con-HCR), reformed hydrocarbon resource (ref-HCR), can be predicted according to the mass balance principle (Fig. 2.9b). Thirdly, the WPS provides theoretical guidance for the unified genetic classification of conventional and unconventional reservoirs. By the occurrence and genesis mechanism, oil and gas accumulations in the WPS can be divided into conventional oil and gas reservoirs and unconventional oil and gas reservoirs. There is another type of reservoirs, whose geological characteristics are similar to conventional oil and gas reservoirs but are associated with the formation mechanism of unconventional reservoirs, involving heavy oil, dry bitumen, gas hydrate reservoirs, tight trap reservoirs, etc. It is very important to reveal genetic mechanism of this type of complex reservoirs and find out their correlations with both of the conventional and unconventional reservoirs for us to create a unified classification scheme suitable for all kinds of reservoirs in the WPS (Fig. 2.9c).

64

2 Unified Classification of Oil and Gas Reservoirs in the WPS

Fig. 2.9 Original hydrocarbon amount from organic matter transformation and matter balance principle among all kinds of oil and gas amount in the whole petroleum system (WPS) of sedimentary basin. a Generated and expelled hydrocarbon amount from source rocks and their vertical distribution characteristics in petroliferous basins; b composition characteristics of hydrocarbon products from sedimentary organic matter in the WPS and their correlations with oil and gas resources; c the distribution characteristics of oil and gas resources in WPS and their correlation with conventional and unconventional oil and gas reservoirs

2.4 Differences Between the Conventional and Unconventional Oil and Gas Reservoirs There are many differences between conventional and unconventional reservoirs, and the following five aspects are the most important.

2.4.1 Conventional and Unconventional Oil and Gas Both Different in Compositions There are significant differences between conventional and unconventional oil and gas. It is widely known that conventional oil and gas resources tend to contain lighter oil and gas than unconventional oil and gas resources because the hydrocarbon migration distance from source rocks to conventional reservoirs is longer (Karlsen and Skeie 2006). Tight oil and gas reservoirs and shale oil and gas reservoirs are formed near or in the source rocks (Spencer 1985; Law 2002; Law and Curtis 2002). Hydrocarbon composition difference with respect to the distance from the source was discussed by studying preferential migration of lighter n-alkanes over heavier ones (Leythaeuser et al. 1984; Mackenzie et al. 1983). Tectonic deformation uplifting conventional oil reservoirs causes oxidation and biodegradation of oil, resulting in compositional changes such as the formation of 25-norhopane, decrease of alkane contents as well as increasing its density and viscosity (Bennett et al. 2006; Fustic

2.4 Differences Between the Conventional and Unconventional Oil and Gas …

65

et al. 2019). Tectonic deformation burying conventional oil reservoirs to deeper area causes oil cracking, e.g., heavy oil cracked into methane or liquid oil cracked into gaseous ones, and also causes other compositional changes such as decrease of hydrocarbon molecular weights, increase of diamondoid content, and triggering thermal sulfur reduction (TSR) reactions (Zhu et al. 2019). Besides, biodegradation, formation water properties and many other factors may also influence oil and gas composition. Thus, great caution should be taken when comparing oil and gas compositions in conventional and unconventional reservoirs of the WPS. It has long been realized that the oil retained in source rocks and that expelled from source rocks have different compositions. Organic matters in source rocks have great sorption capacities, and thus heavy hydrocarbon components such as asphaltene and resin tend to be retained in source rocks while light hydrocarbons are likely to be expelled out of the source rocks during primary migration (Stainforth 1990; Sandvik et al. 1992; Ritter 2003). For oils, the differences of conventional and unconventional are mainly reflected in the concentrations of saturated hydrocarbon, aromatic hydrocarbon, resin, and asphaltene (Table 2.1). Conventional oils have high contents of saturated hydrocarbon with an average value of 55.8%, while tight oils have high concentrations of aromatic hydrocarbon with an average value of 26.37%. Oils in shales or coal seams are rich in aromatics and resins, their average contents of aromatics and resins of shale oils are 17.58% and 17.48%, while those of coal-derived oils are 25.63% and 44.31%, respectively. For nature gases, their differences are reflected in the relative contents of methane, C2+ , CO2 , H2 , H2 S and N2 (Table 2.2). Methane content of gas hydrate is the highest, followed by coal-bed gas. Contents of C2+ in tight gas reservoirs and shale gas reservoirs are the highest, with average 11.91% and 1.34%, respectively, compared to other types of gas reservoirs. The variation of nonhydrocarbon gas content is greatly influenced by many factors, differing from basin to basin. Figure 2.10 shows geochemical characteristics of crude oils from source rocks and sandstone reservoirs at the same burial depth in the Bamianhe Sag in the Jiyang Depression of the Bohai Bay Basin of China. Great differences have also been found in compositional characteristics and biomarkers. The crude oils at burial depths of less than 2700 m are from deeper source rocks rather than from adjacent source rocks at similar burial depth because they have not reached the hydrocarbon expulsion threshold (Pang et al. 2005). In contrast, oils at buried depths larger than 2700 m are mainly derived from adjacent source rocks, forming tight oil and gas reservoirs neighboring to their source rocks. Figure 2.11 shows oil and gas reservoirs distribution and relationship between geochemical characteristics of crude oil and its burial depth in the western sag of the Liaohe Depression of the Bohai Bay Basin in China. Structure changes of the depression control changes of oil composition. Heavy oil and bitumen mainly occur in areas with depth of less than 1500 m, adjacent to deep faults and are characterized by low groundwater alkalization. The crude oil density and viscosity are negatively correlated with burial depth. All these indicate that areas with weak alkaline ground water are unfavorable for the preservation of oil and gas, and extremely high temperature and pressure will lead to cracking of crude oil and transformation into gas.

Shale oil

Tight oil

Conventional oil

2nd member of Kongdian Formation, 53.13 Cangdong Sag, Huanghua Depression, Bohai Bay Basin, China

44.88–51.31

Funing Formation, Haian Depression, Subei Basin, China

50.00–60.00

Xiagou Formation, Qingxi Depression, Jiuquan Basin, China 73.20–83.70

41.4–79.70

Gaotaizi reservoir of Gulong Sag, Songliao Basin, China

Yanchang Formation, Ordos Basin, China

52.67

Lucaogou Formation, Junggar Basin, China

32.10

Rudeis Formation, Gulf of Suez, Egypt 44.15

23.00

19.67–21.83

10.70–13.30

17.00–22.00

41.40–79.70

15.83

2.80–16.40

23.92

51.85

Middle Albian-Lower Cenomanian Black Flysch Member, Basque-Cantabrian Basin, Spain 56.90–96.40

26.00–28.00

56.00–58.00

Nenjiang Formation, Songliao Basin, China

Yanchang Formation, Ordos Basin, China

40.00–47.00

Lingshui Formation, Yingqiong Basin, 50.00–58.00 China

Aromatic (%) 13.00–14.50

Saturate (%)

Shahejie Formation, Bohai Bay Basin, 69.00–75.00 China

Chemical composition

< 20.00

19.94–23.58

7.90–13.50

20.00–25.00#

6.70–18.90

12.34

0.70–27.10

–

10.22

14.00–16.00

0.14–0.20

12.00–15.00

Resin (%)

< 10.00

1.11–5.46

–

1.80–8.80

2.56

–

8.45

4.45

0.70–1.80

-

1.00–2.00

Asphaltene (%)

Table 2.1 Differences of geochemical components between conventional and unconventional oil in different petroliferous basins

Guo (2016)

(continued)

Liu et al. (2018)

Wang (2018)

Sun (2016)

Yang (2016)

Xie (2016)

Wang (2018)

Mohamed et al. (2014)

Permanyer et al. (2018)

Huang (1983)

Chen et al. (2000)

Pan (2009)

References

66 2 Unified Classification of Oil and Gas Reservoirs in the WPS

Heavy oil/bitumen

Coal-derived oil

28.14 37.65

Eastern Venezuela Basin, Venezuela

Yuwei Formation, Beibu Gulf Basin, China

28.32

35.54

32.40

43.30

25.90

Nenjiang Formation, Songliao Basin, China

21.58

Ramsa Basin, Greenland

22.00

28.49

66.00

Marcelina Formation, Guasare Basin, Venezuela

29.00

Aromatic (%)

Shahejie Formation, Bohai Bay Basin, 26.07 China

15.00

Saturate (%)

Mukalla Formation, Jiza-Qamar Basin, Yemen

Chemical composition

Table 2.1 (continued)

12.97

–

32.10

41.65

32.63

–

56.00

Resin (%)

7.03

27.20

–

3.38

–

–

–

Asphaltene (%)

Li et al. (2018)

Ding et al. (2012)

He (2012)

Bai (2009)

Petersen et al. (2013)

Escobar et al. (2016)

Mohammed et al. (2017)

References

2.4 Differences Between the Conventional and Unconventional Oil and Gas … 67

Shale gas

Tight gas

Conventional gas

Gas hydrate

85.63–94.25

71.1

P2 x in Sulige tight gas field in Ordos Basin, China

Saskatchewan Bakken Group, Canada 98.32–99.09

> 55.00

Taibei Sag, Turpan-Hami Basin

Longmaxi Formation, Sichuan Basin, China

78.91–93.29

0.47

19.9

3.31–8.37

< 35.00

0.00–8.76

5.2

Xujiahe Formation Chuanzhong, Sichuan Basin, China

0.4

97.53

The Anglo-Dutch Basin 91.2

Sichuan Basin, China

68.10–85.10

14.9–31.9

3.7

Barkley Canyon, Vancouver Island

96.24

Central Baikal Basin, Russia

16.71–38.94

0.00–0.02

58.21–76.80

Qilian mountains, Qinghai, China

0.01–0.09

C2–5 (%)

South China Sea 99.37–100.00 Trough, Japan’s coastal

99.60–99.90

CH4 (%)

Mackenzie delta, Canada

Chemical composition

0.36–0.42

–

0.13–2.25

0.24

0.03–0.63

0.27

0.8

–

0.03–0.63

–

0.45–20.26

0.05–0.20

CO2 (%)

–

–

–

–

–

–

–

–

–

–

–

–

H2 (%)

–

–

–

–

–

–

–

–

–

–

–

–

H2 S (%)

0.01–0.81

9

0.51–1.73

< 10.00

0.00–2.00

3.6

0.76

–

–

–

–

–

N2 (%)

(continued)

Wu et al., 2016

Luo et al., 2017

Dai et al., 2017

Zhang et al., 2018

Qin et al., 2018

Newell et al. (2007)

Newell et al. (2007)

He (2012)

He (2012)

He (2012)

He (2012)

He (2012)

References

Table 2.2 Differences of geochemical components between conventional and unconventional natural gas in different petroliferous basins

68 2 Unified Classification of Oil and Gas Reservoirs in the WPS

Coal-bed methane

Table 2.2 (continued)

0.06–2.22

99.22

Arkoma Basin, USA

0.01

0.0013

2.55

73.13–92.73

97.13

Marcellus shale in Appalachian Basin, USA

1

C2–5 (%)

Badaowan Formation, Junggar Basin, China

86.63

Leping Formation, Pingle Depression, China

Bowen Basin, Australia 97.11

CH4 (%)

Chemical composition

< 2.09

6.48–23.89

0.82

0.04

0.72

CO2 (%)

–

–

< 0.05

–

–

H2 (%)

–

–

< 0.05

–

–

H2 S (%)

< 2.09

0.10–4.73

2.07

0.28

11.6

N2 (%)

Liu et al. (2019)

Song et al. (2012)

Kinnon et al. (2010)

Mariano, 2016

Xie et al., 2018

References

2.4 Differences Between the Conventional and Unconventional Oil and Gas … 69

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2 Unified Classification of Oil and Gas Reservoirs in the WPS

Fig. 2.10 Differences of geochemical components between conventional and unconventional liquid oils in the Bamianhe Sag in the Jiyang Depression of the Bohai Bay Basin, China. a Biomarker characteristics of liquid oil in sandstone reservoir layers and in source rocks at same depth; b cross plots of biomarkers of liquid oil in sandstone reservoirs and source rocks versus burial depth, indicating difference between conventional and unconventional oils (Pang et al. 2005)

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Fig. 2.11 Geochemical characteristics of liquid oil in sandstone reservoirs and their burial depth in the western sag of the Liaohe Depression of the Bohai Bay Basin in China. a Distribution of conventional and unconventional oil and gas reservoirs in the Western Liaohe Sag. The heavy oil is distributed at the edge of the depression and near the surface of the deep fault zone and the cracking gas is distributed in the deep zone with high temperature and pressure in the central part of the depression. b Relationship between groundwater properties and buried depth, the heavy oil and bitumen is distributed in the area with buried depth of less than 1500 m

2.4.2 Conventional and Unconventional Oil and Gas Both Different in Source Rocks Spatial relationships of conventional and unconventional oil and gas reservoirs with their source rocks are quite different. Statistical analysis results show that conventional oil and gas reservoirs are separated from their source rocks, with a vertical maximum distance up to approximately 4 km (Pang et al. 2014b), a lateral maximum distance up to hundreds of kilometers (Creaney et al. 1994; Gussow 1954). In most cases, the lateral hydrocarbon migration distance ranges from 5 to 10 km (Hu 1982). Figure 2.12 shows the spatial distribution of four types of gas reservoirs and their relationships with source rocks, including conventional, tight, shale and coal-bed gas reservoirs in the Paleozoic strata in the Ordos Basin, China. Vertically, conventional oil and gas reservoirs are far above the source rocks, tight reservoirs are close to source rocks or within the sandstone layers interbedded with source rocks, while shale oil and gas reservoirs and coal seam gas and oil reservoirs formed and distributed within source rocks. The number of oil and gas-bearing reservoirs decreases with an increasing distance to source rocks. Laterally, most oil and gas reservoirs distributed within or around source rock centers. These can also be seen in many petroliferous basins such as in Piceance Basin (Cumella et al. 2017), Devonian Appalachian Basin (Lash et al. 2004; Engelder et al. 2009), Illinois Basin (Kenneth and Landes 1970; Carr 1981), and Michigan Basin (Apotria et al. 1994; Budai et al. 2002).

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Fig. 2.12 Spatial relationships between conventional and unconventional oil and gas reservoirs and their source rocks in Paleozoic strata in the Ordos Basin, China. a In Permian Xiashihezi (P2 x) Formation located above the source rock strata, conventional gas reservoirs were discovered in structure traps; b in Permian Shanxi (P1 s) Formation which is interbedded with major source rocks, unconventional tight gas reservoirs were discovered; c the vertical distribution of reservoir layers and source rocks; d a model of reservoir layer and major source rock distribution in a lateral cross section. There are more gas reservoirs in intervals near source rocks. P3 s—Permian Shiqianfeng Formation; P2 s—Permian Shangshihezi Formation; P1 t—Permian Taiyuan Formation; C2 b—Carboniferous Benxi Formation

2.4.3 Conventional and Unconventional Oil and Gas Both Different in Reservoirs Conventional and unconventional oil and gas accumulations are formed in reservoir layers with different tightness, which is determined by the layers’ lithology and pore structures. An important reservoir property-the tightness of reservoir rocks, is usually quantified by reservoir porosity and permeability. Conventional hydrocarbon

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accumulations commonly occur in reservoirs with porosity larger than 10 ± 2% and permeability larger than 1 mD. However, the lower limits of porosity and permeability for oil and gas accumulation may vary, depending on the grain size, grain sorting and rock type (Jiang et al. 2017). For example, the porosity and permeability thresholds of conventional reservoirs and unconventional tight reservoirs for the Cretaceous sandstone reservoirs in the Kuqa Depression in the Tarim Basin in China, are 8% and 1.0 mD, respectively (Fig. 2.13a1). Generally, tight oil and gas reservoirs have low porosity ranging from 2 to 12% and low permeability from 0.01 to 1.0 mD, the Upper Paleozoic tight sandstone reservoirs in the Ordos Basin has a porosity of less than 12% and permeability of less than 1.0 mD (Fig. 2.13a2) (Guo et al. 2017a). Shale oil and gas accumulations commonly develop in ultra-low-permeability reservoirs, with porosity of 2–20% and permeability of no larger than 0.01 mD, Tertiary shales in the Jiyang Depression of the Bohai Bay Basin, representative continental shale system in China, along with most shales in North America, have reservoir porosity of less than 18% and very low permeability of less than 0.01 mD (Fig. 2.13a3). Reservoir porosity is generally governed by compaction and diagenesis, and organic pores related to thermal decomposition of kerogens can improve the shale reservoir quality (Chen and Jiang 2016). While porosity and permeability are both commonly used to describe reservoir quality, permeability is a better parameter to distinguish conventional reservoirs from unconventional reservoirs because the fluid behavior in porous media is majorly determined by permeability. For instance, a conventional sandstone reservoir with high porosity (>10%) indicates a shallow burial depth and low compaction, but a shale reservoir with higher porosity (>10%) does not necessarily imply a shallow burial depth and low compaction. The tightness of a reservoir varies as a function of many factors such as grain size of sediments, burial depth, cementation and diagenesis. According to comprehensive analysis of different sandstone’s permeability, the different reservoirs were realized to form under different geological conditions (Fig. 2.13b): conventional sandstone reservoir with permeability > 1 mD was formed with large grain size and better sorting sands during their early burial stage (Maxwell 1964); unconventional tight sandstone reservoir with permeability of 1–0.01 mD was formed either in fine-grained sediments at shallow depth (Pitman et al. 1982; Wescott 1983) or in better sorted sandstone of larger grain size but buried deeply that underwent a strong compaction (Wilson and McBride 1988; David et al. 1994); unconventional ultra-tight reservoir with permeability < 0.01 mD was formed in three different scenarios. In the first scenario, the reservoir is formed in shales and can occur at various depths (Wright. 1957; Stow et al. 2001); In the second and the third scenarios, the unconventional ultra-tight reservoir is formed by transformation of a conventional reservoir or an unconventional tight reservoir due to further compaction (Scherer 1987; Pang et al. 2015). Real geological conditions are more complicated than those shown in Fig. 2.13a, as porosity and permeability of reservoirs in most cases show abnormal relationships. For example, a reservoir rock can have high porosity but with low permeability or have low porosity but with high permeability (Lucas and Drexler 1976; Weinzapfel

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Fig. 2.13 Correlations between the porosity and the permeability of conventional and unconventional reservoir layers in petroliferous basins. a The porosity and the permeability: a1-conventional sandstone reservoirs in the Tarim basin; a2-unconventional tight sandstone reservoirs in Ordos basin; a3-shale reservoirs in Bohai Bay basin and basins from North America (modified from Aguilera 2016). b Relationships between permeability and burial depth of conventional reservoir (I), tight reservoir (II), and ultra-tight reservoir (III)

and Neese 1986). The formation of reservoirs with high porosity and low permeability is usually associated with the formation of unconformity, characterized by fluids activity and dissolution. The formation of low-porosity and high-permeability reservoirs is mostly associated with folding and faulting in target layers, characterized by stress action and fractures. The occurrence of these reservoirs with abnormal porosity and permeability relationships proves that oil and gas accumulations were controlled by external force effects such as tectonic stress and subsurface fluids activities. In the Tarim Basin, 37 oil and gas accumulations have been discovered in the shallow-medium strata at depths of less than 4500 m (Fig. 2.14a1). high-porosity and high-permeability reservoirs account for 76.6% of them, while the percentages of reservoirs with low-porosity and low-permeability, high-porosity and lowpermeability, and low-porosity and high-permeability account for only 18.4%, 2.9% and 2.1%, respectively, indicating that their formation are dominated by buoyancy.

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Fig. 2.14 Differences and correlations of the porosity and permeability between conventional and unconventional oil and gas reservoirs. a Reservoirs in the Tarim basin, China: a1—Burial depth < 4500m; a2—Burial depth > 4500m. b Reservoirs in the world’s petroliferous Basin: b1 —Burial depth < 4500m; b2 —Burial depth > 4500m

Among 82 oil and gas accumulations with depths of larger than 4500 m, the proportion of high-porosity and high-permeability reservoirs only accounts for 9%, indicating that most of these reservoirs are not formed by buoyancy-driven, but formed by non- buoyancy-driven (Fig. 2.14a2). Around the world, 20,438 fields (IHS 2010) are discovered in 692 petroliferous basins at depth of less than 4500 m (Fig. 2.14b1). High-porosity and highpermeability reservoirs account for 81.9% of the total, the percentages for lowporosity and low-permeability reservoirs, high-porosity and low-permeability reservoirs and low-porosity and high-permeability reservoirs are 2.6%, 1.0% and 14.5%, respectively, indicating that most of the oil and gas reservoirs are formed dominantly under the control of buoyancy. Among the 562 deep-buried reservoirs with depths > 4500 m from 71 petroliferous basins (Fig. 2.14b2), the ratios of reservoirs with highporosity and high-permeability and with low-porosity and low-permeability account for 58.0% and 6.9%, respectively, indicating that buoyancy is responsible for the formation of most reservoirs. Reservoirs with high-porosity and low-permeability and those with low-porosity and high-permeability account for 0.4% and 34.7%, respectively, and these reservoirs not controlled by buoyancy.

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2.4.4 Conventional and Unconventional Oil and Gas Both Different in Tectonic Settings Distributions of conventional and unconventional oil and gas reservoirs are controlled by tectonic settings (Fig. 2.15). Conventional oil and gas accumulations typically occur at the top and the margins of a paleo-uplift or a positive structure in the shallow part of a basin. Anticline traps are commonly developed at structural highs, while lithology traps and stratigraphic traps tend to occur along their margins, so oil and gas can migrate upward under buoyancy-driven to form conventional reservoirs in those traps. This process is also controlled by other dynamic forces, such as fluid pressure, capillary pressure and water dynamics (Fig. 2.15a). Unconventional oil and gas accumulations typically occur in negative structure units or in the depression center of a basin. The recently discovered shale oil and gas accumulations in North America mostly occur within source rocks. They are not controlled by traps and have self-contained source-reservoir systems with continuous distribution (Fig. 2.15b). Although the burial depths of oil and gas reservoirs vary from place to place due to the influences of tectonic deformation and other factors, conventional oil and gas reservoirs tend to have smaller burial depths compared to unconventional tight oil and gas reservoirs in a WPS. Tectonic activities not only can change the burial depth of a WPS and the conditions of oil and gas accumulations, but also can change the structure style and the type of oil and gas reservoirs. For example, tectonic movement can deform sedimentary layers, leading to leakage and re-migration of trapped oil and gas, forming fractured-vuggy reservoir (Odling et al. 1999), heavy oil and oil sand (Wu et al. 2012), and secondary biogenetic gas reservoirs (Huang 1983). Besides, an increase of the reservoir burial depth can lead to thermal cracking of the previously trapped oil into natural gas (Tian et al. 2008). Formation and distribution of conventional and unconventional oil and gas reservoirs are controlled by different original oil and gas from source rocks (Fig. 2.16). Formation and distribution of conventional oil and gas reservoirs are controlled by oil and gas expelled earlier from source rocks between the Hydrocarbon Expulsion Threshold (HET, Ro ≈ 0.6%) and the BHAD (Ro ≈ 1.2%). Formation and distribution of unconventional tight oil and gas reservoirs controlled by oil and gas expelled from source rocks between the BHAD and the Active Source Rock Depth Limit (ASDL, Ro ≈ 3.5%). Formation and distribution of shale oil and gas reservoirs are controlled by oil/gas retained within source rocks with Ro ranging from 0.2 to 3.5%. Figure 2.16a shows relationships between original hydrocarbon amount and burial depth of source rocks in six petroliferous basins in China. Figure 2.16b illustrate the distribution depth range of proved hydrocarbon reserves at different burial depth or thermal maturity degree in petroliferous basins in China, showing that unconventional oil and gas resources are distributed in a much broader depth range than conventional resources. Unconventional oil and gas reserves in the Junggar Basin mainly consist of heavy oil and bitumen near surface, and 65% of the reserves are distributed in strata with Ro < 0.75%. Fracture-reformed oil and gas reservoirs and cracking-reformed oil and gas reservoirs are main unconventional resources in Tarim Basin, and 90%

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Fig. 2.15 The differences of tectonic settings between conventional and unconventional oil and gas accumulations in petroliferous basins. a1—Anticlinal conventional reservoir-Pars gas field of Persian Gulf Basin (Alsharhan and Nairn 1997); a2—fault-block conventional reservoir-Dossor oil pool in Emba province of the USSR (Sanders 1939); a3—lithologic conventional reservoirKhadyzhinskaya oil field in the Maikop region, USSR (Prokopovand and Maximov 1937); a4— stratigraphic conventional reservoirs-Quirequire field, eastern Venezuela (Preston and Cloud 1952). b1—Basin-center tight gas reservoir—Red Desert Basin, US (Law 2002); b2—basin-slope tight gas reservoir-Great Green Basin, US (Law 2002); b3—overthrust deep-basin tight gas reservoir, Alberta Basin, Canada (Putnam and Ward 2001); b4—Deep-basin tight gas reservoir-Ordos Basin, China (Wang 2002)

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of them are in strata with Ro > 1.2%. Tight gas is the most important form of oil and gas resources in Ordos Basin, and 66% of tight gas is distributed in strata with Ro ranging from 1.2 to 3.5%. The Bohai Bay Basin and the Songliao Basin in Eastern China possess generally unstable tectonic settings, and the discovered reserves in the basins are mainly conventional resources. More than 75% of discovered reserves in these two basins are in strata with Ro of 0.5–1.2%. Figure 2.16c is a simplified model showing the effect of oil and gas origin on the formation and distribution of conventional and unconventional reservoirs. Oil and gas expelled from source rocks at the early stage typically migrate upward and form conventional oil and gas resources in shallow areas. Then, some of them were uplifted by tectonic movement and biodegraded by microorganisms to form heavy oil or bitumen, forming unconventional oil and gas reservoirs near the surface. At the late stage, oil and gas expelled from source rocks formed mainly unconventional tight oil and gas reservoirs adjacent to or within source rocks, which can be buried to a deeper depth and reformed to another type of unconventional reservoir containing cracking oil and gas due to higher temperature. Distribution of conventional and unconventional oil and gas reservoirs are controlled by their positions in a petroliferous basin. Figure 2.17 illustrates the distribution of conventional oil and gas reservoirs, tight oil and gas reservoirs, shale oil and gas reservoirs and reformed oil and gas reservoirs in the Junggar Basin and their spatial relationships. Conventional oil and gas reservoirs are distributed in positive

Fig. 2.16 The differences between conventional and unconventional oil and gas reservoirs in six representative basins of China. a Vertical distribution of original oil and gas amounts, available for shale oil and gas reservoir formation (green), conventional oil and gas reservoir formation (red), and tight reservoir oil and gas reservoir formation (yellow). b Vertical distribution of proved conventional and unconventional reserves in six representative basins of China. Different original hydrocarbons and proved reserves are expressed in different colors. c Vertical distribution model of conventional and unconventional resources in petroliferous basins and their relation to original hydrocarbon amount

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structures in the Permian strata with depth < 2800 m, and oil/gas are stored in porous and permeable reservoirs sealed by Triassic cap rocks (Cao et al. 2005) with a pressure coefficient of > 1.0 (Luo et al. 2007). Tight oil and gas reservoirs are discovered in the Permian strata in negative structures with depth > 2800 m, adjacent to the Permian source rocks (Cao et al. 2016; Wu et al. 2016). The in-place oil resources in the Jimusaer Sag in the east and in the Mahu Depression in the west are 7.02 and 8.35 billion tons, respectively (Hu et al. 2016; Tao et al. 2016). In addition, the uplift along the basin margin (Feng et al. 1989) resulted in alterations of the original hydrocarbon accumulations by microbial degradation and oxidation at later stages, forming heavy oil and bitumen resource with a proved reserve of over 3.6 billion tons (Yang 2016). Continuous subsidence increased burial depths of original reservoirs (Feng et al. 1989), and led to dry gas accumulations due to hydrocarbon cracking in the deep area of the basin (Zhang et al. 2015). Such reservoirs are common in other petroliferous basins around world. For example, a clastic oil and gas reservoir is found in the upper area of the Viking Formation in the Albert Basin, Canada (Bekele et al. 2002); A tight oil reservoir is in the lower area (Hamm and Struyk 2011), and Athabasca oil sands are at the surface of the eastern part of the basin (Kramers and Brown. 1976; Mossop 1980). The evidence indicates that tectonic evolution of petroliferous basins shapes the characteristics of oil and gas reservoirs formed earlier in different positions.

Fig. 2.17 Distribution of conventional and unconventional oil and gas accumulations at different locations in the Junggar Basin in the west of China. Conventional oil and gas reservoirs are distributed in traps at top of positive structure above BHAD, while unconventional tight oil and gas reservoirs are distributed at the bottom of depressions continuously. Shale oil and gas reservoirs are located within source rocks, while heavy oil and bitumen is in the reformed west margin of the basin. Each sandstone porosity data point in the figure is the average value of reservoirs in a 250-m depth range. Data points are from 5280 samples of 1789 wells (modified from Pang et al. 2021a)

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2.4.5 Conventional and Unconventional Oil and Gas Reservoirs Both Different in Formation Mechanism Formations of conventional and unconventional oil and gas reservoir are associated with different dynamic mechanisms. Buoyancy acts as the major driving force in conventional oil and gas accumulations, but it is not the primary driving force in the formation of unconventional oil and gas reservoirs because many other forces reduce the effect of buoyancy, such as relative permeability jails (Masters 1979), diagenetic trapping (Cant 1986), critical pore throat (Berkenpas 1991), and lateral sealing of faults (Robert and Suzanne 2004). Many previous studies attempted to explain the distribution of conventional oil and gas reservoirs in shallow zones and more unconventional oil and gas reservoirs in deep zones by various mechanisms. Hillis et al. (2001) suggested that the differences in fluid pressures control the distribution of hydrocarbon accumulations, e.g., normal fluid pressure in the shallow-medium allows the formation of conventional oil and gas accumulations under buoyancydriven, while abnormal pressure in deeper zone enables hydrocarbon to migrate and accumulate to form unconventional oil and gas reservoirs (Fig. 2.18a). Schenk and Pollastro (2001) suggested that thermal decomposition of kerogen in the shallow zone can result in oil accumulation in conventional reservoir layers, while gas derived from kerogen or oil cracking in the medium-deep zone could accumulate in unconventional tight reservoirs (Fig. 2.18b). Statistical analyses of drilling results exhibit that both porosity and permeability decrease with increasing depth (Bloch et al. 2002; Ehrenberg and Nadeau 2005), along with increasing resistance for hydrocarbon migration: Shallow reservoirs are characterized by large pores and throats as well as smaller capillary resistance, where buoyancy is larger than the resistance and dominates oil and gas accumulations; In contrast, deep-burial reservoirs are characterized by small pore and throats as well as larger capillary resistance, where buoyancy is much smaller than the capillary resistance, and non-buoyancy forces act as the dominant driving forces (Fig. 2.18c). A physical simulation experiment was conducted to prove a transition of the primary driving force from buoyancy in shallow strata above BHAD to non-buoyancy forces in deep strata below the BHAD (Guo et al. 2017a), the driving force (Pe) at BHAD is almost equal to the resistance which is the sum of hydrostatic pressure (Pw) and capillary pressure (Pc). Above the BHAD, buoyancy drives oil and gas to migrate upward into traps, forming conventional oil and gas reservoirs, whereas below the BHAD, other non-buoyance force such as capillary force difference between reservoirs and source rocks drives oil and gas to migrate out of source rocks to form unconventional oil and gas accumulation in nearby reservoirs (Fig. 2.18d). Furthermore, external conditions play an important role in the formation and distribution of oil and gas accumulations, e.g., tectonic activities can generate abundant fractures in a tight reservoir (Lucas and Drexler 1976; Gale et al. 2014), resulting in oil and gas migration upward under buoyancy-driven to form fractured oil and gas reservoir. In another scenario, tectonic uplift can destroy conventional oil and gas accumulation by inducing leakage in traps and producing heavy oil and bitumen through biodegradation (Niu and Hu 1999; Hein 2017). All above suggest

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Fig. 2.18 Comparison of dynamic mechanisms of conventional and unconventional oil and gas reservoirs formation. a Schematic illustration of dynamic mechanisms for the formation of conventional and unconventional oil and gas reservoirs controlled by pressure zone (Hillis et al. 2001). b Schematic illustration of dynamic mechanisms for the formation of conventional and unconventional oil and gas reservoirs controlled by organic matter transformation (Schenk and Pollastro 2001). c Variation of reservoir porosity versus depth in major petroliferous basins in China. d Schematic illustration of dynamic mechanisms of the formation of conventional and unconventional oil and gas reservoirs controlled by BHAD and forces balance condition, Pe— hydrocarbon pressure in reservoirs, Pw—state water column pressure, Pc—capillary pressure. BHAD—Buoyance-driven Hydrocarbon Accumulation Depth (Pang et al. 2021b)

that hydrocarbon accumulation mechanisms are closely associated with geological conditions, and different oil and gas reservoirs are formed by different mechanisms.

2.5 Unified Genetic Classification of Conventional and Unconventional Oil and Gas Reservoirs Based on the differences and correlations between conventional and unconventional oil and gas reservoirs, a unified genetic classification scheme is proposed and all oil and gas reservoirs are divided into 3 categories, 6 subcategories, 15 types and

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49 styles by their dynamic mechanisms, major controlling factors, and underground occurrences.

2.5.1 The Unified Genetic Classification Scheme and Principle The occurrences of conventional and unconventional oil and gas reservoirs in petroliferous basins are generally controlled by many factors including tectonic settings, source rocks, reservoir properties, relative locations to source rocks, driving forces, preservation, etc. Some of these factors are either causal or interdependent, and can be applied in the genetic classification. In this scheme, all oil and gas reservoirs are divided into 3 categories and 6 subcategories by the dominant driving forces and formation mechanisms for hydrocarbon migration and accumulation, illustrated in Fig. 2.19. Category I is buoyancy-driven conventional trap oil and gas reservoirs, category II is unconventional tight oil and gas reservoirs driven by non-buoyancy force, and category III is unconventional reformed oil and gas reservoirs driven by external force. There are remarkable differences among these three categories in terms of hydrocarbon compositions, pore structures, reservoir lithologies, reservoir locations in basins, and formation controlling factors. The three major categories are further divided into 6 subcategories by formation mechanisms of oil and gas reservoirs. Conventional trap oil and gas reservoirs are

Fig. 2.19 The unified genetic classification scheme of conventional and unconventional oil and gas reservoirs. Driving force are essential element for hydrocarbon accumulations in petroliferous basins, and they determine the oil and gas reservoir types. Each of three categories is further divided into two subcategories according their formation mechanisms

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divided into 2 subcategories, the conventional structural trap oil and gas reservoirs (I-1) and non-structural trap oil and gas reservoirs (I-2). Unconventional tight oil and gas reservoirs are divided into 2 subcategories, the unconventional tight oil and gas reservoirs near the source rock (II-1) and the unconventional ultra-tight oil and gas reservoirs within source rock (II-2). Unconventional reformed oil and gas reservoirs are divided into 2 subcategories, the media-reformed oil and gas reservoirs (III-1) and the components-reformed oil and gas reservoirs (III-2). The 6 subcategories are further divided into 15 types by major controlling factors on reservoirs distribution. Conventional trap oil and gas reservoirs are divided by trap differences and formation mechanisms into five types, including anticlinal trap oil and gas reservoir (I1 ), faults trap oil and gas reservoir (I2 ), lithology trap oil and gas reservoir (I3 ), stratigraphic trap oil and gas reservoir (I4 ), and hydrodynamic trap oil and gas reservoir (I5 ). Unconventional tight oil and gas reservoirs are divided by their tightness into five types, i.e. tight trap oil and gas reservoir (II1 ), tight deep basin oil and gas reservoir (II2 ), tight composite oil and gas reservoir (II3 ), ultra-tight shale oil and gas reservoir (II4 ), and ultra-tight coal oil and gas reservoir (II5 ). Unconventional reformed oil and gas reservoirs are divided by their abnormal changes into five types, i.e. reformed fracture oil and gas reservoir (III1 ), reformed vuggy oil and gas reservoir (III2 ), reformed fracture-vuggy oil and gas reservoir (III3 ), reformed heavy and bitumen reservoir (III4 ), and reformed dry gas reservoir (III5 ). The 15 types of hydrocarbon reservoirs are further divided into 49 styles by different oil and gas reservoir occurrences in petroliferous basins. The differences and correlations among these reservoirs are listed in the Table 2.3.

2.5.2 Identification Criteria for Conventional Trap Oil and Gas Reservoirs Formation of conventional trap oil and gas reservoirs is controlled by buoyancy and geological elements including source rocks, reservoirs, seal rocks, migration, traps, and preservation (Fig. 2.20). The five types of conventional trap oil and gas reservoirs are further divided into 14 styles based on their occurrence characteristics. For example, anticline trap oil and gas reservoirs (I1 ) are further divided into basementuplift anticline trap oil and gas reservoir (I11 ), tectonic-compression anticline trap are further divided reservoir (I12 ), diapir-related anticline trap are further divided reservoir (I13 ), drape-related anticline trap are further divided reservoir (I14 ), reversed-drag anticline trap are further divided reservoir (I15 ), and the like. Most hydrocarbon accumulations discovered in early stage of petroleum exploration history belong to this category. Daqing Oilfield in the Songliao Basin is the most famous oilfield in China, and its huge oil and gas resources were uncovered due to the existence of a large anticline in the year 1959. There are three critical points in the identification of trap oil and gas reservoirs. First, four geological elements including source rock, reservoir layer, cap rock, and trap, as well as their spatial and temporal combination are crucial

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Table 2.3 A unified genetic classification scheme for conventional and unconventional oil and gas reservoirs Categories

Names

I

Buoyancy-driven I1 conventional trap oil/ gas reservoirs

II

Types

Names

Styles and oil and gas reservoirs names

Anticlinal trap oil and gas reservoirs

I11 Uplift trap reservoirs, I12 Compression trap reservoirs, I13 Diaper trap reservoirs, I14 Drape-related trap reservoirs, I15 Reversed-drag trap reservoirs

I2

Fault trap oil and gas reservoirs

I21 Faulted-nose trap reservoirs, I22 Fault-block trap reservoirs

I3

Lithological trap oil and gas reservoirs

I31 Lens trap reservoirs, I32 Reef trap reservoirs, I33 Strata-pinchout trap reservoirs

I4

Stratigraphic trap oil and gas reservoirs

I41 Stratigraphic-overlap trap reservoirs, I42 Unconformity-related trap reservoirs

I5

Hydrodynamic trap oil and gas reservoirs

I51 Hydrodynamic-sealed traps reservoirs, I52 Water-molecule-sealed traps reservoirs

Unconventional tight II1 oil/gas reservoirs driven by non-buoyancy

Tight trap oil/gas reservoirs

II11 Tight anticlinal trap reservoirs, II12 Tight fault trap reservoirs, II13 Tight lithologic trap reservoirs, II14 Tight stratigraphic trap reservoirs, II15 Tight hydrodynamic trap reservoirs

II2

Tight deep-basin oil/gas reservoirs

II21 Tight deep-basin center reservoirs, II22 Tight deep-basin slope reservoirs, II23 Tight deep-basin margin reservoirs

II3

Tight composite oil/gas reservoirs

II31 Tight deep-basin center composite reservoirs, II32 Tight deep-basin slope composite reservoirs, II33 Tight deep-basin margin composite reservoirs (continued)

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Table 2.3 (continued) Categories

III

Names

Unconventional reformed oil/gas reservoirs driven by external force

Types

Names

Styles and oil and gas reservoirs names

II4

Ultra-tight shale oil/gas reservoirs

II41 Low-mature ultra-tight shale oil/gas reservoirs, II42 Mature shale ultra-tight oil/ gas reservoirs, II43 High-mature ultra-tight shale oil/gas reservoirs, II44 Over-mature ultra-tight shale oil/gas reservoirs

II5

Ultra-tight coal oil/gas reservoirs

II51 Low-mature ultra-tight coal oil/gas reservoirs, II52 Mature ultra-tight coal oil/ gas reservoirs, II53 High-mature coal ultra-tight oil/gas reservoirs, II54 Over-mature ultra-tight coal oil/gas reservoirs

III1

Reformed fracture III11 Reformed fracture oil/gas reservoirs sandstone reservoirs, III12 Reformed fracture carbonate reservoirs, III13 Reformed fracture volcanic reservoirs, III14 Reformed fracture metamorphic reservoirs

III2

Reformed vuggy oil/gas reservoirs

III3

Reformed III31 Reformed fracture-vuggy oil/ fracture-vuggy sandstone gas reservoirs reservoirs, III32 Reformed fracture-vuggy carbonate reservoirs, III33 Reformed fracture-vuggy volcanic reservoirs, III34 Reformed fracture-vuggy metamorphic reservoirs

III21 Reformed vuggy sandstone reservoirs, III22 Reformed vuggy carbonate reservoirs, III23 Reformed vuggy volcanic reservoirs, III24 Reformed vuggy metamorphic reservoirs

(continued)

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Table 2.3 (continued) Categories

Names

Types

Names

Styles and oil and gas reservoirs names

III4

Reformed heavy oil/ bitumen reservoirs

III41 Reformed heavy oil reservoirs, III42 Reformed bitumen reservoirs

III5

Reformed cracking gas reservoirs

III51 Reformed cracked wet gas reservoirs, III51 Reformed cracked dry gas reservoirs

for oil and gas accumulations. Second, oil and gas accumulations typically occur at the top of a trap with normal contacts of oil/water, gas/water or gas/oil/water, sealed by overlying cap rock strata with low permeability. Thirdly, the oil and gas reservoirs are separated from their source rocks, and have high porosity and permeability. Formation of anticline trap oil and gas reservoirs (I1 ) is controlled by the anticline structure and buoyancy-driven. Fault trap oil and gas reservoirs (I2 ) are controlled by faults, buoyancy-driven and fluid-pressure. Stratigraphic trap oil and gas reservoirs (I3 ) are controlled by variation of strata conditions, buoyancy-driven and fluid pressure. Lithology trap oil and gas reservoirs (I4 ) are controlled by sedimentary reservoir facies, buoyancy-driven and capillary pressure. hydrodynamic trap oil and gas reservoirs (I5 ) are controlled by hydraulic conditions, buoyance-driven and the water system (Adams 1936; Hubbert 1953; Berkenpas 1991). Methane hydrate reservoir is currently regarded as an unconventional hydrocarbon resource (Dillion et al. 1980; Vedachalam et al 2015). Commercial methane hydrates are distributed in reservoir layers with high pores or fractures (Berecz and Balla-Achs 1983; Collett 1993; Milkov 2004) and in a vast special trap with high pressure and low temperature. Their formation and distribution are the same as conventional oil and gas reservoirs in terms of hydrocarbon migration from source rocks to traps (Kvenvolden 1988). Methane hydrates accumulate in reservoirs with high porosity and high permeability, and are sourced from either thermal degradation of kerogens in source rocks from deep basins (Soloviev and Ginsburg 1994) or from biogenic degradation of kerogens in shallow regions, e.g., Japan Nankai Trough (Colwell et al. 2004). Methane hydrates reservoirs are also separated from their original source rocks, and driven by buoyancy (Kwon et al. 2008). Therefore, they are classified into conventional trap reservoirs in this study.

2.5.3 Identification Criteria for Unconventional Tight Oil and Gas Reservoirs Formation and distribution of unconventional tight oil and gas reservoirs are not controlled by buoyancy and traps as illustrated in Fig. 2.21. All types of tight and

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Fig. 2.20 Formation mechanisms and identification criteria of conventional trap oil and gas reservoirs

ultra-tight oil and gas reservoirs are further divided into 19 styles based on their distributions and occurrence characteristics. For example, ultra-tight shale oil and gas reservoirs (II4 ) comprises low-mature shale reservoirs (II41 ), mature shale reservoirs (II42 ), high-mature shale reservoirs (II43 ), over-mature shale reservoirs (II44 ), etc. There are three identification criteria for these oil and gas reservoirs. Firstly, their formation and distribution are controlled by geological elements including source rock, reservoir, seal rock, tectonic stability, tightness of reservoir layer as well as the spatial–temporal combination of these elements (Grunau 1987; Wang et al. 2010). Secondly, the buoyancy-driven and traps are no longer the main controlling factors. Tight oil and gas reservoirs usually appear adjacent to source rocks at the basin center setting or at the deep basin setting, and have features such as reversed gas\water or oil\water contact, low porosity and permeability, low pressure, and a pattern of continuous distribution. Thirdly, different types of tight oil and gas reservoirs have different occurrence characteristics. The tight trap oil and gas reservoirs (II1 ) refer to the oil and gas accumulations in traps with porous and permeable reservoir rock prior to tightening due to compaction and diagenesis. Except the tightness of the reservoirs, the occurrences of tight trap oil and gas reservoirs (II1 ) are in no difference with conventional ones (Pang et al. 2013). Tight deep basin oil and gas reservoirs (II2 ) occur in deep basins or at basin centers, where oil and gas are driven into a tight reservoir by capillary pressure difference and displace the water in the reservoir layers (Jiang et al. 2016). One key criterion for identifying the tight deep basin oil and gas reservoirs is that oil and gas commonly saturate the whole

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reservoir layer near the source rocks instead of filling into traps (Law 2002). Tight composite oil and gas reservoir (II3 ) is the continuous tight oil and gas reservoirs formed by superimposing tight trap oil and gas reservoirs and tight deep-basin oil and gas reservoirs. Hydrocarbon accumulations in traps in positive structure initially form by buoyancy, then along with tightening of the reservoir, oil and gas charges into the same reservoir layer by non-buoyance driven forces (Pang et al. 2014a). Combination of these processes leads to the formation of the continuous tight oil and gas reservoirs (Schmoker and Oscarson 1995). Ultra-tight shale oil and gas reservoirs (II4 ) refer to reservoirs form by oil and gas retained within source rock shale which acts as both the reservoir and the source rock (Li et al 1994; Bowker 2007; Jarvie et al. 2007; Ross and Bustin 2008; Passey et al. 2010). An ultra-tight shale oil and gas reservoir has three characteristics: (1) it is a self-contained source-reservoir system in an organic-rich shale; (2) shale oil is in relatively low-mature stage and shale gas is in high-mature stage for the evolution of a shale source rock; (3) its economic value depends on shale properties including thickness, area, organic matter abundance, thermal maturity, oil–gas mobility, mineral brittleness, etc. (Curtis 2002; Montgomery et al. 2005; Jarvie et al. 2007; Pollastro et al. 2007; Loucks et al. 2009; Ougier-Simonin et al. 2016). Ultra-tight coal-bed methane reservoir (II5 ) is a gas reservoir formed by gas retained in a coal bed (Gunter et al. 1997; Song et al. 2013). It is also a self-contained source-reservoir system with its economic value varying with reservoir thickness, area, thermal maturity, gas mobile possibility, etc. (Butler et al. 1988; Teichmüller 1989; Bustin and Clarkson 1998; Ayers 2002). These identification criteria have been helpful in discovering huge oil and gas resources in recent decades. An important feature of tight oil and gas accumulations is “sweet spot”, which refers to hydrocarbon-bearing geographic areas with the best enrichment in unconventional reservoirs. “Sweet spots” characterized by locally good reservoir quality in continuous tight oil and gas reservoirs, and are always the most productive area in a tight oil and gas accumulation. For instance, the vast continuous tight gas reservoirs in the Ordos basin in China, tight oil resources in deep basin area of the Songliao Basin in China, and springing up shale oil and gas resources in North America.

2.5.4 Identification Criteria for Reformed Oil and Gas Reservoirs Formation and distribution of reformed oil and gas reservoirs are controlled by external forces (Fig. 2.22). The reformed oil and gas reservoirs are subdivided into 16 styles based on the reservoir features and hydrocarbon components. For example, reformed vuggy-fracture oil and gas reservoir (III3 ) comprises reformed sandstone vuggy-fracture oil and gas reservoir (III31 ), reformed carbonate vuggy-fracture oil and gas reservoir (III32 ), reformed volcanic vuggy-fracture oil and gas reservoir (III33 ), and reformed metamorphic vuggy-fracture oil and gas reservoir (III34 ), and

2.5 Unified Genetic Classification of Conventional and Unconventional Oil …

89

Fig. 2.21 Formation mechanisms and identification criteria for unconventional tight oil and gas reservoirs

the like. Reformed oil and gas reservoirs have been explored throughout the history of petroleum industry, their discoveries required comprehensive understandings on complex geological history. The formation of reformed oil and gas reservoir is totally different from that of conventional trap oil and gas reservoir and unconventional trap oil and gas reservoir. There are three identification criteria for reformed oil and gas reservoirs. Firstly, they are characterized by the complicated history of petroliferous basin and external force actions related to the evolution of this basin, such as tectonic deformation, geo-fluid activities, microbial biodegradation, and thermal cracking (Harding and Lowell, 1979). Secondly, the reformed oil and gas reservoirs generally controlled by uplifting, deep burial, erosion, fluid flow, folding, faulting, as well as the spatial–temporal combination of these activities (Johnsson et al. 1993; Satyana et al. 1999; Prost 2004; Pang et al. 2012b). Thirdly, the 5 types of reformed oil and gas reservoirs differ from each other in terms of their formation mechanisms and identification criteria. The reformed fracture oil and gas reservoir (III1 ) is characterized by low porosity and high permeability, and it generally occurs around a fault zone or a folded region (Lorenz and Mroz 1999; Jiang et al. 2015). The reformed vuggy oil and gas reservoir (III2 ) typically has high porosity and low permeability, occurring around unconformities or regions with strong fluid activities (Burchette 1996; Gao and Fan 2015). The reformed fracture-vuggy oil and gas reservoir (III3 ) appears in the fault-unconformity cross zone, and is characterized by local high porosity and high permeability (Lu et al. 2017). Reformed heavy oil and bitumen reservoir (III4 ) is transformed from conventional oil and gas accumulation by biodegradation (Head

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Fig. 2.22 Formation mechanisms and identification criteria for reformed oil and gas reservoirs

et al. 2003), and is widely developed in shallow areas with low temperature and low salinity. The reformed heavy oil reservoirs usually have high-density and highviscosity components, especially 25-norhopane (Connan 1984; Ruble et al. 1994; Wu et al. 2012). The reformed dry gas reservoir (III5 ) is transformed from tight or ultra-tight oil and gas reservoirs due to oil cracking at high temperature (Hao et al. 2008). It has heavy isotope, high adamantane content as well as low density and low viscosity. It is commonly developed in deeply buried high-temperature strata (Horsfield et al. 1992). It is necessary to separate the reformed oil and gas reservoirs from conventional and unconventional oil and gas reservoirs, and there are three main reasons. First, the driving force and dynamic mechanism that leads to the formation and distribution of reformed oil and gas reservoirs is completely different from that of conventional and unconventional oil and gas reservoirs, as reformed oil and gas reservoirs are finally determined by the external forces due to the tectonic movements after the formation of conventional and unconventional oil and gas reservoirs. Second, the major controlling factors are also completely different, which include stress extrusion, fluid dissolution, biodegradation and high-temperature cracking. Third, they have a variety of underground occurrences, including the location migration, size modification, hydrocarbon components alteration and phase transformation. The reformed oil and gas reservoirs mainly form and exist in petroliferous basins with frequent tectonic movements. The proven oil and gas reserves in the superimposed basins in western China in the past 10 years account for more than 90% of total proven reserves, and the global proven bitumen are estimated to be 1438 × 109 m3 gas

2.6 Summary

91

equivalent. Studying them as one category is helpful in guiding their exploration and development. By realizing the genetic correlations and differences of different oil and gas reservoirs, the classification can be applied to petroleum exploration and exploitation. All oil and gas reservoirs could find their positions in this classification scheme. In addition, the proposed classification in this study can aid in prediction of oil and gas reservoirs distribution in sedimentary basins, especially in those area with low exploration degree. According to the complex condition of oil and gas exploration, development and trading, the styles of oil and gas accumulations can also be divided further in detail. For example, natural gases reservoirs can be further divided based on the H2 S contents; the crude oil reservoirs can be divided by their density and viscosity. These subdivisions are very important because they affect quality and price of oil and gas reserves in market. Subdivisions can also be made on oil and gas reservoirs by their depths, sizes, and abundances of oil and gas reserves, which are also important for exploration because they reflect the cost of oil and gas resources.

2.6 Summary The discovery and large-scale exploration of unconventional oil and gas resources since 1980s have been considered as the most important advancement in the history of petroleum geology. It has not only changed the balance of supply and demand in the global energy market, but also improved our understanding of the formation mechanisms and distribution characteristics of oil and gas reservoirs. However, misconceptions widely exist in studies of different types of oil and gas accumulations because of the lack of a unified genetic classification. Unconventional reservoir has been used in the literature as a general name for various oil and gas reservoirs that are formed under complex dynamic mechanisms as long as buoyancy is not the major controlling factor. On the other hand, different terms have been given to the oil and gas reservoirs even with the same formation mechanism. This paper selected six representative basins in China as the major research subject, analyzed their drilling results of 80,762 reservoir layers from 12,237 exploration wells in these basins. By investigating the progress of unconventional oil and gas resources exploration in North America in the past 30 years and addressing the distribution characteristics of discovered 52,926 oil/gas reservoirs in 1186 basins around the world, this study revealed the correlations and differences of formation and distribution characteristics between conventional and unconventional oil and gas reservoirs. It was found that there are five correlations between conventional and unconventional oil and gas reservoirs, including sharing the same oil and gas source rocks, occurring in strata with the same geological age, being enriched in the same reservoir layers, being confined in the same petroleum systems and coexisting in the same sedimentary basins. It was also found that there are five differences between conventional and unconventional oil and gas reservoirs, including the differences in hydrocarbon

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compositions, spatial relations to source rocks, reservoir lithology and quality, distribution in geological settings, and reservoir formation mechanism. A unified genetic classification scheme is put forward to clarify their differences and correlations: All kinds of conventional and unconventional oil and gas reservoirs are classified into 3 categories and 6 subcategories according to their dynamic mechanisms of formation, reclassified into 15 types based on main controlling factors, and further divided into 49 styles considering their underground occurrences. The application results show that all different oil and gas reservoirs can find their corresponding positions in the classification scheme, and all the oil and gas reservoirs with the same genetic mechanism, major controlling factor and occurrence can find their particular position in this classification scheme. The major content of this chapter has been published in Gondwana Research (Pang et al. 2021c).

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Chapter 3

Buoyancy-Driven Hydrocarbon Accumulation Depth in the WPS

New Understanding: BHAD widely exists in petroliferous basins, it represents a critical dynamic boundary where buoyancy-dominated hydrocarbon accumulation is transformed to non-buoyancy-dominated hydrocarbon accumulation with increasing depth. BHAD corresponds to a force equilibrium between the hydrocarbon pressure in reservoirs and the total of the pressure of overlying water and the capillary pressure in reservoir, with a critical porosity of 10 ± 2% and permeability of 1 mD in sandstone strata. The critical porosity and permeability of BHAD are constrained by the components of oil and gas, the grain size of the reservoir layer, the geothermal gradient and others in petroliferous basins. BHAD becomes shallower with heavier hydrocarbon, finer grain size in reservoir layers, a higher geothermal gradient and more strata eroded. In six representative petroliferous basins (Junggar Basin, Tarim Basin, Ordos Basin, Sichuan Basin, Bohai Bay Basin and Songliao Basin) in China, the BHAD vary from 1200 m in the basins with high heat flow in Eastern China to 4200 m in the basins with low heat flow in Western China. BHAD can be identified by oil and gas reservoir features in their basins. Conventional oil and gas reservoirs are formed above BHAD, appearing in features as accumulated in high point of trap, enriched in layer with high porosity, sealed by cap rocks at high position, and formed in reservoirs with high pressure, separated from source rock; while, the unconventional oil and gas reservoirs are formed below BHAD, appearing in features as distributed at the low depression of a basin, accumulated in layers of low porosity, located in the low position, keep stable in low pressure and connecting to source rocks. The original hydrocarbon amount for conventional reservoirs formation is about 10% of the total generated hydrocarbon amount in the basins, while the share of the proved hydrocarbon reserves is disproportionally high at 82%, indicating the limitation of remaining resource potential of the conventional hydrocarbons. The original hydrocarbons amount for unconventional reservoirs formation below BHAD is about 40% of the total generated hydrocarbon amount, while the share of the proved reserves is only 18% of the total, indicating a greater resource potential.

© Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_3

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3.1 Introduction and Issue The exploration and discovery of unconventional oil and gas resources since the late twentieth century is one of the greatest advances in the history of hydrocarbon exploration (Schmoker 1999; Aguilera and Ripple 2012; Tang et al. 2012; Schelly 2016; Thomas et al. 2017; Zhong et al. 2017; Montgomery and Sullivan 2017; Af¸sar and Luijendijk 2019). It increases the global hydrocarbon resource potentials (Gautier et al. 2009; Littlefield 2013; McCollum et al. 2016; Tan and Barton 2017; Wang et al. 2019a), but also changes the structure of energy worldwide (Holditch 2003; Munasib and Rickman 2015; Ansari and Kaufmann 2019) and gives hope to solving problem of energy shortage (Deffeyes, 2004; Sovacool, 2007). In 2016, the production of unconventional oil in the USA accounted for 41% of its total production, unconventional gas production in China accounted for 35% of its total (Jia 2017). The discovery of unconventional oil and gas also changes geologists’ understanding of petroleum formation and accumulation (Fu et al. 2016; Jia 2017; Wang et al. 2019b). The formation and distribution of unconventional oil and gas resources are remarkably different from conventional oil and gas resources (Ding et al. 2012; Zou et al. 2013a; Esmaili and Mohaghegh 2016; Xu et al. 2017; Kibria et al. 2018; Zhao et al. 2019). Unconventional oil and gas resources are usually distributed in deep depressions and tight reservoir layers in petroliferous basins (Master 1979; Schmoker 1995; Zou et al. 2013b; Zheng et al. 2019a, 2019b, 2020), which were considered unfavorable for oil and gas migration and accumulation in the view of the classical petroleum geology (Levorsen 1956; White 1885). Unconventional oil and gas reservoirs generally co-exist with conventional oil and gas reservoirs in WPS; they sometimes occur separately in WPS, not coexisting with conventional oil and gas reservoirs at all (Rose et al. 1986; Ridgley et al. 2002). Unconventional oil and gas reservoirs were given different names in previous literatures, including deep basin oil and gas reservoirs (Masters et al. 1979), basincenter oil and gas reservoirs (Law 2002), source-connecting oil and gas reservoirs (Zhang 2006), tight oil and gas reservoirs (Spencer 1989) and continuous oil and gas reservoirs (Schmoker 1995). The unconventional oil and gas reservoirs have remarkable geological features as following: (1) distributed in the low depressions of a basin; (2) they are formed in tight reservoir layers (Shanley et al. 2004; Zou 2011; Pang et al. 2015a); (3) closely connected to source rocks (Zou et al. 2013b; Pang et al. 2015a); (4) appearing in continuous form. On the other side, conventional reservoirs commonly occur in shallow areas at the top of uplift structures, separating from the source rocks. The distributions of conventional oil and gas reservoirs are controlled by trap structures (Shanley 2004; Ehrenberg and Nadeau 2005). The study of migration and accumulation of oil and gas has been focused on the understanding of non-buoyance-driven. Several dynamic mechanisms for nonbuoyance driven oil and gas accumulations have been proposed, including the variation of permeability in reservoir layers (Masters 1979), the variation of diagenesis in reservoirs (Cant 1986), the capillary force inhibition in oil and gas migration (Berkenpas 1991), the lateral fault blockage of oil and gas in the carrier layers (Robert

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and Suzanne 2004). However, none of these mechanisms can explain the depth difference of conventional oil and gas reservoirs and unconventional oil and gas reservoirs, or why unconventional oil and gas reservoirs coexist with conventional oil and gas reservoir and distribute widely in tight reservoir layers in petroliferous basins? In this study, we analyzed 12,237 drilling wells in 6 representative petroliferous basins in China and proposed a new concept of buoyance-driven hydrocarbon accumulation depth (BHAD) to explain the depth difference of conventional oil and gas reservoirs and unconventional oil and gas reservoirs, then discussed major controlling factors for BHAD, and applied BHAD to predict the resources potential of unconventional oil and gas reservoirs in basins in China and the world.

3.2 Buoyancy-Driven Hydrocarbon Migration and Accumulation 3.2.1 Definition of Buoyance-Driven Hydrocarbon Accumulation Depth The buoyance-driven hydrocarbon accumulation depth, in short of BHAD, is defined as the critical conditions corresponding to the transformation of driving force, where the buoyancy-dominated hydrocarbon migration/accumulation is changed to the nonbuoyancy-dominated migration/ accumulation as increasing the burial depth of reservoir layers (Fig. 3.1). Below BHAD, the total effects of non-buoyance-driven factors, such as strata capillary force (Wang et al. 2020), compaction, mineral and fluids thermal expansion, oil and gas diffusion due to concentration gradient, volume expansion due to transformation of clay and organic matter, will be more significant than the effects of the buoyance (Fig. 3.1a). A BHAD can be identified by the differences between conventional oil and gas reservoirs f above the BHAD and the unconventional oil and gas reservoirs below the BHAD (Fig. 3.1b). The average pore throat radius of reservoir layers decreases with the increase of buried depth of reservoirs, which in turn results in the disappearance of buoyance-driven hydrocarbon accumulation at the BHAD and the driving force then is changed to non-buoyance forces below the BHAD (Fig. 3.1c).

3.2.2 Representative Basins Used to Study the BHAD Six representative basins in China were selected to study the correlations and differences between conventional and unconventional oil and gas reservoirs, including Tarim Basin, Junggar Basin, Sichuan Basin, Ordos Basin, Bohai Bay Basin and the Songliao Basin (Fig. 3.2). These basins have the largest effective exploration areas, the highest degrees of exploration, the largest proved oil and gas reserves, and the

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Fig. 3.1 The buoyance-driven hydrocarbon accumulation depth (BHAD) and its controlling on the distribution of different oil and gas accumulations (Pang et al. 2021). a During the burial process, buoyancy is a dominant force for oil and gas accumulation and it does not change with depth, but the capillary pressure increases with depth, resulting in the change of the buoyancy-dominated force above BHAD to capillary pressure-dominated force below BHAD. b The change of the driving force with increasing depth leads to the formation of conventional oil and gas reservoirs above BHAD and the formation of unconventional oil and gas reservoirs below BHAD. c The pore throat radius of reservoir layers decreases with increasing depth, resulting in the formation of oil and gas accumulation in traps above BHAD and the continuous distribution of oil and gas in reservoir layers below BHAD

greatest resource potentials among all petroliferous basins in China (Ministry of Land and Resources 2009). Three steps were taken to study the BHAD and predict its distribution in these basins. Firstly, the oil and gas reservoirs discovered in these basins were analyzed, and the BHAD in them was determined. We analyzed 44,770 drilling results from 12,237 drilling wells in these basins, the BHAD identifying criteria were proposed. Secondly, the main controlling factors and formation mechanism for BHAD were studied by physical simulation experiments, designed to simulate formation mechanism and variations of BHAD with geological factors. A dynamic equilibrium equation characterizing the BHAD was established based on experiment results. Meanwhile, quantitative simulation research on the variation characteristics of BHAD for the major reservoir layers in representative basins were conducted based on actual geological data and parameters. Finally, the model of BHAD controlling the distribution of oil and gas reservoirs was established to explain the research results obtained from the geological analysis, physical experiments and numerical simulation, and it was validated by the distribution features of 52,926 oil and gas reservoirs discovered in 1186 basins around the world.

3.3 Identification of Buoyancy-Driven Hydrocarbon Accumulation Depth

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Fig. 3.2 The distribution of major basins in China with six representative basins in this study colored. The areas, proved reserves, resources and exploration degrees are the highest among these major basins in China. The inset shows the proved reserves, prospective resources and basin areas of China’s ten major petroliferous basins. Their geological settings and petroleum geology features were discussed in related literatures (Ministry of Land and Resources 2009)

3.3 Identification of Buoyancy-Driven Hydrocarbon Accumulation Depth There are five major evidences indicating that BHAD exists in petroliferous basins. (1) the distribution characteristics of oil and gas reservoirs is different in areas above BHAD and below BHAD; (2) the accumulation characteristics of oil and gas reservoirs is different in areas above BHAD and below BHAD, (3) the pressures characteristics of oil and gas reservoirs is different in areas above BHAD and below BHAD, and (4) the media characteristics of oil and gas reservoirs is different in areas above BHAD and below BHAD. All of them can be used to identify the existing of BHAD.

3.3.1 Identifying BHAD by Distribution Characteristics of Oil and Gas Reservoirs Distribution characteristics of oil and gas accumulations in a reservoir layer shows the existence of BHAD. Figure 3.3 shows the case study of the BHAD in the main

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sandstone layers of the Daqing Oil Field, which is the largest continent oil field in China, discovered in the Daqing Placanticline in the center of the Songliao Basin. The Yaojia member (K1y) and Qingshankou member (K1q3-4) are the major reservoirs. The oil in these layers come from the shale rocks of K1n above K1y and K1qn below K1y in the Eastern and Western Depressions, the oil from the source rocks migrated up to the structure traps of the Daqing Placanticline to form conventional reservoirs by the buoyance-driven. Data from 5401 exploration wells were used to identify the BHAD by the correlations and differences between the oil accumulations in the same sandstone reservoir layers. The BHAD of the sandstone reservoirs in the Eastern and the Western Depressions is about 2100 m with a porosity of 10 ± 2% and a permeability of 1 mD. About 4.68 × 109 t reserve of conventional oil was discovered above BHAD in Cretaceous sandstone of the Placanticline with porosity > 10% and permeability > 1 mD. About 1.57 × 109 t reserve of unconventional tight oil were proved in the sandstone below BHAD in both depressions around the Placanticline with porosity < 10 ± 2% and

Fig. 3.3 Distribution features of different oil reservoirs in the same sandstone layers of the Songliao Basin showing the existence of BHAD and how the BHAD is related to the porosity of the reservoirs. a Porosity variation of the reservoirs in the E-W profile in the Songliao Basin. b Distribution of the oil accumulations in the sandstone layers of E-W profile in the Songliao Basin and the identification of BHAD

3.3 Identification of Buoyancy-Driven Hydrocarbon Accumulation Depth

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permeability < 1 mD. The study by Feng et al. (2011) showed that the distribution area of unconventional tight oil was more than 0.6 × 104 km2 .

3.3.2 Identifying BHAD by Accumulation Characteristics of Oil and Gas Reservoirs Accumulation characteristics of oil and gas reservoirs in a WPS shows the existence of BHAD. Figure 3.4 illustrate the oil and gas drilling results and the distribution features of the Tertiary sandstone oil and gas reservoirs in the Zhanhua Sag of the Bohai Bay Basin in eastern China. Based on these features, the BHAD in different sandstone reservoirs were identified at the depth of about 3200 m. Above the BHAD, oil and gas migrated and accumulated dominated by buoyancydriven and controlled by traps with features of “four highs”, i.e., oil and gas accumulated in high point of traps, distributed in layers with high porosity and permeability, richen in high position and sealed by cap rocks, and formed with high fluid pressure in the reservoirs. These reservoirs are separated from their source rocks. Below the BHAD, oil and gas migrated and accumulated dominantly by non-buoyancy-driven and controlled by tight reservoirs with features of “four lows”, i.e., oil and gas are distributed in the low depression of a basin, accumulated in layers with low porosity, located in the form of inverted low position, and are stable in low pressure. These oil and gas reservoirs are close to their source rocks, distributed continuously and not

Fig. 3.4 Distribution features of oil and gas reservoirs in a WPS of the Zhanhua Depression in the Bohai Bay Basin, showing the existence of a BHAD. Above the BHAD, oil and gas migrate upward into traps to form conventional oil and gas reservoirs by the buoyancy-driven. Below the BHAD, oil and gas accumulate in tight sandstone layers to form unconventional oil and gas reservoirs driven by the non-buoyance

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controlled by trap structures. Such features with reservoirs above and below BHAD are found in all six representative basins in China, reflecting the controlling effects of BHAD on the formation and distribution of oil and gas reservoirs in WPS. Distribution characteristics of oil and gas accumulations in petroliferous basins shows the existence of BHAD. Figure 3.5 illustrate the distribution features of conventional oil and gas reservoirs and unconventional oil and gas reservoirs in some petroliferous basins around the world. Conventional oil and gas reservoirs are formed and distributed in the top regions of uplift structures (Fig. 3.5a), and oil and gas are driven by buoyance (White 1885) to migrate upward and accumulate in the traps developed in the uplift regions. Levorsen (1967) studied the conditions for oil and gas migration and accumulation under buoyancy-driven and classified the conventional oil and gas reservoirs into four categories, including anticlinal oil and gas reservoirs (Fig. 3.5a1), fault block oil and gas reservoirs (Fig. 3.5a2), stratigraphic oil and gas reservoirs (Fig. 3.5a3), and lithology oil and gas reservoirs (Fig. 3.5a4). The conventional oil and gas reservoirs have “four highs” features as mentioned above. The unconventional oil and gas reservoirs are formed in reservoir layers generally located in the depressions of a petroliferous basin (Fig. 3.5b). All the conventional oil and gas reservoirs formed by buoyancy-driven are distributed in the shallow reservoir layers with high porosity and permeability, while all the unconventional oil and gas reservoirs formed by non-buoyancy-driven are distributed in the deep reservoir layers with low porosity and permeability. Therefore, it is inferred that the reservoir layer in a basin during the burial process undergoes a transition where the oil and gas migration driving force inside the layer changes from buoyancy-driven to nonbuoyancy-driven. The point of transition is corresponding to the BHAD. World’s first deep basin gas reservoirs were discovered in the Alberta Basin in Western Canada in 1970s (Masters, 1979) in the regions that were once regarded as barren regions for oil and gas exploration using the buoyancy-driven theory until some unconventional or subtle oil and gas reservoirs were discovered (Shanley 2004). Unconventional oil and gas reservoirs were later discovered in many other places around the world (Zou et al. 2013a). Unconventional oil and gas reservoirs mainly have four different occurrences, i.e., in the center of a basin (Fig. 3.5b1), under over thrust faults at the edges of a basin (Fig. 3.5b2), at the side margins of a basin (Fig. 3.5b3), and at the bottom of a basin (Fig. 3.5b4). The differences in distribution and occurrence between conventional and unconventional oil and gas reservoirs imply that a BHAD exists in a petroliferous basin, which divides the basin into two fields vertically, one is favorable for conventional oil and gas reservoirs above the BHAD and the other is favorable for unconventional oil and gas reservoirs below the BHAD.

3.3 Identification of Buoyancy-Driven Hydrocarbon Accumulation Depth

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Fig. 3.5 Distribution features of oil and gas accumulations in different basins showing the existence of BHAD. a Representative conventional oil and gas reservoirs. a1 Anticlinal conventional gas reservoir, the South Pars Oil and Gas Field in the Northern Persian Gulf Basin (Nairn and Alsharhan 1997). a2 Fault block type conventional oil reservoir, the Dausol oil reservoir in the Umba oil region of the Soviet Union (Sanders, 1939). a3 Lithologic conventional oil reservoir, the Kadushin oil field in the Maikop oil region of the Soviet Union (Prokopov and Maximov 1937). a4 Stratigraphic conventional oil reservoir, the Kualunkuaer oil field in Venezuela (Cloud 1952). b Representative unconventional oil and gas reservoirs: b1 Unconventional gas reservoir in the center of Red Desert Basin in America (Law and Curtis, 2002). b2 Unconventional gas reservoir at in the lateral edge of Green River Basin in America (Coskey 2004). b3 Unconventional gas reservoir in the over thrust region of Alberta Basin in Canada (Masters 1984). b4 Unconventional gas reservoir in the deep depression of Ordos Basin in China (Zou et al. 2013b)

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3.3.3 Identifying BHAD by Pressure Characteristics of Oil and Gas Reservoirs The characteristics of fluid pressures in different oil and gas reservoirs within a reservoir layer shows the existence of BHAD. Figure 3.6 illustrates the variation of oil and gas accumulation pressure or pressure coefficient (Kp) with increasing depth from the same reservoir layer in different basins. (1) Abnormally large negative pressure (Kp < 1) in the reservoir with low porosity and low permeability indicates that the oil and gas reservoirs are unconventional, located below the BHAD (Fig. 3.6a). (2) The normal pressure (Kp ≈ 1) in the reservoir with high porosity and high permeability indicates that the accumulated oil and gas reservoirs are conventional and are located above the BHAD (Fig. 3.6b). (3) The abnormal intensive positive pressure (Kp > 1) in the reservoir with low porosity and low permeability indicate that the oil and gas reservoirs inside the layer are unconventional, formed by non-buoyancydriven during hydrocarbon generation and expulsion, and the BHAD exists above these reservoirs (Fig. 3.6c). (4) The coexistence of abnormal high pressure (Kp > 1) and abnormal low pressure (Kp < 1) in the reservoir with low porosity and low permeability indicates the reservoirs inside the layer are unconventional, and the BHAD exists at the top of these abnormal pressure reservoirs (Fig. 3.6d). Based on the comparison of oil and gas reservoir pressure and aquifer pressure in the reservoir layers, the BHAD and corresponding critical geological conditions can be identified.

Fig. 3.6 Distribution of pressures from the same reservoir layer in different basins and the determination of BHADs. a A tight deep-basin gas reservoir in the Alberta Basin of Canada, featured by negative pressures. b Continuous tight gas reservoirs in the Kazakhstan Basin, featured by normal pressures. c Continuous tight oil reservoirs in the Songliao Basin in China, featured by high pressures. d Tight deep-basin gas reservoirs in Green River Basin in America, featured by mixed high and low pressures

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3.3.4 Identifying BHAD by Media Characteristics of Oil and Gas Reservoirs Statistical analysis of porosity and permeability from different kinds of oil and gas reservoirs within the same layer show the existence of BHAD. Figure 3.7a illustrates the drilling results from a gas-bearing sandstone reservoir in the upper Paleozoic in Ordos Basin in Central China. The reservoir layer is widely distributed in the basin and is the main gas-bearing formation closing to the source rock layers. When the porosity is ≤ 12% and permeability is ≤ 1 mD of the layer, over 75% of wells yield natural gas, indicating the existence of a wide and continuous tight gas reservoir. When the porosity is > 12% and permeability is > 1 mD, only about 5–25% of wells drilled for the layer at the structure trap yield natural gas, indicating the presence of conventional trap gas reservoirs formed by buoyancy. Figure 3.7b illustrates the oil-bearing results of the Permian sandstone layer in the Junggar Basin in Western China. The reservoir layer is widely distributed in the basin, and is the major oil-bearing formation closing to Permian source rocks. When their porosity is ≤ 12% and permeability is ≤ 1 mD, almost 75% of wells show the existence of oil accumulations, indicating a wide continuous oil reservoir. When their porosity is > 12% and permeability is > 1 mD, only about 5–25% of wells show the existence of oil accumulations, indicating a conventional oil reservoir in

Fig. 3.7 Comparison of the BHAD for oil and the BHAD for gas by statistical analysis of porosity and permeability for sandstone oil and gas reservoirs in petroliferous basins. a Distribution and relation of the porosity and permeability for conventional and unconventional gas reservoirs in sandstone of the upper Palaeozoic in Ordos Basin, indicating the existence of BHAD and the corresponding critical porosity of 10 ± 2% and permeability of 1 mD. b Distribution and relation of the porosity and permeability for conventional and unconventional oil reservoirs in the sandstone of Permian in Junggar Basin, indicating the existence of BHAD and the corresponding critical porosity of 10 ± 2% and permeability of 1 mD

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the structure trap. Therefore, a porosity of 10 ± 2% and a permeability of 1 mD are the critical conditions for identifying BHAD.

3.4 Variation Features and Controlling Factors of the BHAD The BHAD in six basins of China was determined using the methods described above. By studying the features of BHAD and its controlling factors, the identifying criteria and variation characters of BHAD were determined. Through physical and numerical simulations, their formation mechanisms are revealed and the method to predict the distribution of unconventional oil and gas accumulations and their resource potentials in WPS is proposed. BHAD in different basins is very different, the variations of BHAD are controlled by four geological factors, including the lithology of reservoir layers, the hydrocarbon components, the tectonic movements, and the heat flow of a petroliferous basin.

3.4.1 Variation of BHAD with the Lithology of Target Layer The BHAD increases with the increase of grain size of reservoir layers. Figure 3.8a shows the drilling results of the Upper Paleozoic Carboniferous and Permian sandstone layers in the Ordos Basin. When the sandstone reservoir layer is deeply buried, the gas reservoir is widely and continuously distributed. The BHAD of the reservoir with fine grain size (at left side of Fig. 3.8a) is shallower than that of the reservoir with coarse grain size (at right side of Fig. 3.8a). The BHAD corresponds to a depth of 1350 m with fine sandstone and a depth of 2700 m with coarse sandstone, showing an increasing trend of the BHAD with increasing sandstone grain size.

3.4.2 Variation of BHAD with Hydrocarbon Components The BHAD is related to the components of hydrocarbon (Pang et al. 2014) and increase with decreasing molecular size of components. The natural gas with smaller molecular size has larger buoyancy than liquid petroleum with large molecular size under the same geological conditions. However, this realization (Ma et al. 2008) is not confirmed in deep geological conditions. The BHAD for oil in Junggar Basin (Fig. 3.7b) and the BHAD for natural gas in Ordos Basin (Fig. 3.7a) are very similar or identical, where the critical porosities and permeabilities of both BHADs for oil and gas are almost the same with porosity of 12% and permeability of 1 mD. A possible explanation is that the interfacial tension of natural gas is larger than that of

3.4 Variation Features and Controlling Factors of the BHAD

115

Fig. 3.8 Variation of the BHAD with changing lithology of reservoir layer and components of hydrocarbon. a Tight gas reservoirs discovered in upper Paleozoic sandstone in Ordos Basin in Central China are continuously distributed. b Variation features of interfacial tension for oil and gas in petroliferous basins. The geological parameters for calculation of interfacial tension: Depth (Z) = 0 m, Pressure (pa) = 1 bar, Temperature (T) = 20 °C, Pa = 0.1 × Z bar (Z /= 0), Geothermal gradient (GT) = 0.03 °C/m (Bao, 1998)

liquid petroleum at the same depth (Fig. 3.8b), so the larger buoyance of nature gas at ground surface is balanced by the larger capillary resistance in the underground due to the larger interfacial tension.

3.4.3 Variation of BHAD with Tectonic Movement The BHAD varies with tectonic movement, it decreases with increasing thickness of eroded strata above the reservoir layers due to a tectonic movement or an uplift in the whole petroliferous basin. Figure 3.9 illustrate variations of BHAD in Mesozoic layers in the Kuqa Depression of the Tarim Basin. In the northern part of Kuqa Depression, the BHAD is as shallow as 1000 m due to a large uplift, while in its southern part, the depth of BHAD is about 4200 m because of smaller uplift compared to the northern part. Natural gas was continuously and widely accumulated in the Triassic and Jurassic tight sandstone (Wells Yn4 and Ys4), which were destroyed by later tectonic fractures and uplift (Pang et al. 2019). Conventional oil and gas reservoirs were first formed in the well of Dn202, then transformed to tight reservoirs due to a later deep burial and dense process (Zhu et al. 2012). Continuous and superimposed tight reservoirs were formed in the Jurassic and

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Fig. 3.9 Variation of BHAD in Kuqa Depression of Tarim Basin due to tectonic movements

Triassic sandstone indicated by Well DX1 (Lu et al. 2016). The illustrated BHAD is the depth limit for conventional and unconventional oil and gas reservoirs before the tectonic movements, and becomes deeper after the tectonic movements. The southwestern Sichuan Basin was denuded by about 3000 m due to an uplift movement during the Triassic and Tertiary periods. As a result, the BHAD for Triassic and Jurassic sandstone was shallowed from the original 4200 m to the current 1200 m. In the Alberta Basin of Canada, the BHAD of the lower Cretaceous sandstone was reduced by 1900 m due to a whole basin uplift. When a basin is reformed by faulting and folding, the original tight medium for reservoirs is damaged by fractures. As a result, the non-buoyancy-driven status is changed to the buoyancy-driven status, and the BHAD becomes deeper. A basin with a history of strong tectonic movements tends to have a large variation of porosity and permeability in the same reservoir layer at different local regions, leading to large BHAD variations and complicated distribution of conventional and unconventional oil and gas reservoirs throughout the WPS.

3.4.4 Variation of BHAD with Underground Heat Flow BHAD increases with decrease of heat flow in petroliferous basins. Figure 3.10 shows the variation of BHAD with changing heat flow. BHAD in a basin with high geotherm gradient is relatively shallow, because of the quick compaction, cementation and decrease in the porosity and permeability of the reservoir layers with increasing the burial depth. In Fig. 3.10, the BHADs in different basins were corrected for the influence of structural variation, and the maximum burial depths for oil and gas accumulations were predicted based on the sandstone porosity of 2%. When

3.5 Simulation Experiments on Dynamic Equilibrium of the BHAD

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Fig. 3.10 BHAD variations with heat flow for different petroliferous basins in the world. The maximum burial depth for the formation and distribution of oil and gas reservoirs was inferred from 2% of porosity for sandstone reservoirs. The effects of erosion thickness and other factors on the BHADs and the maximum buried depth of reservoirs in different basins were calibrated

the geothermal gradient of a petroliferous basin varies from 1 to 5 °C/100 m on the X-axis of Fig. 3.10, the BHAD changes from 9200 m to about 1500 m, and the hydrocarbon accumulation depth limits for both buoyance-driven and non-buoyancedriven changes from 15,000 to 3000 m. The conventional and unconventional oil and gas resources in “cold basin” with a heat flow below 40 mW/m2 are much deeper than those in “hot basin” with a heat flow above 60 mW/m2 .

3.5 Simulation Experiments on Dynamic Equilibrium of the BHAD 3.5.1 Physical Modelling Experiments on Dynamic Equilibrium The BHAD is a dynamic equilibrium boundary in reservoir layers out of the source rocks, where the driving force for oil and gas migration and accumulation is equal to the resistances. In general, the porosity and permeability of the reservoir layers decrease with increasing burial depth, resulting in a decrease of the pore throat radius and an increase of the capillary pressure in reservoir layers, which, in turn, impedes oil and gas migration and accumulation. However, oil and gas migration and

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accumulation in the reservoir layers will change from the buoyancy-dominated to the non-buoyancy-dominated when the resistance from the capillary pressure reaches and exceeds the buoyancy of oil and gas. Two physical experiments were performed by Guo et al. (2017) to characterize the BHAD, the results are shown in Figs. 3.11 and 3.12. The first experiment with different pore throat radii uses a conical glass tube under variable fluid pressure conditions (Fig. 3.11a) and the second experiment with different sand particle sizes uses a cylindrical sand column filled with increasing size of sand particles from the bottom to the top (Fig. 3.12a). The results of these two experiments (Figs. 3.11b and 3.12b) show that, at the dynamic equilibrium boundary (i.e., BHAD), the hydrocarbon expansion pressure (Pe) is equal to the sum of overlying hydrostatic pressure (Pw) and the capillary pressure (Pc) in the reservoir layer (Eq. 3.1). The errors are within 0.01%. The expansion pressure in oil reservoirs and gas reservoirs, Peo and Peg, are calculated by Eqs. 3.2 and 3.3. Pe = Pw + Pc . Peo =

RT V −b

Peg =

z·ρg Mg

−

a V2

=

ρo RT Mo −ρo b

(3.1) −

ρo2 ·a Mo2

· R · T × 1.01 × 102

(3.2) (3.3)

where ρ o is the density of oil (kg/m3 ), R is the gas constant, 8.31433, T is the temperature of oil (k), Mo is the molar mass of oil (g/mol), a and b are the van der waals constants, z is the compression factor of natural gas, Mg is the molar mass of natural gas (g/mol), and ρ g is the density of natural gas (kg/m3 ). The overlying hydrostatic pressure, Pw, is calculated based on Archimedes’ principle using Eq. 3.4: Pw = ρ · w · g · Hcritical = ρ · w · g · ec1+15.854X3−Φ

(3.4)

where ρ w is the density of water (kg/m3 ), g is the gravitational acceleration constant (m/s2 ) and Φ is porosity (%). The capillary pressure of oil and gas migration in a reservoir, Pco and Pcg , are calculated by Eqs. 3.5 and 3.6: Pco =

2σo · cos θ γ

(3.5)

Pcg =

2σg · cos θ γ

(3.6)

where σ o and σ g are interfacial tensions of oil- water and gas–water (N/m), θ is twophase fluid contact angle and γ is pore throat radius. Equation 3.1 comes from Guo et al. (2017). Equations 3.5 and 3.6 come from England et al. (1987). The dynamic balance equations of oil and gas are separate, there is no mathematical relationship among the capillary pressure Pc , Pco and Pcg , so as Pe , Peo and Peg . The dynamic balance equations of oil and gas are expressed using Eqs. 3.7 and 3.8:

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119

Fig. 3.11 Physical modelling experiment with different pore throat radii for verifying the existence and formation mechanism of the BHAD in reservoir layer. a Force equilibrium experiment using a glass tube of decreasing throat radius from top to bottom. a1 a drawing of the experimental setup and related parameters. a2 a photo of the experiment. b Relationship among the critical parameters corresponding to BHAD, including the expansion pressure (Pe), the sum of hydrostatic pressure (Pw) and the capillary pressure (Pc)

Peo = Pw + Pco

(3.7)

Peg = Pw + Pcg

(3.8)

where Peo is the expansion pressure in oil reservoirs, Peg is the expansion pressure in gas reservoirs, Pw is the overlying hydrostatic pressure, Pco is the capillary pressure of oil migration and Pcg is capillary pressure of gas migration in a reservoir. All the geological parameters related to Pe, Pc and Pw have effects on the BHAD, but the effects differ from basin to basin.

3.5.2 Numerical Simulation and Quantitative Characterization By substituting Pe, Pw and Pc of Eq. 3.1 with their expressions and numeric values in Eqs. 3.2–3.8 based on real data from the Songliao Basin (Ma 2008), the equations to determine the identifying criteria of BHAD for oil and gas are obtained, respectively, as follows: 0.085e7.8+0.16D−0.07Φ + 97.6σo · e−0.22Φ = 101

(3.9)

0.085e7.8+0.16D−0.07Φ + 97.6σg · e−0.22Φ = 98.28

(3.10)

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Fig. 3.12 Physical modelling experiment with different sand particle sizes for verifying the existence and formation mechanism of BHAD in reservoir layers. a Force equilibrium experiment using a cylinder of sands with decreasing grain size from top to bottom. a1 a drawing of the experimental setup and related parameters. a2 a photo of the experiment. b Relationship among the critical parameters corresponding to BHAD, including the expansion pressure (Pe), the sum of hydrostatic pressure (Pw) and the capillary pressure (Pc)

where σ o and σ g are oil–water and gas–water interfacial tension (N/m), D is particle diameter (mm) of sandstone, and Φ is porosity of reservoir layer (%). All parameters related to different forces in the force equilibrium equation (Eq. 3.1) affect BHAD, but the BHAD majorly varies with 4 geological factors. The first is reservoir layer lithology (Fig. 3.8a), the coarser of the grain size is, the deeper of the BHAD is. The second is hydrocarbon components and their physical properties (Fig. 3.13), the BHAD becomes deeper when the pore throat radius in reservoir layer decreases with increasing the reservoir temperature while keeping other parameters unchanged (Fig. 3.13a); the BHAD depth becomes shallower with increasing oil and gas density (Fig. 3.13b), oil/gas–water interfacial tension (Fig. 3.13c) and wetting angle of the oil–gas (Fig. 3.13d). Although gas and oil have different physical states, their reservoir porosities at BHAD are almost the same, within the range of 10–12% (Fig. 3.13e). The third factor is tectonic movement, the BHAD decreases with an uplift in the whole basin (Fig. 3.9). The fourth is underground heat flow, the BHAD increases with decreasing heat flow in a basin (Fig. 3.10).

3.6 Discussion and Conclusion 3.6.1 Ubiquitous Presence of BHAD in Petroliferous Basins For 12,237 drilling wells, data on porosities/permeability, thickness/pressures, cap rocks/traps, original source rocks/hydrocarbon accumulation times, reservoirs distribution area/reserves were collected to evaluate hydrocarbon resource potentials of the

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Fig. 3.13 Numerical simulation results on critical parameters at BHAD based on force equilibrium equation (Pe = Pw + Pc). Radius variation of critical pore throat for BHAD with a formation temperature, b oil–gas density, c interfacial tension of oil/gas–water, d wetting angle, and e variation of the critical porosity for BHAD with grain size of reservoir layer

major sandstone reservoirs by using BHAD. The comprehensive results are summarized in Fig. 3.14, showing that conventional oil and gas accumulations are separated from their source rocks and distributed in the shallow layers above BHAD, while unconventional tight oil and gas accumulations are close to their source rocks and distributed in the deep reservoir layers below BHAD. The BHAD varies from 3800 to 5000 m (Fig. 3.14a1) for the Cenozoic sandstone in Tarim Basin (Jiang 2015) and from 2800 to 4000 m (Fig. 3.14a2) for Permian sandstone of Junggar Basin (Pang et al. 2015a, b). The BHAD varies from 1200 to 1800 m (Fig. 3.14b1) for Paleozoic formation of Ordos Basin in Central China, a set of clastic rock sedimentation for target sandstone and major source rock strata (Pang et al. 2014). The BHAD changes from 600 to 1000 m (Fig. 3.14b2) for Triassic Xujiahe Formation of the Chuanxi Depression in Sichuan Basin, a set of clastic rock with Member 1, 3 and 5 being argillaceous source rock strata and Member 4 and 5 being sandstone reservoir layers (Yang and Pang 2012). The BHAD is about 4200 m (Fig. 3.14c1) for Tertiary system of Dongpu Sag in Bohai Bay Basin in Eastern China, a set of clastic sedimentary rocks where argillaceous source rock and sandstone reservoir are interbedded (Li and Pang 2004). The BHAD is about 2100 m (Fig. 3.14c2) for Cretaceous system of Songliao Basin, a set of clastic rock, in which the Qingshankou and Nenjiang Formations are the major source rocks and the sandstone strata above, below or between these two formations are reservoir layers

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Fig. 3.14 Distribution of BHAD in six representative basins of China. a1 Tarim Basin, a2 Junggar Basinin, b1 Ordos Basin, b2 Sichuan Basin, c1 Bohai Bay Basin, c2 Songliao Basin

(Ma et al. 2008). In total, more than 26.14 billion tons of oil and gas reserves have been discovered in these six basins. The ratios of proved oil and gas reserves above and below the BHAD are 82% and 18%, respectively (Fig. 3.15a2). The predicted unconventional oil and gas resource potential below the BHAD in the six basins is more than 15.71 × 109 t oil equivalent and 4.71 × 109 t of them have been proved (Ministry of Land and Resources 2009), therefore, the unconventional oil and gas resources below the BHAD have an enormous potential. The reservoirs distribution in other basins around the world follows the same pattern, i.e., conventional oil and gas reservoirs are distributed in shallow areas above BHAD and unconventional oil and gas reservoirs are distributed in the deep areas below BHAD (Shanley et al. 2004). These examples include the Cretaceous sandstone reservoir layers in Western Alberta basin in Canada (Masters 1979), the Jurassic sandstone reservoirs of the San Juan basin in New Mexico (Ridgley et al. 2002), and the Cretaceous sandstone reservoirs of the Wattenberg Field in the Denver Basin in Colorado (Rose et al. 1986). Among the 52,926 oil and gas reservoirs discovered in 1186 basins in the world, 94% are distributed in the areas above the BHAD and only 6% are in areas below the BHAD (Fig. 3.15a1), showing an enormous potential for exploration of unconventional oil and gas resources. It was found that, in all different petroliferous basins, the distributions and/or percentages of unconventional oil and gas reserves below the BHAD and conventional oil and gas reserves above the BHAD are different (Fig. 3.15b). Percentages of unconventional oil and gas resources increase with depth and the unconventional oil and gas resources in

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123

Fig. 3.15 Vertical distribution of oil and gas reservoirs discovered in basins with different temperature gradients over the world controlled by BHAD. a1 Distribution characteristics of 52,926 reservoirs proved in basins over the world; a2 Distribution characteristics of the proven 26.14 billion tons oil equivalent in six representative basins in China, b variation of BHAD in petroliferous basins with different temperature gradients and the distribution of proven reservoirs in the world

the low-heat flow basin have a lower proven rate in deeper area, showing a greater exploration potential. Although BHAD depths differ from 1200 to 4200 m or from altitude − 400 to − 4000 m in different basins, related critical parameters such as the porosity and permeability are almost the same, 10 ± 2% for porosity and 1 mD for permeability, which can be used as identifying criteria for determining BHAD. Therefore, the distribution of BHAD in a basin can be predicted and confirmed by the distribution features of conventional and unconventional oil and gas reservoirs.

3.6.2 Relationship Between the BHAD and Oil and Gas Accumulations Accumulation of conventional and unconventional oil and gas reservoirs and their categories in basins are controlled by BHAD and their relationship are illustrated in Fig. 3.16, in which four categories of conventional oil and gas reservoirs are labeled as anticline trap oil and gas reservoirs (C1), faulted trap oil and gas reservoirs (C2), lithology trap oil and gas reservoirs (C3), and stratigraphic trap oil and gas reservoirs (C4) and four categories of unconventional oil and gas reservoirs are also labeled as tight trap oil and gas reservoirs (U1), tight deep-basin oil and gas reservoirs (U2), tight superimposed oil and gas reservoirs (U3), and tight reformed oil and gas reservoirs (U4). Above the BHAD, oil and gas reservoirs are formed by buoyancy-driven and distributed in traps with unique features, such as oil and gas accumulated at the high points of traps, preserved by cap rocks on their high positions, enriched in layers with high porosities, formed oil and gas reservoirs with high fluid pressure, and separated

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from their source rocks. Below the BHAD, oil and gas reservoirs are formed by nonbuoyancy-driven and distributed in tight reservoirs near source rocks, appearing in unique features such as oil and gas distributed in the low depressions, located in the inverted low position, accumulated in the layers with low porosities, being stable in low fluid pressures. Conventional oil and gas reservoirs usually formed earlier than that of unconventional oil and gas reservoirs in the same reservoir layers. By continuous compaction, a conventional oil/gas reservoir can be converted to an unconventional oil/gas reservoir if its depth reached and exceeded BHAD. In some cases, an unconventional oil/gas reservoir formed under a conventional oil/gas reservoir in the same reservoir layer, making the features of the oil and gas reservoir formed below the BHAD more complicated. BHAD changes with the tectonic evolution of a petroliferous basin, thus modify the formation and distribution of oil and gas reservoirs in the basin. If the overlying strata of a conventional oil and gas reservoir is denuded due to basin uplifting, the original oil and gas in the reservoir may undergo a biodegradation or an oxidative degradation process that produces high-density and high-viscosity oil and asphalt. If the reservoir layers with conventional oil and gas

Fig. 3.16 Relationship between BHAD and oil and gas accumulations. Four categories of conventional oil and gas reservoirs: anticline trap oil and gas reservoirs (C1), faulted trap oil and gas reservoirs (C2), lithology trap oil and gas reservoirs (C3), and stratigraphic trap oil and gas reservoirs (C4). Four categories of unconventional oil and gas reservoirs: tight trap oil and gas reservoirs (U1), tight deep-basin oil and gas reservoirs (U2), tight superimposed oil and gas reservoirs (U3), and tight reformed oil and gas reservoirs (U4)

3.6 Discussion and Conclusion

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accumulations are further compacted through settlement of the basin and sedimentation of strata overlying the reservoir layer, the original conventional oil and gas accumulations can be converted into unconventional tight oil and gas reservoirs. If the tight oil and gas reservoirs are deeply buried and experiences high-temperature pyrolysis, they can be converted into pyrolysis oil and gas reservoirs or totally dry gas reservoirs. The tight oil and gas reservoirs can also be reformed drastically by cracks and fractures generated by folding, faulting or fluid activities in the reservoir layers, creating “sweet spot” of oil and gas due to its high porosity and permeability. In an extreme scenario, if the thickness of the eroded strata is large enough or the basin experiences strong tectonic movements, both conventional and unconventional oil and gas reservoirs formed earlier can be completely destroyed without any oil and gas resources left.

3.6.3 Resource Potentials of Oil and Gas Accumulations Constrained by BHAD Oil and gas amounts generated by, expelled from, and remaining in source rocks in different stages during the basin evolution were calculated from the drilling results of oil and gas reservoirs and the geochemical data of their source rocks for six representative basins in China by using different methods (Jiang et al. 2018; Zheng et al. 2019a, b) and the material balance principle (Pang et al. 2005). The total original oil and gas amounts available for conventional reservoirs formation, tight reservoirs formation and shale reservoirs formation were obtained to evaluate the oil and gas resource potentials in six representative basins (Fig. 3.17). Figure 3.17a shows that the ratios of original conventional hydrocarbon, unconventional hydrocarbon and shale hydrocarbon are about 10%, 44%, and 46%, respectively. The total original hydrocarbon amount for the unconventional tight and shale together is 9 times that for the conventional, with the original hydrocarbon amount for the unconventional tight below the BHAD along being 4–5 times of that for the conventional, showing huge resource potentials of the unconventional oil and gas reservoirs. Figure 3.17b shows predicted favorable areas for tight oil and gas reservoirs formation in the Fuyang reservoir layer in the Songliao Basin with an area of 26 × 104 km2 . The total proven oil and gas reserves are 6.25 × 109 t oil equivalent. In Songliao Basin, the dark mudstones of Nenjiang Formation (K1n1 ) and Qingshankou Formation (K1qn) are the source rocks. The sandstone of Yaojia Formation (K1y) is the reservoir layer. The BHAD of sandstone in Songliao Basin (Fig. 3.14c2) corresponds to the porosity of 12%, permeability of 1 mD, and depth of 2100 m, confirmed by the drilling data from 5401 wells. Above the BHAD, the proven oil and gas reserves are 4.68 × 109 t oil equivalent, majorly in the Daqing Placanticline with 50–500 m longitudinal distance to their source rocks center. Under the BHAD, the tight oil and gas reservoirs are distributed in an area of 0.6 × 104 km2 in the Eastern and Western

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Fig. 3.17 a The relationship between the BHAD of six basins and their original hydrocarbons available for the formation of three types of oil and gas reservoirs. a1 Original hydrocarbons available for shale oil and gas formation (green color, about 50%). a2 Original hydrocarbons available for conventional oil and gas formation (red color, about 10%) above the BHAD and available for tight oil and gas formation (yellow color, about 40%). b The BHAD of the Fuyang sandstone and divided areas favorable for the formation of conventional reservoirs and unconventional tight reservoirs in the Northern Songliao Basin

Depressions closing to their underlying source rocks, the proven oil and gas reserves are 1.57 × 109 t (Feng et al. 2011). In the representative basins of China, the predicted unconventional resource below BHAD is larger than 15.71 × 109 t oil equivalent, 4.71 × 109 t of them have been proved. In the world, 52,926 oil and gas reservoirs have been discovered in 1186 basins, 94% of them are distributed in the areas above the BHAD and only 6% are in the areas below the BHAD, indicating that the fields below HBAD are promising for future explorations of unconventional oil and gas resources.

3.7 Summary The discovery and exploration of unconventional oil and gas resources in large scale since the late twentieth century changed geologists’ understanding of oil and gas reservoirs formation, providing a solution to energy shortage. The unconventional oil production in 2016 of the USA accounted for 41% of its total oil production, the unconventional gas production in China accounted for 35% of its total gas production, showing a strong growth momentum of unconventional oil and gas explorations. Unconventional oil and gas generally coexist with the conventional, sometimes distribute in a separate WPS. Identification and prediction for unconventional

References

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oil and gas resources are prominent challenges for geologists. This study analyzed the drilling results of 12,237 wells in six basins in China and studied the correlations and differences between conventional oil and gas reservoirs and unconventional oil and gas reservoirs by comparing their geological features and formation mechanisms. Migration and accumulation of conventional oil and gas reservoirs are caused dominantly by buoyance-driven, we proved the existence of BHAD, which can be used to describe the deepest hydrocarbon accumulation depth driven dominantly by buoyance. We found that the BHAD controls the distribution of different oil and gas reservoirs and their resource potentials in petroliferous basins. Oil and gas migration and accumulations above the BHAD is dominated by buoyancy-driven, forming conventional oil and gas reservoirs in traps with high porosity and permeability, while oil and gas migration and accumulation below the BHAD is dominated by non-buoyancydriven, forming unconventional oil and gas reservoirs. The depth for BHAD in six basins in China range from 1200 to 4200 m, controlled by several geological factors, such as decreasing with increasing geothermal gradient, decreasing particle size of sandstone. The predicted unconventional oil and gas resource potential below the BHAD in 6 basins of China is more than 15.71 × 109 t oil equivalent, 4.71 × 109 t of them have been proved. In the world, 94% of proved 52,926 oil and gas reservoirs are conventional oil and gas reservoirs and only 6% of them are unconventional oil and gas reservoirs, showing a great promising exploration prospects in the deep area below the BHAD. The major contents of this chapter had been published in Geoscience Frontiers (Pang et al. 2021).

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Chapter 4

Hydrocarbon Accumulation Depth Limit in the WPS

New Understanding: Hydrocarbon Accumulation Depth Limit (HADL) widely exists in exploration wells of petroliferous basins where dry layer ratio, oil and gas saturation and movable oil and gas ratio in reservoir layers tend to approach 0 and the bound water saturation for the reservoir layers reach 100%, corresponding to critical values of sandstone reservoirs with thermal maturity of 2.75 ± 0.25%, pore throat radius of 25 ± 15 nm, and porosity of 3 ± 1%. HADL in petroliferous basins varies with oil and gas components, reservoir lithology and age, sorting and particle size, tectonic movement, and thermal gradient. It changes majorly with formations compaction degree and heat flows, ranging from < 3000 to > 13,000 m if temperature gradient changes from 5 to 1 °C/100 m. Two geological factors result in the formation and distribution of HADL, one is disappearing of the compaction differentials between the inside and outside of reservoir layers, which ends the driving force for oil and gas migration and accumulation, and another one is the depletion of oil and gas generation potential in source rocks, which cuts off providing of oil and gas. All discovered reservoirs and proven reserves as well as potential resources in petroliferous basins in China and over the world are formed and distributed above the HADL, most of the unproven oil and gas resources are mainly distributed in “cold and deep” basins with depth of greater than 4500 m and heat-flow of less than 40 mW/m2 .

4.1 Introduction and Issue Hydrocarbons are energy resources originated from palaeophytic and paleontological remains in sedimentary formations through the process of thermal evolution (Brooks 1935; Bekaert et al. 2018) and distributed in pores of reservoir layers in petroliferous basins (Whitelaw et al. 2019). The earliest time for massive oil and gas formation on the earth is realized to be 1000–1300 Ma (Ghori et al. 2009). Oil and gas explorations target basins with abundant organic matter in sedimentary strata (Cox 1946; Tissot © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_4

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et al. 1984), the increasing demand for oil and gas resources pushes the exploration activities into deep sedimentary strata (Dyman et al. 2002). For example, the Tiber oil and gas pool was discovered in the Gulf of Mexico at a depth of 11,945 m, including water depth (Kennan et al. 2007). A 12,000-m drilling project in the Tarim Basin of western China have discovered a significant amount of deep oil and gas (Jia et al. 2016). The proven reserves with depths greater than 6000 m increased from 66% in 2000 to 92% in 2013, and the predicted maximum depth for oil and gas accumulation is greater than 10,000 m (Sun et al. 2013). On the other hand, the maximum depth for oil and gas accumulation in the Songliao Basin, as defined by 100% thickness ratio of dry reservoirs to total reservoirs, occurred at a drilling depth of less than 4500 m (Pang et al. 2014, 2015), suggesting the deeper areas may not be favorable for oil and gas accumulation. The maximum depth for oil and gas formation, accumulation and preservation in the Earth’s crust remains mysterious ever since petroleum was discovered since in eighteenth century. Abiogenic petroleum hypotheses assume the maximum depth for oil and gas formation and accumulation is much deeper than that of sedimentary basins itself (Lobanov et al. 2013; Huang et al. 2017; Brovarone et al. 2020; Kenney et al. 2002), while biogenic origin hypothesis (Whitelaw et al. 2019; Wood and Sanei 2016) suggested the maximum depth of oil and gas formation and accumulation is controlled by the active source rocks, which generate and expel oil and gas in the evolution of sedimentary basins (Durand 1980; Tissot and Welte 1984; Hunt 1996; Pang et al. 2020). Since the genetic relationship of petroleum and organic matter has been proved (Peters et al. 2005; Magoon et al. 1994) and no commercial petroleum reservoirs from abiogenic origin has been discovered so far (Kenney et al. 2002; Glasby et al. 2006; Höök et al. 2010; Selley et al. 2014), our study does not take the abiogenic origin of petroleum into account. In order to further understanding of the vertical distribution of oil and gas accumulations, we clarify the definition of HADL in this study and discuss the formation mechanism of HADL and its key controlling factors by analyzing the variation trends of oil and gas saturations (So), movable oil and gas ratios (Mo) and dry layer ratios (Ko), permeability (K) and pore throat radius (R) with increasing depth in major petroliferous basins in China.

4.2 Research Method and Identifying Criteria of the HADL 4.2.1 Geology of Research Basins There are six representative petroliferous basins in China, including Songliao Basin, Bohai Bay Basin, Ordos Basin, Sichuan Basin, Junggar Basin and Tarim Basin (Fig. 4.1). These basins have the largest areas and proved oil/gas reserves, the most remaining resource potential and the highest exploration degree (Oil and Gas Resources Strategy Research Center 2009). They are representative of a broad range

4.2 Research Method and Identifying Criteria of the HADL

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Fig. 4.1 Distribution of major petroliferous basins in China, including six representative basins selected to study. They are Tarim Basin, Junggar Basin, Sichuan Basin, Ordos Basin, Bohai Bay Basin and Songliao Basin. The basin area, proved reserves, and potential resources of 10 major basins are shown in the three small charts in the figure (Data from the Oil and Gas Resources Strategy Research Center, Ministry of Land and Resources 2009; Pang et al. 2021a, b, c)

of basin types. From the east to the west, the tectonic environment of these basins changes from extension to compression, the type of basins changes from simple to complex, the number of oil/gas-bearing layers in them increases, the strata age change from young to old and the geothermal gradient changes from high to low. Therefore, tectonic setting, the basin architecture, and oil/gas-bearing properties of reservoirs in these basins are drastically different. These geological settings the six petroliferous basins were documented by literatures (Oil and Gas Resources Strategy Research Center 2009). The drilling results of 12,237 exploration wells from the 6 representative basins were used to quantify HADL and identify its critical conditions, including variation of HADL as well as their impact on oil and gas reservoirs distribution and oil and gas resource potentials. The data set of 52,926 oil and gas reservoirs in 1186 basins worldwide were utilized to confirm the existence of the HADL and discuss their implications for predicting potential oil and gas resources.

4.2.2 Definition of HADL and Its Research Significance HADL is defined as the maximum depth for oil and gas to accumulate on the Earth, beyond which oil and gas cannot accumulate to form commercial reservoirs in reservoir layers in a petroliferous basin (Pang et al. 2022). HADL is a dynamic boundary characterized by critical parameters of the reservoir properties, such as porosity and permeability, pore throat radius and thermal evolution degree. Above the

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HADL, geological conditions are favorable for oil/gas to accumulate as commercial reservoirs.

4.2.3 Identification of the HADL The major challenge to confirm the existence of HADL is that there are no exploration wells or there are very few exploration wells that have reached the HADL in petroliferous basins. We take two steps to solve this problem. First, the drilling results of exploratory wells in a research area or in petroliferous basins were used to simulate the correlations between hydrocarbon-bearing properties (oil and gas saturation, dry layer ratio, movable hydrocarbon ratio, irreducible water saturation, and some others) and essential geological parameters (thermal evolution degree, porosity/permeability, pore throat radius, and some others), and then to determine the critical values of the essential parameters corresponding to HADL, where the dry layer ratios and irreducible water saturation tend to reach 100% and the hydrocarbon saturation and movable hydrocarbon ratio tend to approach 0. Secondly, the vertical variation trend of these essential parameters with increasing depth were statistically analyzed to confirm the depth of HADL. (1) Identifying HADL by Vertical Variation of Dry Layer Ratio in Reservoirs Dry layer ratio is defined as the ratio of dry reservoir layers thickness to total reservoir layers thickness drilled by wells at a given depth interval, dry layers showing no movable fluids in test production (Table 4.1). The HADL in the Central Uplift of Tarim Basin was confirmed from the drilling results of 7180 reservoir layers from 246 exploration wells (Fig. 4.2a). The results indicate that the reservoirs porosity decreases from 28–30 to 2–4% with the increase of depth and that the dry layer ratio of reservoirs increase from 0 to 100% with increasing depth, the critical depth with porosity of 2% and dry layer ratio of 100% confirms the existence of the HADL. The HADL of the Northern Uplift and Kuqa Depression in the Tarim Basin as well as in the other five basins were determined similarly in the same ways. (2) Identifying HADL by Vertical Variation of Irreducible Water Saturation Fluid in the pore of reservoirs consists of irreducible water and free water as well as hydrocarbons measured by nuclear magnetic resonance (Mansfield and Issa 1994). In normal conditions, the irreducible water saturation will increase as the free fluid of water or oil and gas saturation decreases with increasing depth (Scherer 1987). The 100% of saturated irreducible water at a certain depth leads to the ending of oil and gas accumulation. Figure 4.2b1, b2 show the variation of irreducible water saturation with porosity in the Tertiary sandstone of the Kuqa Depression of the Tarim Basin and in the Cretaceous sandstone of Songliao Basin have been plotted, respectively, which illustrate the irreducible water saturation tends to reach 100% when the porosity decreases to 2–4%, showing the formation of HADL. For the

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Table 4.1 Identification parameters for dry layers in testing production Depth of reservoir (m)

Depth of liquid (m)

Daily production Oil (kg/d)

Gas (m3 /d)

Water (L/d)

Days of observation (d)

< 2000

500 m from perforation section

≤ 100

≤ 200

≤ 250

2

2000–3000

1800

≤ 200

≤ 400

≤ 400

2

3000–4000

2000

≤ 300

≤ 600

≤ 500

2

> 4000

Casing allows depth of hollowing

≤ 400

≤ 800

≤ 600

2

Fig. 4.2 Identification of the HADL by vertical bound water saturations and variation of dry layer ratios in all reservoir layers with increasing burial depth. a Drilling results of Paleozoic marine sandstone oil and gas reservoirs in the Central Uplift of Tarim Basin: a1 Drilling results of porosity and fluids with increasing burial depth, a2 variation of relative ratios for 4 kinds of drilling results, a3 correlations among critical parameters related to the HADL of dry layer ratio, burial depth and porosity. b Identification of the HADL by the variation of bound water saturations in sandstone with increasing burial depth: b1 case study of Kuqa Depression, b2 case study of Songliao Basin, cb3 vertical variation of average porosity for major sandstone reservoirs with increasing depth in representative basins of China and the determination of their HADL

studied six basins, all their determined HADLs correspond to a same critical value of porosity with 3 ± 1%, although their depths vary from 4000 to 9000 m (Fig. 4.2b3) due to the different decreasing rates of porosity with increasing depth. (3) Identifying HADL by Vertical Variation of Oil and Gas Saturation and Daily Production Oil and gas saturations are tested by high pressure mercury injection (Shanley et al. 2004; Ougier-Simonin et al. 2016). Figure 4.3a illustrates the variation of oil and gas saturation (Fig. 4.3a1) and daily production (Fig. 4.3a2) with the increase of major reservoirs depth in the Dongpu Depression of Bohai Bay Basin. When the depth is less than 1500 m, the oil and gas saturation is low with an average value of less than 40%, and the reservoirs produce both water and hydrocarbons with low daily

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4 Hydrocarbon Accumulation Depth Limit in the WPS

yield from 0.02 to 32 t/d with a mean of 8.3 t/d. When the depth is between 1500 and 3000 m, the oil and gas saturation increases from 40 to 90%, and the reservoirs produce highest daily yield with an average of 18.6 t/d. When the depth increases to over 3000 m, the fluids yield and oil and gas saturation decrease rapidly. However, when the depth of reservoirs increases to over 5500 m, the irreducible water saturation increases to 100% and the dry layer ratio tends to reach 100%, and neither oil/gas nor water could be extracted, showing the ending of oil/gas accumulation and the existence of the HADL with a critical depth of 5500 m. (4) Identifying HADL by Vertical Variation of Effective Porosity in Reservoirs The pore throat radio distribution and space volume in reservoirs are routinely measured by high pressure mercury injection (Shanley et al. 2004; Ougier-Simonin et al. 2016), low-pressure nitrogen (Zhang and Yang, 2013) and carbon dioxide adsorption (Whitelaw et al. 2019; Ross and Bustin, 2009). Fluid viscosity and capillary pressure exert a strong binding effect on oil and gas fluids in pores when the pore throat radii decrease to a certain value, making these fluid difficult to seepage (Scherer, 1987). Zou et al. (2013) proposed 25 nm as the lower limit of effective pore

Fig. 4.3 a Identification of HADL by variation of oil and gas saturation and daily production of oil and gas for Dongpu Depression, Bohai bay Basin. a1 Variation of oil and gas saturations; a2 variation of gas equivalent yields. b Variation of effective porosity with increasing the thermal maturity of Ro and determination of HADL: b1 pore radius variation of sandstone with increasing the thermal maturity of Ro in Bohai Bay Basin and determination of HADL, b2 pore volume ratio of shale reservoirs with increasing the thermal maturity of Ro in Sichuan Basin and the determination of HADL. c Determination of HADL in sandstone reservoirs of Nanpu Sag in Bohai bay Basin by variation of movable oil ratios in reservoirs with variation of reservoir properties: c1 porosity, c2 permeability, c3 pore throat radius

4.3 The HADL Variation and Key Controlling Factors

137

throat radius for oil and gas accumulation in reservoirs, no effective pore space could be identified with a pore throat radius of less than 25 nm (Zou et al. 2013). Our data show the pore throat radius decreases with increasing depth or thermal maturity Ro. The pore throat radius of 25 nm correspond to the maturity of Ro = 3.55%, indicating the ending of oil and gas accumulation and existence of the HADL (Fig. 4.3b1). The pore diameters of shale as measured by low-pressure nitrogen adsorption and carbon dioxide adsorption are in the range of 2–50 nm and less than 2 nm, respectively, the number of pores smaller than 50 nm in the shale reservoirs of Sichuan Basin increases with increasing Ro apparently, and the non-effective pore volume ratios with pore diameters less than 50 nm in the shale reservoirs increased to 100% as maturity of Ro reaches 3.62%, indicating the ending of oil and gas accumulation and the existence of the HADL (Fig. 4.3b2). (5) Identifying HADL by Vertical Variation of Movable Oil and Gas Ratios in Reservoir Layers Nuclear magnetic resonance (Mansfield and Issa 1994) was used to measure movable hydrocarbon contents in hydrocarbon-bearing cores from drilling wells in the Nanpu Depression, Bohai Bay Basin (Fig. 4.4). The results show that the movable hydrocarbon ratios (the movable oil content to the total hydrocarbon content) in the reservoir layers decreases gradually with decreasing effective porosity and increasing depth until zero. According to the NMR results before and after water flooding, the relationships between the movable oil ratios and porosity, permeability, and pore throat radius were obtained. As illustrated in Fig. 4.3c, HADL exists in the sandstone reservoir layers in the Nanpu Depression of Bohai Bay Basin. The movable oil ratios of the 7 core samples labeled as k1–k7 were 57.4%, 42.4%, 43.4%, 13.7%, 10.8%, 10.1%, and 1.2% respectively, decreasing with decreasing porosity, permeability, and pore throat radius. The HADL is confirmed when the movable hydrocarbon ratios decrease to zero, and the radius, porosity, and permeability of sandstone reservoirs tend to decreases to less than 25 nm, 2%, and 0.02 mD, respectively.

4.3 The HADL Variation and Key Controlling Factors The confirmed HADL was different in the six basins (Table 4.2). Figure 4.5 illustrates the relationship between the essential parameters at HADL for the six basins. It is obvious that the HADL is confirmed by porosity, permeability, pore throat radius, and the thermal maturity of the reservoir layers. Oil and gas reservoir layers in different basins have similar critical values of essential parameters such as porosity (3 ± 1%), permeability (0.01 mD), pore throat radius (35 ± 15 nm) and vitrinite reflectance (2.75 ± 0.25%) at HADL, while the depth of HADLs vary greatly, from < 4000 to > 9000 m. HADL are affected by many geological factors, including the oil and gas composition, reservoir lithology, reservoir age, thermal gradients and tectonic movements, of which the thermal gradient is the most common and most important factor.

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Fig. 4.4 Principle and results of measuring movable hydrocarbon ratios in tight reservoir layers by NMR. a Principles of the NMR experiment examining movable oil, by conducting high pressure water flooding experiment for the sandstone cores, the residual oil contents in the cores at different stages can be measured by the NMR technique, the residual oil that could not been displaced is “dead oil”, and the residual oil displaced in experiment is “movable oil”, b experiment results of movable oil in 7 oil-bearing sandstone cores from four exploration wells in the Nanpu Sag, Bohai Bay Basin

Eastern China

Central China

Western China

Nanpu Depression in Bohai Bay Basin

64

53.2

2.7–3.15

2.5–3.0

1.8–2.8

Junggar Basin 42.3

Ordos Basin

1.5–2.0

44.6

Kuqa Depression in Tarim Basin

2.0–2.5

2.0–2.5

42.3

Northern Uplift in Tarim Basin

Sichuan Basin 61.78

2.0–2.5

Wang et al. (2002)

Liang et al. (1992)

Xu et al. (2011)

Rao et al. (2013)

Feng et al. (2009)

2.0–3.0

2.0–4.0

2.0–4.0

2.0–3.0

2.0–3.0

2.0–4.0

2.0–3.5

0.01

0.02

0.01

0.01

0.01

0.01

0.01

Sandstone permeability (mD)

0.036

< 0.1

< 0.1

0.036

0.025

< 0.1

< 0.1

Pore throat radius of sandstone (µm)

6280/2.96

5350/2.80

6450/3.12

6850/2.61

7990/3.23

6750/2.96

6250/2.72

Depth and Ro of reservoirs (m/%)

Sandstone porosity (%)

References

Heat flux (mW/m2 )

Geothermal gradient (°C/ 100 m)

Predicted critical condition parameters corresponding to the HADL

Geothermal field background

Central Uplift 45 in Tarim Basin

Basin or study area position

Table 4.2 The HADLs and their critical parameters of the six representative basins in China

299/4181

245/8154

71/1220

1789/ 5280

34/1585

76/1410

246/7180

Well number/ reservoir layer number

(continued)

7051/3.3

6493/3.4

7660/3.7

8143/3.1

9143/3.7

8430/3.7

8025/3.5

Predicted ASDL/Ro of source rock (m/%)

4.3 The HADL Variation and Key Controlling Factors 139

64.1–70.7

26

Songliao Basin

3.8–4.2

2.9–3.7

Jiang et al. (2016)

Zuo et al. (2017)

2.0–4.0

2.0–3.0

0.05

0.025–0.036

Sandstone permeability (mD)

< 0.1

025–0.063

Pore throat radius of sandstone (µm)

5050/3.58

5200/3.02

Depth and Ro of reservoirs (m/%)

Sandstone porosity (%)

References

Heat flux (mW/m2 )

Geothermal gradient (°C/ 100 m)

Predicted critical condition parameters corresponding to the HADL

Geothermal field background

Dongpu Depression in Bohai Bay Basin

Basin or study area position

Table 4.2 (continued)

401/ 14,853

2107/ 44,058

Well number/ reservoir layer number

5348/3.8

5682/3.3

Predicted ASDL/Ro of source rock (m/%)

140 4 Hydrocarbon Accumulation Depth Limit in the WPS

4.3 The HADL Variation and Key Controlling Factors

141

Fig. 4.5 The correlation and difference of critical parameters with HADL in six representative basins in China. a Relationship between porosity and burial depth, b relationship among porosity, thermal evolution degree, and dry layer ratio. Their maximum depth is different but other critical parameters are almost the same at the HADL

4.3.1 HADL Variation Controlled by Oil and Gas The maximum depth for oil reservoirs distribution is much shallower than that for the gas reservoirs (Fig. 4.6a). In the Junggar Basin, with the current geothermal gradient at about 1.8–2.8 °C/100 m, the drilling results of the Permian sandstone oil reservoirs have a HADL with depth of 6000 m, porosity of 5%, permeability of 0.7 mD, and thermal maturity of Ro = 2.2% (Fig. 4.6a1). In the Ordos Basin, with current geothermal gradient at approximately 2.5–3.0 °C/100 m, the drilling results of the Permian sandstone gas reservoirs show a HADL of depth greater than 7000 m at less than 2% of porosity, less than 0.01 mD of permeability, and approximately 3.0% of thermal maturity Ro (Fig. 4.6a2). These examples indicate that the depth of HADL for oil is less than that of HADL for gas. Due to much smaller molecular size and weight, natural gas could accumulate in much more tight rocks than oil. Furthermore, the oil would crack or evaporate into gas due to higher temperatures in deep strata and therefore the gas is much stable than oil in deep and ultra-deep strata. Analyses of the proved oil and gas reserves in China’s petroliferous basins show that, almost 90% of the oil reserves distribute in the strata with Ro less than 2.0%, while more than 70% of gas reserves distribute in the strata with Ro from 1.5 to 3.5% (Fig. 4.6a2). Even though, significant amounts of oil have been discovered in ultra-deep strata with Ro larger than 2.0%, the oil survives at high thermal conditions is probably due to their overpressure (Huang et al. 2017) or an unusual carbon–hydrogen fluid

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4 Hydrocarbon Accumulation Depth Limit in the WPS

Fig. 4.6 The HADL variation with hydrocarbon phases and lithology. a Comparison of the HADL for oil in the Junggar Basin (a1) and for gas in the Ordos Basin (a2), oil and gas reserves vertical distribution in six representative basins with increasing thermal maturity of Ro. The HADLs are in accordance with Ro = 3.0% in general, some oil and gas can also be found in reservoirs with Ro > 3.0% due to the existence of fractures in reservoirs (a3). b Comparison of the HADLs of different particle size for reservoirs: b1 relation between porosity and burial depth of different particle sizes for the Palaeogene sandstones in Nanpu Sag of Bohai Bay Basin, b2 relation between dry layer ratio and burial depth interval of different particle sizes for the Palaeogene sandstones in the Nanpu Sag, b3 relation between porosity and burial depth of different particle sizes and sorting sandstones of the Cretaceous in Songliao Basin

evolution (Lobanov et al. 2013; Brovarone et al. 2020), which inhibits hydrocarbon cracking (Hao et al. 2004).

4.3.2 HADL Variation Controlled by Reservoir Layer Lithology The sorting and size of fragment particles in sandstone reservoirs have significant influences on the HADL. Based on the drilling results of oil and gas reservoirs in the Nanpu Depression of Bohai Bay Basin, the HADL increases gradually with increasing particle sizes from siltstone, fine sandstone, medium sandstone to coarse sandstone (Fig. 4.6b1). Statistical analyses show that the larger the particle sizes are, the deeper the HADL is (Fig. 4.6b2). Numerical simulation results on sandstone oil and gas reservoirs with various particle sizes in the Songliao Basin suggest a similar variation trend of HADL (Fig. 4.6b3). For the fine, medium, and coarse sandstone reservoirs, the HADL with 2% of porosity is 1930 m, 2270 m and 2780 m, respectively (Fig. 4.6b3). The sandstones with similar grain sizes but better sorting led to deeper HADL. With the sorting degree from well to medium, the HADL for fine, medium, and coarse sandstone reservoirs with 2% of porosity change from 1930 m to 1900 m, 2270 m to 2230 m, and 2780 m to 2750 m, respectively (Fig. 4.6b3). The HADL variations with lithology are also observed in reservoirs made of carbonate, igneous rock, and shale. In terms of igneous rocks, the HADL of intrusive rocks are also different from those of extrusive rocks and tuff.

4.3 The HADL Variation and Key Controlling Factors

143

4.3.3 HADL Variation Controlled by Reservoir Layer Age The HADL of different reservoirs within the same basin can be different. A younger reservoir generally has a deeper HADL. The HADL for Cenozoic sandstones in the Kuqa Depression of Tarim Basin is about 7990 m with a critical porosity of 2% (Fig. 4.7a), while the HADL of the Paleozoic sandstones of the Northern Uplift of Tarim Basin is only 6,750 m with the same porosity of 2% (Fig. 4.7b). The HADL in the Paleozoic sandstones in the Northern Uplift (6750 m) and the Tazhong Uplift (6250 m) is similar, but significantly less than that of Cretaceous—Cenozoic sandstones in the Kuqa Depression (7990 m) in the same basin, suggesting that the reservoirs age affects the HADL. Compared with younger layers, the older ones underwent longer compaction process, and the reservoirs became tighter at the same depth, which is the key reason for reservoirs with same lithology but different ages have different HADL.

4.3.4 HADL Variation Controlled by Geothermal Gradient The HADLs for six petroliferous basins of China are different due to their different thermal evolution (Fig. 4.8). Petroliferous basins with high heat flux or geothermal gradient have shallower depth of HADL (Fig. 4.9). The heat flow and geothermal gradient of the Songliao Basin and Bohai Bay Basin in eastern China are much higher than that of the other four basins (HF > 60 mW/m2 ; TG > 3.5 °C/100 m), and their HADLs are relatively shallower with depth < 5200 m. The heat flow and geothermal gradient of the Tarim Basin and Junggar Basin in western China are the lowest among the six basins (HF < 40 mW/m2 ; TG < 2.8 °C/100 m), and their depth of HADLs are the deepest with depth > 6850 m. Compared with the above basins in eastern and western China, the heat flow and geothermal gradient of the Sichuan Basin and Ordos Basin in central China are medium (HF = 40–60 mW/m2 ; TG = 2.0–3.0 °C/100 m), and the depth of HADL fall in between 5200 and 6850 m. The temperature for hydrocarbons generation variates from as low as 20 °C to higher than 62 °C (Rowe and Muehlenbachs 1999), compared to lower heat flow or lower geothermal gradient, the higher heat flow and temperature in reservoir layers lead to stronger compaction and higher maturity degree.

4.3.5 HADL Variation Controlled by Other Geological Factors Geological factors, such as reservoir depressurization, temperature reduction, and pore fluid volume dilation caused by hydrocarbon leakage during uplift and erosion

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4 Hydrocarbon Accumulation Depth Limit in the WPS

Fig. 4.7 The HADL varies with reservoirs age in Tarim Basin. a The HADL depth for CretaceousCenozoic sandstones in the Kuqa Depressions is about 8000 m: a1 variation of drilling results with increasing depth, a2 variation of drilling results with decreasing porosity, a3 correlations among critical parameters with HADL. b The depth of HADL for the Paleozoic marine sandstones in the Northern Uplift is about 6750 m: b1 variation of drilling results with increasing depth, b2 variation of drilling results with decreasing porosity, b3 correlations among critical parameters with HADL

of overburden complicate the HADL determination (Wood and Sanei 2016). Theoretically, the maximum depth for oil and gas accumulation in a petroliferous basin can be deeper than the HADL predicted by statistical analysis of drilling results if the whole basin had been uplifted due to the overlying strata eroded. There are two ways to solve this problem. One is to identify the thermal maturity Ro or porosity Φ of the reservoirs with HADL, then calibrating the burial depth (D) by established model of D = f(Ro) or D = f(Φ) beforehand by data from reservoirs without strata erosion. This method has been utilized to confirm the HADLs for the Ordos Basin,

4.3 The HADL Variation and Key Controlling Factors

145

Fig. 4.8 The heat flow evolution in six representative basins of China. The average heat flow values for each basin during the geological history are a 88.6 mW/m2 for Songliao Basin, b 71.7 mW/m2 for Bohai Bay Basin, c 66.9 mW/m2 for Sichuan Basin, d 60.1 mW/m2 for Ordos Basin, e 59.4 mW/m2 for Junggar Basin, and f 49.0 mW/m2 for Tarim Basin

Fig. 4.9 Effects of geothermal fields on depth of HADL in six representative basins in China (Pang et al. 2020). The depth of HADL in the sandstones is distributed between 8765 and 5050 m, which has the general characteristics of continuously shallower from the western basin to the eastern basin, with shallower depth of HADL in basins with higher geothermal gradient

Songliao Basin, and Sichuan Basin. The other one is to investigate the basin evolution and restore the eroded thickness of overlaying strata on reservoirs. The drilling data affected by strata erosion has been excluded from the data used to establish model for predicting HADLs by statistical analysis. This method has been utilized in the Tarim Basin, Junggar Basin, and Bohai Bay Basin, their burial histories were restored and listed in Fig. 4.10.

146

4 Hydrocarbon Accumulation Depth Limit in the WPS

Fig. 4.10 Burial history of reservoir layers in three representative petroliferous basins of China. a In the Bohai Bay Basin, b in the Junggar Basin, and c in the Tarim Basin

4.4 Formation Mechanism of the HADL Two major geological factors lead to the formation of HADLs in petroliferous basins: one is the depletion of oil and gas generation potential in source rocks that cut off provision of oil or gas for reservoirs formation in deep and tight area; the other is the termination of differential compaction or capillary pressure difference between the inside and outside of reservoir layers with increasing depth that ends the driving force for oil and gas migration and accumulation in deep reservoirs.

4.4.1 Depletion of Oil and Gas Generation Potential in Source Rocks Oil and gas source is basic materials for oil and gas reservoirs formation, and the oil and gas accumulation process in reservoirs will be ended when associated source rocks cease to provide oil and gas (Fig. 4.11). The oil and gas expelled from source rocks are originated from transformation of organic matter called kerogen with increasing burial depth (Peters 1986). Kerogen starts to generate oil and gas when the temperature is higher than 60 °C. As long as the generated oil and gas satisfying all types of retention in the source rocks, such as mineral adsorption, solution in water and so on, the extra oil and gas are expelled out of the source rocks with a free state (Pang et al. 2005). With increasing depth and thermal evolution, oil and gas generation and expulsion from source rocks undergo a process from weak to strong, then to weak again and finally exhausted. In the process of oil and gas generation, the original organic matter becomes gradually carbonized, and the atom ratios of H/ C and O/C decrease continuously and reach zero eventually at active source-rock depth limit (ASDL) or hydrocarbon dead line (Pang et al. 2020). The biomarker concentration of steranes and hopanes in oil and gas from both the reservoirs and source rocks gradually decrease with increasing thermal maturity (Mackenzie 1984; Li et al. 2015), and tend to be 0 at the ASDL with maturity of Ro≈3.5%, indicating the exhaustion of hydrocarbon generation potential of source rocks (Pang et al. 2020) and marking the ending of hydrocarbon accumulation (Fig. 4.12).

4.4 Formation Mechanism of the HADL

147

Fig. 4.11 Variation of oil and gas generation potential with increasing burial depth of major source rocks in the six representative basins and confirmation of ASDL (Pang et al. 2020). a Variation of H/C with increasing depth, b variation of hydrocarbon generation potential index “(S1 + S2 / TOC)” with increasing depth, c variation of pyrolysis-released hydrocarbon amount index (“S1 / TOC”) with increasing depth, d variation of chloroform extracted hydrocarbon amount index “A”/ TOC with increasing depth. ASDL-Active Source Rock Depth Limit, refer to the maximum depth for hydrocarbon generation and expulsion from source rocks

4.4.2 Capillary Pressure Difference Termination Outsider and Insider the Reservoir Capillary pressure is resistance for oil and gas migration and accumulation in tight reservoirs, smaller pore throat have larger resistance (Jiang et al. 2014; Wang et al. 2020). However, the capillary pressure difference (CPD) is the driving force for oil and gas migration and accumulation, it can be expressed as the difference of capillary pressure in surrounding rocks (Pcs) and capillary pressure in connected reservoir layers (Pcr ) by equation of CPD = (Pcs – Pcr ), and the Effective CPD is expressed by ECPD = CPD – Pcr > 0, which is realized as the major driving force for oil and gas migration and accumulation in tight media. Theoretically, the minimum critical ECPD to drive hydrocarbons into reservoir layers should be greater than the capillary pressure in reservoir layer, or the capillary pressure in surrounding source rock is more than 2 times of the capillary pressure in reservoir layer, expressed as Pcs ≥ 2 × Pcr . Physical modeling results for oil migration and accumulation confirm that ECPD is a major driving force for oil and gas accumulation (Pang et al. 2013), the minimum critical ECPD to drive oil to migrate from source sands body with particle size (d) to accumulate in connected reservoir sands body with particle size (D) correspond to a ratio of D/d ≥ 2/1. Oil cannot be driven out from source sands body to reservoir sands body by ECDP if the ratio of D/d is less than 2/1. Larger ECPD leads to higher saturation of oil accumulation in reservoir sands body: the

148

4 Hydrocarbon Accumulation Depth Limit in the WPS

Fig. 4.12 Variation of absolute biomarker concentration with increasing thermal maturity in hydrocarbons and source rocks in the Bohai Bay Basin and in the Tarim Basin and confirmation of their ASDL. a Variation of absolute biomarker concentration of oil in reservoirs with increasing its thermal maturity, b variation of biomarker concentration of oil in the source rocks with increasing its thermal maturity

saturation of oil in particle size D will increase with increasing D/d if D is constant; the oil saturation in D will decease with increasing D if D/d is constant, implying that ECPD is the major driving force for oil and gas migration and accumulation in tight media, and that the smaller the particle size, the more important the ECPD is for oil and gas accumulation in deep tight reservoir.

4.4.3 Compaction Difference Termination Outsider and Insider the Reservoir The differential compaction between mudstone and sandstone with increasing depth results in variation of three essential factors, which jointly lead to the end of hydrocarbon accumulation. Firstly, the differential compaction between mudstone and sandstone with increasing depth finally lead to the depletion of oil and gas generation potential of source rocks and the formation of ASDL, which cut off provision of oil and gas (Fig. 4.13a); Secondly, the differential compaction with increasing depth decrease the thickness, porosity (Fig. 4.13b) and pore throat radius (Fig. 4.13c) of all

4.4 Formation Mechanism of the HADL

149

strata, increase the resistance of capillary pressure to oil and gas migration in reservoirs, which finally lead to immovable of oil and gas in tight reservoir layers; Thirdly, the differential compaction with increasing depth first increase the ECPD between mudstone and sandstone and then decrease the ECPD between the surrounding rocks and inner reservoirs, which finally eliminate the ECPD and lead to the end of oil and gas accumulation in deep tight reservoirs. This process could be divided into four stages (Fig. 4.13d): in the first early stage (I1 ) of depth from surface to 500 m, the sandstone and surrounding rocks are not very compacted, the value of ECPD is very small or negative, the reservoirs cannot accumulate a lot of oil and gas or be featured with very low saturation of oil and gas; in the first late stage (I2 ) of depth from 500 to 1500 m, the compaction rate of surrounding shale is more than 2–5 times larger than that of sandstones (Pang et al. 2013), which result in rapid increase of the ECPD value and a lot of oil and gas are accumulated in reservoir layers with increasing depth, driven dominantly by buoyance due to large porosity and permeability of reservoir layers; in the second stage (II) of depth from 1500 to 4000 m, the buoyance gradually decrease to its critical minimum value at BHAD (Pang et al. 2021a) and the ECPD gradually increase to its critical maximum value, combination of buoyance and ECPD result in highest saturation of oil and gas in reservoir layers; in the third stage (III) of depth from 4000 m to HADL, the migration and accumulation of oil and gas in reservoir layers are dominantly by ECPD due to very small of their porosity and throat radius, and finally the ECPD gradually decrease with increasing depth to disappear (Jiang et al. 2014; Wang et al. 2020), which leads to the end of oil and gas accumulation and the formation of HADL at the depth of ≥ 5600 m; in the fourth stage (IV), oil and gas reservoirs cannot be formed in the deeper area because of non-existence of effective source rocks, effective reservoir layers, and effective CPD, the oil and gas reservoirs formed previously in the areas above the HADL would be reformed or completely destroyed in this stage by tectonic movements or further compaction.

4.4.4 Variation of Geothermal Gradients in Petroliferous Basins Except for some special cases, the HADL in petroliferous basins generally decreases with increasing heat flows or geothermal gradients as showed in Fig. 4.14. When a source rock in a petroliferous basin is surrounded by extremely thick and plastic salt beds, and strong disequilibrium compaction is developed inside the source rock, the original porosity and generated hydrocarbons can be preserved in area below the HADL at a depth greater than 13,000 m, such as in the sedimentary strata in both Pre-Caspian Basin and North Caspian Basin (Nevolin et al. 1995; Lerche 2017). Similarly, in some ancient special reservoir rocks, such as carbonate reservoir rocks, volcanic reservoirs or metamorphic reservoirs surrounded by young and huge thick fine-grained shale rocks, the compaction is not completed and the hydrocarbons

150

4 Hydrocarbon Accumulation Depth Limit in the WPS

Fig. 4.13 The dynamic mechanism for the formation of the HADL in deep and tight reservoir layers of petroliferous basins during their evolution with increasing depth. HGTD— Hydrocarbon Generation Threshold Depth; HETD—Hydrocarbon Expulsion Threshold Depth; BHAD—Buoyance-driven Hydrocarbon Accumulation Depth; ADSL—Active Source-rock Depth Limit

accumulated in earlier time could be preserved at a burial depth greater than the predicted HADL. For example, hydrocarbons can be stored beneath the Cambrian salt layers in the North Caspian Basin and Tarim Basin (Nevolin et al. 1995; Song et al. 2014). In addition, anaerobic degradated hydrocarbons can also exist in deep reservoir layers (Aitken et al. 2004), being inconsistent with the HADL prediction. The HADL is not the dead line for the existence of all hydrocarbons, but is the depth limit for commercial oil and gas reservoirs to form, the previously formed oil and gas reservoirs could be preserved in area below the HADL at special geological conditions.

4.5 Implication of the HADL for Potential Resource Prediction The HADL controls the maximum depth for oil and gas accumulations in petroliferous basins and the promising domain for oil and gas exploration, as well as their resource potentials.

4.5 Implication of the HADL for Potential Resource Prediction

151

Fig. 4.14 The occurrence and distribution of oil and gas reservoirs controlled by the HADL in petroliferous basins with different geothermal gradients. Basins with low geothermal gradient have large area for oil and gas reservoirs to form and distribution. The HADL depth varies from less than 3000 m to larger than 13,000 m with the temperature gradients change from 5.0 to 1.0 °C/100 m. All discovered oil and gas reserves in the six representative basins of China are distributed in area above the HADL. Besides, all proved 52,596 oil and gas reservoirs from 1186 basins are distributed in area above the HADL. All data are from Chinese oil companies and from the IHS Energy Group (Pang et al. 2012)

4.5.1 Predicting Promising Areas for Oil and Gas Exploration Distribution of oil and gas reservoirs in petroliferous basins is controlled by the HADL. Figure 4.14 illustrates the distribution pattern of proven oil and gas reserves and the characteristics of discovered oil and gas reservoirs are controlled by the HADL, which are confirmed by 14 representative petroliferous basins across the world. Ten basins of them were selected for their proven abundant conventional and unconventional reserves, and twelve basins were selected for their vastly different heat flow values, making it possible to construct a whole pattern of oil and gas reservoir distribution, applied to represent many types of basins in the world. Although the HADL was controlled by many factors, such as the lithology, strata age, particle size, overlying strata erosion and so on, the geothermal gradient is realized as the most significant controlling factor. Specifically, the HADL becomes shallower with increasing geothermal gradients. The distribution of proved 52,926 oil and gas reservoirs in 1186 basins worldwide is consistent with the pattern described in Fig. 4.14.

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4 Hydrocarbon Accumulation Depth Limit in the WPS

The controls of the HADL on oil and gas reservoirs distribution were summarized in three aspects. First, the HADLs exist in all petroliferous basins across the world, all the oil and gas reserves discovered in six representative basins in China and the commercial oil and gas reservoirs distributed worldwide are distributed in the domain above the HADL which is corresponding to thermal maturity of Ro = 3.0% and permeability of K = 0.01 mD; Secondly, the HADL formation was controlled by several geological factors, including the decrease of porosity and permeability in reservoir layers due to their compaction, the disappearing of driving force or the ECPD between the inside and outside of reservoir layers with increasing depth, the depletion of hydrocarbon generation potential, and the depth of HADL decreases with increasing geothermal gradients; Thirdly, the risks for oil and gas exploration in deep areas (> 4500 m) are different for different types of petroliferous basins, the “Cold Basins” with lowest heat flows (< 40 mw/m2 ) have the largest favorable domain and greatest potential for oil and gas exploration, their HADL is ranging from 9000 to 13,000 m; the “Hot Basins” with highest heat flows (> 60 mw/m2 ) have the smallest domain and smallest potential for oil and gas exploration, their HADL is ranging from 3000 to 5000 m; the “Warm basins” with moderate heat flows (40–60 mw/m2 ) have moderate domain and moderate potential for oil and gas exploration, their HADL is ranging from 5000 to 9000 m.

4.5.2 Evaluating Oil and Gas Resource Potentials The area (S), thickness (H), organic matter abundance (TOC) and type (KTI), and thermal maturity (Ro) of source rocks above the HADL in a petroliferous basin determine its total oil and gas generation amount and resource potentials (Pang et al. 2005). The hydrocarbon amount expelled from source rocks above BHAD (Pang et al. 2021b, 2012; Guo et al. 2017) is favorable for the formation of conventional reservoirs and dominantly controlled by buoyancy-driven; the hydrocarbon amount expelled from the source rock beneath the BHAD is favorable for the formation of unconventional tight reservoirs and dominantly controlled by non-buoyancy-driven, and the hydrocarbon amount retained in source rocks mainly forms shale oil and gas reservoirs (Fig. 4.15) (Pang et al. 2021c). Figure 4.16 illustrates the distribution of generated oil and gas amount and proven reservoirs/reserves with increasing maturity and burial depth. Figure 4.16a shows the vertical distribution of original hydrocarbon amount generated by main source rocks in the six petroliferous basins in China. The hydrocarbon amount expelled out of source rocks and available for forming conventional resources in red color ranges from 8.7 to 11.8% of the total generated hydrocarbon amount, with average value of 10.3%. The expelled hydrocarbon amounts available for forming unconventional tight resources in yellow color ranges from 35.0 to 54.3% of the total, with a mean of 45.3%. The hydrocarbon amount remained in the source rocks available for forming shale oil and gas resources in green color ranges from 34.7 to 54.1%, with an average of 44.4%. The total original hydrocarbon amount for the formation of unconventional resources is approximately

4.5 Implication of the HADL for Potential Resource Prediction

153

Fig. 4.15 Hydrocarbon thresholds and their controlling on hydrocarbon generation and resource potential distribution in Chinese petroliferous basins. a Distribution characteristics of oil and gas reservoirs and major source rocks of Qingshankou Formation in Songliao Basin of China. HET— Hydrocarbon expulsion threshold of 750 m with Ro ≈ 0.6%; BHDL—Buoyance-driven hydrocarbon depth limit of 1850 m with Ro ≈ 1.2%; HADL—Hydrocarbon accumulation depth limit of 4900 m with Ro ≈ 3.0% (Pang et al. 2021b). b Vertical distribution of original hydrocarbon amounts generated by main source rocks in 6 representative petroliferous basins of China: Red–Original hydrocarbon amount available for the formation of conventional oil/gas reservoirs; Yellow–Original hydrocarbon amount available for the formation of unconventional tight oil/gas reservoirs; Green–Original hydrocarbon amount available for the formation of unconventional shale oil/gas reservoirs

9 times of that for conventional resources. Statistical analysis results show that 168.6 × 108 tons reserve of oil (red) and 92.8 × 108 tons reserve of oil equivalent gas (yellow) have been discovered in the six basins in China (Fig. 4.16b1). The proven oil and gas reserves decrease with increasing burial depth, more than 50% of the remaining oil and gas resources are mainly distributed in petroliferous basins with burial depth greater than 4500 m according to the distribution of hydrocarbon generation amount from source rocks. All the 52,926 oil and gas reservoirs discovered in 1186 basins in the world have the same distribution characteristics (Fig. 4.16b2), showing that more than 75% of undiscovered oil and gas resource exist in basins with burial depth greater than 4500 m. The proved oil and gas reserves in China are about 33.95 billion tons, of which 82.7% are conventional oil and gas, 12.3% are tight oil and gas, and the rest 5.0% are shale oil and gas. Approximately 544.02 billion tons of oil and gas reserves are discovered in the world (Pang et al. 2021c), of which 91.6% are conventional oil and gas, 3.1% are tight oil and gas, and 5.4% are shale oil and gas. More than 90% of the discovered oil and gas reserves in the world come from the conventional but its original hydrocarbon amount is only about 10% of the total generated hydrocarbon, implying less conventional oil and gas potential resources remained to be discovered in future. However, less than 10% of the proven oil and gas reserves come from the unconventional oil and gas in the world, but their original hydrocarbons amount is larger than 90% of the total generated hydrocarbons, implying much more unconventional potential resources remained in deep strata to be explored by us in future.

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Fig. 4.16 The HADL controlling the distribution of generated hydrocarbon amount, proved reservoirs/reserves and unproved oil/gas resources with increasing maturity and burial depth. a Original hydrocarbon amounts provided by source rocks available for the formation of conventional resource (Red) above the HADL, unconventional tight resources (yellow) below the HADL formation and unconventional shale resources (green) within source rocks (Pang et al. 2021b). b Distribution of proven 26.14 billion tons reserve of oil equivalent and remaining resource potentials in different depths of 6 representative basins in China (b1) and Distribution of discovered 52,926 oil and gas reservoirs and remaining resource potentials in different depths of 1186 basins in the World (b2)

4.6 Summary The horizontal distribution and periodic accumulation of oil and gas in reservoir layers are well understood. However, our understanding about the vertical distribution of oil and gas accumulations in reservoir layers is not clear and remains mysterious to some extent. We proposed a concept of Hydrocarbon Accumulation Depth Limit (HADL) to characterize the hydrocarbon’s vertical distribution in petroliferous basins, which is determined by statistical analyses of the variation trends of reservoir layers’ essential parameters, including oil and gas saturations (So), movable oil and gas ratios (Mo) and dry layer ratio (Ko), when the depth is increased. A total of 80,762 drilling results from 12,237 exploration wells in six representative petroliferous basins in China were collected and analyzed. The reservoir layers’ essential properties of the So, Mo, Ko and their correlations with geological parameters such as the porosity, permeability, pore throat radius and thermal evolution degree were investigated. The critical values of So, Mo and Ko that define HADL were quantified to be So = 0, Mo = 0 and Ko = 100. Our study indicates that the depth of HADL in petroliferous basins varies from less than 3000 m to more than 13,000 m, depending on the hydrocarbon composition, reservoir lithology, reservoir age, geothermal gradient,

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tectonic movement, etc. Two factors play an essential role in the formation and variation of HADL: (1) the depletion of hydrocarbon generation potentials of source rocks which cuts off hydrocarbon contribution to reservoirs formation and (2) the termination of differential compaction which eliminates capillary pressure difference between the outer surrounding rocks and inner reservoir layers, ending the dominant driven force for hydrocarbon migration and accumulation in deep and tight reservoir layers. All proven oil reserves of 33.95 billion tons equivalent in China, the discovered 52,926 oil and gas reservoirs over the world as well as their unproved potential resources, are distributed in the area above the HADL. The major contents of this chapter had been published in Gondwana Research (Pang et al. 2022).

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Chapter 5

Active Source-Rock Depth Limit in the WPS

New Understanding: Active Source-rock Depth Limit (ASDL) is the maximum burial depth for source rocks to generate and expel oil and gas. ASDL marks the depletion of hydrocarbon generation and expulsion potentials from source rocks, and it commonly exists in petroliferous basins. We found the thermal maturity of Ro=3.5% can be regarded as the identification criterion of the ASDL in general geological conditions. The depth of ASDL for source rocks in all basins over the world varies from 3,000 m to 16,000 m, and this variation is mainly caused by heat flow, kerogen type, age of source rock strata, and tectonic movement. The depth of ASDL in a basin is deeper when the basin’s heat flow is low and/or the kerogen type of source rocks is oil-prone. Tectonic uplift of source rock strata can significantly shallow the depth of ASDL. All types of fossil fuel resources, including coal, conventional and unconventional oil and gas are formed and distributed above the ASDL. A basin can be vertically divided into three fields by the hydrocarbon expulsion threshold, the active source-rock depth limit for oil, and active source-rock depth limit for gas. These three fields are favorable for the formation of different types of oil and gas reservoirs.

5.1 Introduction and Issue Unconventional oil and gas resources account for 85.5% of total fossil fuel resources in 2016 (B.P. Global 2017). Due to the important role of fossil fuel in the world energy, a lot of research has been done on them in the past decades, mainly including their plane distribution in various types of sedimentary basins (Tissot and Welte 1978; Wang et al. 1997; Gautier et al. 2009) and their temporal distribution through the past 1.6 billion years in the geological history (Wang et al. 2016). However, the vertical distribution of oil and gas as well as other fossil fuel resources, especially the maximum preservation depth, remains ambiguous because of different understandings of the oil and gas resource origins and the great variations of the depths from basin to basin (Kenney et al. 2002; Peters et al. 2005; Pang et al. 2015). © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_5

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As global demand for energy keeps rising, oil and gas exploration is rapidly expanding to deeper and more challenging regions of the Earth (Dyman et al. 2002). Currently, the world’s deepest commercial oil and gas reservoir is located at the Mexico Gulf Basin with a depth of 11,945 m including water depth (Transocean 2009). In China, the deep (> 4500 m) and ultra-deep (> 6000 m) oil and gas reservoirs are mainly found in the Tarim Basin where the amount of deep oil and gas reserve is estimated to account for more than 90% of the total proved reserves (Pang et al. 2015). In order to boost oil and gas supply to support fast economic growth, China initiated research programs developing 10,000 m-scientific drilling rigs and funded the National Basic Research Program (973 Program) to better understand the deep oil and gas accumulations in petroliferous basins (Jia et al. 2016). One major challenge for deep oil and gas exploration comes from the significant variation of reservoir depths in different basins and the uncertainty it poses to oil and gas resource assessment. In some basins, dry layers, reservoir layers with no oil or gas, are prevalent at a depth of 4500 m or less, whereas in some other basins, the maximum burial depth for oil and gas accumulations is predicted to be more than 10,000 m. To date, the maximum depth to which oil and gas reservoirs can be formed and preserved in the Earth’s crust remains unresolved. Some researches supporting the abiogenic petroleum origin believe that the maximum depth of oil and gas reservoirs occurrence is much deeper than the maximum depth of petroliferous basins themselves (Gold 1993; Kenney et al. 2002). Growing evidence, however, supports that oil and gas are of biogenic origin and suggests that the maximum depth of oil and gas reservoirs is critically controlled by the depth of active source rocks which generate and expel oil and gas in sedimentary basins (Tissot and Welte 1978; Durand 1980; Hunt 1996).

5.2 The Source of Materials and Research Methods 5.2.1 Research Areas and Data Collection To solve relative problems and to understand the process of oil and gas accumulations, six representative petroliferous basins in China was selected in this research, which have the highest exploration degrees (Fig. 5.1; Table 5.1), to identify the maximum depth of oil and gas resources in each basin and investigate factors leading to the variation of the maximum depth. Considering that the genetic relationship between oil/ gas and organic matter in the source rock has been proved and widely accepted, this study will not discuss the abiogenic oil and gas origin (Magoon and Dow 1994; Peters et al. 2005), besides, no commercial oil and gas reservoirs of abiogenic origins have been discovered to date (Kenney et al. 2002; Höök et al. 2010; Selley and Sonnenberg 2014). In this study, geological and geochemical data of 13,634 source rock samples from 1286 exploration wells in six basins were examined. The maximum depth for the formation and occurrence of oil and gas resources in these basins were determined. Major geological factors influencing the maximum depths of active

5.2 The Source of Materials and Research Methods

161

Fig. 5.1 Location of six representative petroliferous basins and five coal-accumulation areas in China. The studied petroliferous basins are plotted on the China mainland and pigmented with different colors. The five coal-accumulation areas are bounded by large geological structural belts and are mapped according to Zhu (2011)

source rocks were analyzed and their controlling on the distribution of oil and gas resources were discussed. We mainly examined active source rock vertical distributions in six representative basins in China, including the Songliao Basin and Bohai Bay Basin in Eastern China, the Sichuan Basin and Ordos Basin in Central China, and the Tarim Basin and Junggar Basin in Western China. For each basin, we utilized at least four different indicators detailed in Sect. 2.2 to determine the ASDL. The data were obtained from PetroChina and Sinopec, available through the PANGAEA database: https://doi.pangaea.de/10.1594/PANGAEA.900865 (Pang et al. 2019). We also investigated the relationship between the ASDLs and the distributions of 52,926 reservoirs in 1186 basins over the world according to the database of IHS (2010) to verify its universality.

5.2.2 Formation Mechanism and Characterization of ASDL Active source rocks are sedimentary rocks rich in organic matter and capable of generating oil and gas. In the evolution history of a basin, source rocks are activated and

Fault depression basin

Rift-fault basin

Songliao Basin

26, 5400

20, 5800

37, 6100

Ordos Basin Superimposed basin

Bohai Bay Basin

26, 7800

Superimposed basin

Sichuan Basin

38, 8900

Junggar Basin

Complex superimposed basin

53, 9100

Basin area (104 km2 ), maximum depth (m)

Tarim Basin Complex superimposed basin

Basin type

69.0, 4.00

64.8, 3.20

62.9, 2.75

58.3, 2.35

45.0, 2.30

43.0, 2.00

Heat flow (mW/m2 ), geothermal gradient (°C per 100 m)

Basin name Basic features of representative basins

*Ro = 0.618 * RoB + 0.40, RoB is solid bitumen reflectance (%)

Eastern China

Central China

Western China

Basin location

2, 3

1, 1

3, 4

6, 6

4, 5

5, 2

National ranking of reserves, resources

Jurassic–Cretaceous Shale

Paleogene Shale

Carboniferous–Permian Coal strata

Triassic Shale

Permian Shale

Cambrian–Ordovician Carbonate

Age and lithology

1.0–4.0

1.0–4.0

2.0–6.5

1.0–3.0

0.5–3.5

0.2–5.0

Organic matter abundance (TOC; %)

Features of main source rocks

Table 5.1 Geological and geochemical characteristics of the main source rocks in six representative basins in China

I–II

I–II

II–III

II–III

I–II

I–II

Organic matter type

3.6

2.7

2.8

3.2

2.5

3.7*

Maximum measured maturity (Ro, %)

162 5 Active Source-Rock Depth Limit in the WPS

5.2 The Source of Materials and Research Methods

163

producing oil and gas at certain conditions, such as the generally regarded threshold of temperature is about 60 °C (Tissot and Welte 1978; Peters and Cassa 1994). With further increasing the burial depth of the source rocks, the potential amount of hydrocarbons generated in the source rocks decreases and eventually approaches zero. The Active Source Rock Depth Limit (ASDL) is defined as the maximum burial depth for source rocks to generate and expel oil and gas. In addition to the burial depth, the ASDL can also be characterized by other parameters of source rocks, such as the thermal maturity of organic matter, the porosity of reservoir layers connecting to the source rocks. The potential amount of oil and gas that can be further generated from a source rock sample cannot be directly measured, but can be evaluated based on many experimentally measurable parameters, such as the atomic ratios of hydrogen to carbon (H/C) and oxygen to carbon (O/C) of the remaining organic matter in the sample. The generation of oil and gas from organic matter is the process of condensation of the aromatic nuclei that enriches carbon by deoxygenation and dehydrogenation. The process can be experimentally studied by measuring the decrease in the atomic ratios of H/C and O/C (Tissot et al. 1974). In theory, organic matter in source rocks eventually evolves to graphite with increasing thermal maturity of Ro to a high value and the atomic ratios of H/C and O/C drop to zero (Fig. 5.2), indicating the active source rocks no longer produce oil and gas and thus reach the depth of ASDL.

Fig. 5.2 The identification of ASDL in process of hydrocarbon generation, expulsion, and retention of source rocks with increasing depth and their relationship

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5 Active Source-Rock Depth Limit in the WPS

Rock-Eval pyrolysis parameters can also be applied to identify the ASDL, such as the hydrocarbon generation potential index of “S1 + S2 ”/TOC. “S1 ” is the hydrocarbons amount released from a source rock sample when it is heated from room temperature to 300 °C, and “S2 ” is the hydrocarbons amount released from 300 to 600 °C. TOC is the measured total organic carbon weight in the source rock sample (Espitalie et al. 1985). The concept of hydrocarbon generation potential index was proposed by Zhou and Pang (2002). Pang et al. (2005) utilized the index to measure the quantity of hydrocarbons that can be generated and expelled from a single unit weight of organic carbon. The index generally increases with increasing burial depth when the thermal maturity of Ro is low and then decreases with increasingly higher burial depth or thermal maturity of Ro. The turning point of hydrocarbon generation potential index corresponds to the hydrocarbon expulsion threshold (HET) which was proposed by Pang et al. (1997). The Hydrocarbon Expulsion Threshold (HET) indicates that oil and gas begin to be expelled from the source rock. As the expulsion continues, the hydrocarbon generation potential index gradually decreases. When the hydrocarbon generation potential index approaches zero, source rocks can no longer expel oil and gas and then reach the ASDL (Fig. 5.2). Along with the evolution of oil and gas generation potential index, the hydrocarbon expulsion ratio (Qe), the hydrocarbon expulsion rate (Ve) and the hydrocarbon expulsion efficiency (Ke) of the source rocks also evolve with the thermal maturity of Ro. Qe represents the hydrocarbons amount expelled from a unit weight of organic carbon; Ve represents the hydrocarbons amount expelled from a unit weight of organic carbon when the burial depth increases by 100 m; Ke represents the ratio of the cumulative amount of hydrocarbons expelled from source rocks to the cumulative amount of hydrocarbons generated by source rocks. When the source rocks reach ASDL, the Qe and Ke approach constant values and Ve approaches the value of zero (Fig. 5.2). Hydrocarbon generation is the transformation of original organic matter (also called as kerogen), to transitional organic compounds and finally to hydrocarbons (Behar et al. 2006). When the amount of transitional organic compounds (also called as residual hydrocarbons, expressed in “S1 ” or “A”) is decreased to zero, the hydrocarbon generation potential of source rocks is also exhausted. Experimentally, “A” is the amount of hydrocarbons extracted by a chloroform solution from a source rock sample. Because some non-hydrocarbon compounds are also extracted, “A” is generally larger than “S1 ”. The residual hydrocarbon content index of “S1 ”/TOC and “A”/TOC, which represents the quantity of oil and gas retained in per unit weight of organic carbon, can therefore be utilized to identify the ASDL. Previous studies (Zhou and Pang 2002; Pang et al. 2005) indicate that the source rocks reach the HET when the residual hydrocarbon content index reaches its maximum value during their evolution with increasing depth. After that, the index begins to decrease, and the source rocks finally become inactive to reach the ASDL when the residual hydrocarbon content index decreases to a minimum value. In summary, the parameters listed in the section, including H/C, O/C, “S1 + S2 ”/TOC, “S1 ”/TOC, “A”/TOC, Ve and Ke, all trend as a function of source rock burial depth of D or thermal maturity of Ro. The ASDL can thus be represented as the critical values of D or Ro when the

5.3 Identification of ASDL

165

indexes of H/C, O/C, “S1 + S2 ”/TOC, “S1 ”/TOC, “A”/TOC, and Ve approach zero or when Ke approaches a constant value.

5.3 Identification of ASDL 5.3.1 The Identification of ASDL in the Junggar Basin The Junggar Basin located in Western China is used as an example to illustrate the identification of ASDL in process of hydrocarbon generation, expulsion, and retention of source rocks with increasing depth and their relationship (Fig. 5.3). The same methods were applied to study the other five basins, and the results are shown in Figs. 5.4, 5.5, 5.6, 5.7 and 5.8 and Table 5.2. The oil and gas generation and accumulation in the Junggar Basin are mainly controlled by the whole petroleum system of Permian (Wang et al. 2001). Previous geology and geochemical data demonstrate that its main source rocks are Permian shales, and its main reservoirs are sandstones in the Permian, Triassic, and Jurassic Formations, capped by the mudstones of the Upper Triassic, Lower Jurassic, and Lower Cretaceous, respectively (Cao et al. 2005). A few Carboniferous volcanic reservoirs are found to distribute in structural highs near fault zones and unconformities, and the hydrocarbons in these reservoirs are also primarily derived from the Permian shales (Chen et al. 2016; Wang et al. 2018). According to the analyses of fluid inclusions and basin modelling, the Permian source rocks started generating oil and gas since the Middle-Late Permian due to a rifting process-related high heat flow, and the main hydrocarbon accumulation period is from the Triassic to the Paleogene (Wang et al. 2001; Cao et al. 2005). The Whole Petroleum Systems in the other five basins were also studied by other researchers (Zhou and Littke 1999; Xiao et al. 2005; Wu et al. 2008; Ping et al. 2017; Zhu et al. 2018). In the method section, we proposed theoretical threshold values of different geochemical parameters or indexes to identify ASDL. In practice, envelope lines enclosing all sample data points are utilized to show the overall trends of how these parameters change with increasing burial depth or thermal maturity. The interceptions of the envelope lines with these threshold values confirm the existence of the ASDL for source rocks. This envelop method has been widely and successfully applied in a variety of basins in China, and numerous studies containing different geochemical data and mathematical models have been published (Peng et al. 2018; Jiang et al. 2016; Pang et al. 2004; Zhou and Pang 2002). It is found that the profiles of hydrocarbon generation potential index and residual hydrocarbons are overall bell-shaped, although details vary according to the source rock types different lithologies and organic matter types. On the other hand, due to the lack of data from ultra deep wells, the envelope method may have some uncertainties. In this case, the ASDL can be identified by extrapolating the profiles according to the variation trend patterns

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Fig. 5.3 Identification of ASDL in the Junggar Basin by using different indicators of source rocks with increasing depth. a Atom ratio of H/C; b Residual hydrocarbon amounts of “A”/TOC (b1) and “S1”/TOC (b2); c Source rocks’ parameters of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

established based on the available data at different burial depths or thermal maturities, the envelope lines employed in this study are guided by well-established models and trends derived from actual geochemical data analysis. Figure 5.3a illustrates the variation of atomic H/C ratios for source rock samples from the Permian shales with increasing burial depth. The average atomic H/C ratio decreases sharply at a depth of about 6000 m, beyond which there are no samples with atomic H/C ratios greater than 1.5, the intercept of the dashed line on the vertical axis marks the ASDL, corresponding to the depth (D) of 8350 m and the maturity degree of Ro ≈ 3.0%. Figure 5.3b illustrates the variation of residual hydrocarbon amounts in source rock samples, expressed in “A”/TOC or “S1 ”/TOC, with increasing burial depth. Initially, the residual hydrocarbon amounts increase with depth because the hydrocarbons are generated but not yet expelled out of the source rocks. Their mean value reached the maximum at the depth of 3500–4000 m or at Ro ≈ 1.0%, corresponding to the hydrocarbon expulsion threshold (HET). With further increase of depth, the amount of residual hydrocarbon starts to decrease, and eventually reaches zero at a depth of 7850–7960 m and a maturity degree of Ro = 3.0%, indicating the existence of the ASDL. Figure 5.3c illustrates the change of hydrocarbon generation potential index of (“S1 + S2 ”)/TOC, hydrocarbon expulsion ratio of Qe, hydrocarbon

5.3 Identification of ASDL

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Fig. 5.4 Identification of ASDL in the Tarim Basin using variation of different indicators with increasing depth or thermal maturity of Ro, including the atom H/C ratios (a), residual hydrocarbon amounts of “A”/TOC (b1) and “S1 ”/TOC (b2), and the variation of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

Fig. 5.5 Identification of the ASDL in the Sichuan Basin using different indicators with increasing depth or maturity degree of Ro, including variation of residual hydrocarbon amounts “A”/TOC (a) and “S1 ”/TOC (b), and the variation of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

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Fig. 5.6 Identification of the ASDL in Ordos Basin using different indicators with increasing depth or maturity degree of Ro, including the variation of residual hydrocarbon amounts of “A”/ TOC (a) and “S1 ”/TOC (b), and the variation of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

Fig. 5.7 Identification of the ASDL in the Bohai Bay Basin using different indicators with increasing depth or maturity degree of Ro, including the variation of H/C ratios (a), residual hydrocarbon amounts (b), and the variation of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

expulsion rate of Ve and hydrocarbon expulsion efficiency of Ke for the source rock samples with increasing burial depth. These results indicate an ASDL of 8200 m with Ro = 3.0%, in good agreement with the ASDL values obtained in Fig. 5.3a, b. In addition, the HET is confirmed to be at depth of D = 3000 m and Ro = 0.9%, and the hydrocarbon expulsion peak occurs at depth of D = 4500 m and Ro = 1.3%.

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Fig. 5.8 Identification of the ASDL in the Songliao Basin using different indicators with increasing depth or maturity degree, including the variation of H/C ratios (a), residual hydrocarbon amounts (b), and the variation of “S1 + S2 ”/TOC (c1), Qe (c2), Ve (c3) and Ke (c4)

5.3.2 The Identification of ASDLs in Other Basins in China The same principle is used to the ASDL identification of other representative basins in China (Figs. 5.4, 5.5, 5.6, 5.7 and 5.8; Table 5.2). According to the ASDL confirmed for the six representative basins, three general conclusions can be drawn. First, the ASDL derived for the same basin by the six geochemical indexes are the same or very close in values. For the Junggar Basin, the derived ASDLs vary from 7850 to 8450 m with an average value of 8168 m and a deviation of 7.6%. Second, ASDLs in different basins can be very different, the ASDLs of the six basins range between 5280 and 9300 m with an average value of 7094 m and a deviation of > 76.1%. Third, for all the ASDLs of the six basins, the corresponding thermal maturity values of Ro have much smaller variation than the depths. Ro values vary from 3.0% in the Junggar Basin to 4.0% in the Songliao Basin, with an average of 3.5% among the six basins and a deviation of 33.3%, much smaller than the 76.1% deviation of the depths. These implies that the thermal maturity of Ro may be a better indicator to characterize the ASDL of source rocks than other indicators, then the average thermal

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Table 5.2 Comparison of active source rock depth limits among the six petroliferous basins in China Research methods and related indicators for identifying ASDLs

The maximum burial depth (D, m) and thermal maturity (Ro, %) corresponding to active source-rock depth limits Tarim Basin

Junggar Basin

The variation H/C of element composition O/C

8970/ 3.5

The variation “A”/ of residual TOC hydrocarbon “S ”/ 1 TOC

Ordos Basin

Bohai bay Basin

Songliao Basin

The average values for six basins

8350/3.2 –

–

5800/ 3.5

5280/3.6

7100/3.4

9050/ 3.6

8450/3.2 –

–

5740/ 3.4

5280/3.6

7130/3.4

9050/ 3.6

7850/3.0 7540/3.6 6450/ 3.3

5560/ 3.1

5330/3.7

6963/3.4

9290/ 3.8

7960/3.0 7780/3.8 6500/ 3.4

5490/ 3.2

5400/3.9

7070/3.5

“S1 + S2 ”/ TOC

9300/ 3.8

8200/3.0 7700/3.8 6600/ 3.4

5900/ 3.3

5400/3.9

7183/3.5

Ve

9210/ 3.8

8200/3.0 7660/3.7 6520/ 3.4

5700/ 3.3

5500/4.0

7115/3.5

The average values 9145/ obtained from different 3.7 methods in each basin

8168/3.1 7670/3.7 6518/ 3.4

5698/ 3.3

5348/3.8

7094/3.5

The data used for identifying ASDLs (sample number/well number)

5353/ 351

1193/ 69

3236/611

Total: 13,634/ 1286

The variation of hydrocarbon generation and expulsion

2063/ 79

Sichuan Basin

460/27

1329/ 149

maturity level of 3.5% derived in this study therefore is regarded as the identification criterion for the ASDL in general geological settings.

5.4 Major Factors Controlling on the ASDL 5.4.1 The ASDL Variation with Organic Matter Types Original organic matter or kerogen in source rocks is generally classified into three types based on its origin or geological characteristics (Tissot et al. 1974; Peters and Cassa 1994). The three types have different organic element compositions and different pyrolytic parameters, and therefore have different oil and gas generation potentials. The oil and gas generation potential indexes for different type organic matter in source rocks from 6 representative basins are plotted in Fig. 5.9. The

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171

Fig. 5.9 Effects of organic matter (kerogen) types on the ASDL represented by thermal maturity (Ro). From left to right are three plots of hydrocarbon generation potential index for source rocks of type I (a), type II (b), and type III (c)

dashed curves enveloping all the sample data points indicate the varying trends of oil and gas generation potential of source rocks with different organic matter types. The variation trends with increasing thermal maturity are very similar for all three organic matter types: the index first increases with increasing Ro and then decreases after source rocks reach the HET. The source rocks with type I organic matter are oil-prone, the source rocks with type II are oil and gas prone, and the source rocks with type III are gas-prone, they reach their ASDLs at the value of Ro = 3.0%, 3.5% and 4.0%, respectively. This indicates that oil-prone source rocks are more likely to reach the ASDL and stop generating and expelling hydrocarbons at a shallower burial depth than the other two types of source rocks under similar geological conditions.

5.4.2 The ASDL Variation with Heat Flows and Geothermal Gradients The depth of ASDL is shallower in petroliferous basins with high heat flow and high geothermal gradient. According to the oil and gas generation potential index, the ASDL in the six basins varies from 5400 to 9300 m (Fig. 5.10). The basins in Western China have low heat flow and low geothermal gradient (1.5–2.8 °C/100 m) and thus have the deepest ASDL, ranging from 8200 to 9300 m. The basins in Eastern China have high heat flow and high geothermal gradient (3.0–4.2 °C/100 m) and then have the shallowest ASDLs, ranging from 5400 to 5900 m. The basins in Central China are moderate and the depths of ASDLs change from 6600 to 7700 m. In addition, the source rock burial depths corresponding to HETs vary similarly: high heat flow and high geothermal gradient lead to shallower depth of HETs (Fig. 5.10).

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Fig. 5.10 Variation in depth of ASDL in six representative basins due to their different heat flows. The ASDL of 6 petroliferous basins is characterized by oil and gas generation potential index of “S1 + S2 ” = TOC. From left to right, the heat flow and geothermal gradient of each basin gradually increases, while their corresponding depth of the ASDLs becomes shallower. a Tarim Basin. b Junggar Basin. c Sichuan Basin. d Ordos Basin. e Bohai Bay Basin. f Songliao Basin

5.4.3 The ASDL Variation with Tectonic Movement and Others The ASDL is also influenced by other two important factors of the tectonic uplift and stratigraphic age of source rocks. As previous stated, the ASDL is better characterized by thermal maturity of Ro than by depth, and Ro = 3.5% is regarded as general threshold for the ASDL in general geological settings. However, the corresponding depth of ASDL for different source rocks is highly variable. Due to the irreversible nature of Ro (Hayes 1991; Peters et al. 2018), the depth of ASDL for source rocks that were historically uplifted after reaching the original ASDL is relatively shallower compared with that of younger source rocks that were not uplifted. The Sichuan Basin that experienced several stages of tectonic uplift in the geohistory and its ASDL was greatly affected by these events. For example, the Ro of the upper Triassic source rocks is about 1.0% at a depth of 2000 m in the Southern Sichuan basin (Zhu et al. 2016). At the same burial depth, however, the Ro of the lower Triassic source rocks can reach 2.0% (Zhu et al. 2016), therefore, the tectonic uplift and stratigraphic age of source rocks have a significant effect on the corresponding depth of ASDL. In addition to the mentioned four main factors above, the deep thermal fluids and overpressure retardation also affect the ASDL (McTavish 1998; Hao et al. 2007; Fetter et al. 2019). The fluid and heat source provided by deep thermal fluid can promote the maturation of organic matter. On the one hand, the conduction of thermal fluids through rocks and faults brings thermal energy to source rocks and promotes source rock maturation and hydrocarbon generation (Rullkötter et al. 1988). On the other hand, the H2 provided by the deep fluids can considerably improve the oil and gas generation rate through the kerogen hydrogenation process (Zhu et al. 2017). Consequently, compared with unaffected source rocks, source rocks influenced by deep thermal fluids may have shallower ASDLs. In terms of overpressure retardation, an overpressure on source rocks can retard the thermal evolution of hydrogen-rich

5.4 Major Factors Controlling on the ASDL

173

kerogen and/or the thermal cracking of oil and gas (McTavish 1998; Hao et al. 2007). As a result, source rocks influenced by overpressure retardation have deeper ASDLs. It is worth noting that the thermal maturity of Ro corresponding to the ASDL remains the same, no matter the ASDL becomes deeper or shallower. Namely, a source rock will reach ASDL when its Ro increases to 3.5% ± 0.5% and its oil and gas generation potential is depleted. Therefore, we argue that the thermal maturity of organic matter is more suitable to characterize the ASDL than depth.

5.4.4 Relationships Between the ASDL and the Heat Flow and Organic Matter Type According to the analysis results in the previous section, heat flow and organic matter type are two main factors controlling the ASDL. In this section, a quantitative relationship is further established by statistics analysis by using the software Origin 2019. We first use a linear model to analyze the depth of ASDL as a function of heat flow, the ASDL inputted in the model for each basin is the average depth obtained from various geochemical indicators. The heat flows used in the model are the average values of present heat flow values measured at different locations in each basin (Table 5.1). There is a strong negative correlation between the ASDL and the current heat flow, with a coefficient greater than 0.9 (Fig. 5.11a), indicating that the high heat flow very likely leads to a shallower depth of the ASDL. Considering that the heat flow values of a sedimentary basin vary with geologic time, the average heat flow since the deposition of source rocks was further employed. As shown in Fig. 5.11a, the ASDL also presents an obvious negative correlation with average paleo-heat flows, implying that the paleo and present heat flows both contribute to the thermal maturation of source rocks and therefore play an important role in variation of the ASDL. We mainly utilize the present heat flow values in the following discussion, mainly because the correlation (R = 0.90) between the ASDL and the present heat flow is much higher than that (R = 0.77) between the ASDL and the average value of paleo-heat flow. It is also observed that the maximum burial depth of oil/gas-bearing reservoirs in the most basins are mainly corresponding to the maximum temperature under the current heat flow. The ASDL for basins with different current heat flows range between 3000 and 16,000 m. Generally, the depth of ASDL is less than 6000 m in basins with high heat flow of larger than 70 mW/m2 , and are greater than 9000 m in basins with low heat flow of less than 40 mW/m2 . Given that the ASDL is also influenced by organic matter type, we further analyzed the effects of organic matter type on the ASDL by adding the hydrogen index of HI, an indicator of organic matter type, to the linear model. HI is a quantitative proxy for the characterization of kerogen types and is easily obtained through Rock-Eval analysis, a lot of studies on source rock evaluation from the scientific community have proven the reliability of HI. Furthermore, HI has been widely chosen as the indicator of kerogen type in professional software, such as PetroMod, which is often used by the industrial

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5 Active Source-Rock Depth Limit in the WPS

Fig. 5.11 Relationships among depth of ASDL, heat flow, and kerogen type for six basins of China. a Relationship between the ASDLs and heat flows. b Comparison of the modeled depths through Eq. (5.1) and the estimated depths of ASDLs. 1—Tarim Basin; 2—Junggar Basin; 3—Sichuan Basin; 4—Ordos Basin; 5—Bohai Bay Basin; 6—Songliao Basin

community. To quantify the influence of organic matter types on the ASDLs, the hydrogen index values of 600 mg HC/g TOC, 525 mg HC/g TOC, 450 mg HC/g TOC, 250 mg HC/g TOC and 125 mg HC/g TOC are assigned to type I, I–II, II, II–III and III kerogens, respectively. The following equation is then deduced: Depth of ASDL = 16,448 − 3.61 ∗ HI − 139.46 ∗ HF

(5.1)

where the ASDL is the active source rock depth limit with a unit of meter; HI is the hydrogen index value of the major source rocks in a basin, in the unit of mg HC/g TOC; HF is the present average heat flow value of a basin, in the unit of mW/m2 . Although Eq. 5.1 shows a high correlation coefficient of 0.96 (Fig. 5.11b), this equation, instead of being utilized to precisely predict the depth of ASDL in a basin, is only presented to confirm the existence of a relationship among the depth of ASDL, the heat flow, and the organic matter type because of the following reasons. First, the variation of organic matter types in our research is relatively small (Table 5.1), therefore, the hydrogen index values utilized to deduce Eq. 5.1 show small variations, bringing uncertainties to some extent. Second, the ASDL as mentioned in the above section is not only influenced by the heat flow and organic matter type, but also influenced by the stratigraphic age and tectonic uplift. Equation 5.1 have not included all the effects of 4 major factors, therefore, it is not sufficient to predict the precise depth ASDL in a basin by using Eq. 5.1. However, according to our database of 6 basins, it is difficult and impossible to establish a model with four independent variables. Construction of a complete and precise model or equation needs help from the scientific community to enrich the database. We suggest that basin modelling and other integrated analysis methods should be applied if readers want to predict the depth of ASDL in a basin without enough geological and geochemical data. Quantitative relationship indicated in Eq. 5.1 provides preliminary insights into the

5.5 Discussion and Conclusion

175

geological basis and boundary condition for the prediction of oil and gas distribution in the basins and helps the evaluation of hydrocarbon resources potential.

5.5 Discussion and Conclusion 5.5.1 The ASDL Controlling on Vertical Distribution of Oil and Gas Reservoirs and HADL Fossil fuel resources formed from organic matter in the course of millions of years are currently the primary energy resources in the world. Oil and gas are the products during the evolution of organic matter, while coal is the residue of organic matter. The ASDL is the critical condition and the dynamical boundary at which the oil and gas expulsion from the organic matter ends. It controls the formation and distribution of all oil and gas reservoirs as well as the economical coals. Once the burial depth of organic matter exceeds the ASDL, the oil and gas are no longer generated from the source rocks, and the coal evolves to graphite losing their economical value as fuel. Theoretically, the ASDL represents the maximum depth of the formation and distribution of fossil fuels, including the oil reservoirs, gas reservoirs and coal reservoirs. According to Fig. 5.12, about 97.7% of coal resources in China and 97.3% of recoverable coal reserves over the world are distributed in areas above the ASDL corresponding to depth of Ro = 4.0% (CCRR 1996; CNACG 2016; Conti et al. 2016), therefore, the ASDL represents the maximum depth of fuel reservoirs distribution, including oil, gas, and coal. This study also analyzed the drilling results for 116,489 samples of target layers from 4978 exploration wells in six representative basins in China (Fig. 5.13). The data

Fig. 5.12 The variation of proven coal reserves with coal ranks in China and over the world. a The proportion of proven coal reserves with different coal ranks in China (data from CCRR 1996; CNACG 2016), the coal ranks are classified according to the Chinese standard, and the coalaccumulation area is shown in Fig. 5.1. b The recoverable coal reserves with different coal ranks around the word (data from Conti et al. 2016), the coal ranks are classified according to international standards, and the proven coal reserves of anthracite C, B, and A are projected according to their variation trends

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5 Active Source-Rock Depth Limit in the WPS

show that all the oil and gas reservoirs in these six basins distribution the areas above the ASDLs, reflecting the controlling of ASDL on the formation and distribution of oil and gas reservoirs. With increasing burial depth, the probability of drilling commercial oil and gas reservoirs decreases, while the probability of drilling dry layers increases. At some depth, the probability of drilling oil or gas reservoirs decreases to zero, and this depth is regarded as the HADL, the depth of HADL is influenced by many factors such as the hydrocarbon composition, the geothermal field, the age and lithology of the reservoir strata, and some others. In this research, we just focus on the relationship between HADL and ASDL. The HADL of the six basins is marked in Fig. 5.13 as yellow dots and connected by a dashed red line, the depth of ASDL deduced from (“S1 + S2 ”)/TOC (Table 5.2) are also marked and connected with a solid blue line in Fig. 5.13. Meanwhile, it can also be observed that all proved oil and gas reserves in the six representative basins are controlled by the depth of HADL which is distributed above the ASDL (Figs. 5.13 and 5.14). This means that the depth HADL in a basin is controlled by the depth of ASDL, and is always be above the ASDL. The currently proved natural gas hydrate over the world are also distributed in areas with active source rocks (Dai et al. 2017). We further extended the research to 52,926 reservoirs in 1186 basins over the world (IHS 2010), the depth of HADL for each basin was derived from the depth data of actual oil and gas reservoirs by using the same way as described in the previous paragraph (Fig. 5.13) and the results are shown in Fig. 5.15. The ASDL for each basin is assumed to be at depth of Ro = 3.5%, and the corresponding depth is obtained from the documented heat flow of that basin. We found that the depth of HADL is always less than that of the ASDL for all the basins.

Fig. 5.13 Oil and gas drilling results in the six representative petroliferous basins of China showing the relationship between the ASDL and the HADL. The results include 116,489 samples of target layers from 4978 exploration wells in China, the blue dashed line represents the evolution of porosity with increasing depth, its intercept with the line of 2% porosity marks the HADL. The depth of ASDL for each basin shown in this figure is represented by the value obtained from oil and gas generation potential index of “S1 + S2 ”/TOC. From left to right: a Tarim Basin. b Junggar Basin. c Sichuan Basin. d Ordos Basin. e Bohai Bay Basin. f Songliao Basin. It is clear that the HADL is always above the ASDL

5.5 Discussion and Conclusion

177

Fig. 5.14 The vertical distribution characteristics of proved oil and gas reserves and the relationship between ASDLs and HADLs in six representative basins in China. Vertical distribution of all oil and gas reserves in six representative basins of China (a) and for different basins such as in Tarim Basin (b), Junggar Basin (c), Sichuan Basin (d), Ordos Basin (e), Bohai Bay Basin (f) and Songliao Basin (g). The HADL refer to the hydrocarbon accumulation depth limit, the average depth of ASDL for each basin shown in this figure is obtained from various kinds of indicators as presented in Table 5.2

Fig. 5.15 The vertical distribution of numbers for proved oil and gas reservoirs and the relationship between the ASDLs and HADLs in 1186 petroliferous basins over the world. a Summation of proven reservoirs in the 1186 basins; b Distribution in the basins with low heat-flow of HF < 25 mW/m2 ; c Distribution in the basins with relative low heat-flow of HF = 25–40 mW/m2 . d Distribution in the basins with relative high heat-flow of HF = 40–55 mW/m2 . e Distribution in the basins with high heat-flow of > 55–70 mW/m2 . The intercept of the green dashed line on the vertical axis marks the HADL. The ASDL shown in this figure for each kind of basin with different heat flow is predicted by using the equation shown in Fig. 5.11

5.5.2 The ASDL Controlling on Vertical Distribution of Liquid Oil and Natural Gas Hydrocarbons are generally classified in two categories as natural gas and liquid oil, which have distinct physical properties. By definition, ASDL marks the end of

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5 Active Source-Rock Depth Limit in the WPS

any hydrocarbon generation from source rocks, but this concept can be modified to incorporate the two types of hydrocarbons. Therefore, two ASDLs are introduced, including ASDLg for gas and ASDLo for oil. The ASDLo indicates that the source rocks can no longer generate oil, and is named as Active Source-rock Depth Limit for liquid oil, and the ASDLg indicates that the source rocks can no longer generate gas, and it is named as Active Source-rock Depth Limit for natural gas. Hydrocarbons generated and expelled from source rocks with low thermal maturities are mainly liquid oil and gaseous hydrocarbons. The gaseous hydrocarbons become the dominant components when the thermal maturity is high. Therefore, the burial depth and thermal maturity corresponding to ASDLo should be shallower than that of ASDLg. To investigate the ASDLo and ASDLs for different source-rocks, the pyrolysis simulation experiments with high temperature (room temperature to 600 °C) and high pressure (50 MPa) were conducted on source-rocks with original immature or low maturity kerogens sampled from Junggar Basin in a closed system. According to the experiment results, source rocks reach the ASDLo at temperature of Ro = 2.0% (Fig. 5.16) and the same source rocks reach ASDLg at temperature of Ro = 3.5% ± 0.5%. Pang et al. (2005) proposed the concept of hydrocarbon expulsion threshold (HET), which marks the starting point of source rocks expelling hydrocarbons at a certain depth, therefore, the HET, ASDLo and ASDLg divide a basin into three regions in the vertical direction, and they control the types of oil and gas reservoirs and their distributions (Fig. 5.17). The upper field of blue area in Fig. 5.17 is favourable for forming conventional oil/gas reservoirs in traps for upward migrating hydrocarbons from the source-rocks underlying the HET, and the source rocks in this field are dominantly immature and/or low mature. The middle field of pink area

Fig. 5.16 Investigation of the ASDLo and ASDLg for different source -rocks with immature or low mature kerogen d by high-temperature and high-pressure pyrolysis simulation. a The variation of oil production rate in process of pyrolysis simulation and identification of ASDLo at the value of Ro = 2%. b The variation of gas production rate with increasing thermal maturity of source-rocks and identification of ASDLg at the value of Ro = 3.5% ± 0.5%

5.6 Summary

179

Fig. 5.17 The distribution of ASDLo and ASDLg and their controlling pattern on the formation and distribution of liquid oil and natural gas reservoirs in petroliferous basins with different geothermal gradients. The upper blue area is favorable for upward migrating hydrocarbons to form oil/gas reservoirs. The middle pink area is favorable for oil and gas expelled from source rocks in this area to migrate and accumulate to form oil or oil and gas reservoirs. The lower yellow area is favorable for natural gas expelled from source rocks with high maturity to migrate and accumulate to form gas reservoirs

in Fig. 5.17 is favourable for forming various kinds of oil/gas reservoirs, and the source rocks in this field can expel hydrocarbons, which can migrate and accumulate as different reservoirs in this area or migrate upward to form conventional reservoirs in the shallower area. The lower field of yellow area in Fig. 5.17 is favourable for forming mainly unconventional gas resources. Figure 5.17 illustrates the effect of heat flow on the distribution of HETs, ASDLo and ASDLg. The characteristics of oil and gas generation and their reservoirs distribution in different areas differ among these basins due to their geological conditions and tectonic settings.

5.6 Summary The fossil fuel resources such as oil and gas as well as coal are invaluable to economic growth and social development. Understanding the formation and distribution of these fossil fuel resources is critical to the search and exploration of them in basins. Until now, the vertical distribution depth of these fossil fuel resources has not been

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5 Active Source-Rock Depth Limit in the WPS

confirmed due to different understandings of their origins and the substantial variation of reservoir depths from basin to basin. Geological and geochemical data of 13,634 source rock samples from 1286 exploration wells in six representative petroliferous basins were examined to identify the maximum burial depth of active source rocks in each basin, which is defined as the Active Source-rock Depth Limit (ASDL). Beyond the depth of ASDL, source rocks no longer generate or expel hydrocarbons and become inactive. Therefore, the ASDL also sets the maximum depth for all fossil fuel resources, sometimes called as an oil and gas death line. The ASDLs of basins over the world are found to range from 3000 m to 16,000 m, while the thermal maturities (Ro) of source rocks at the ASDLs are almost the same, with Ro ≈ 3.5 ± 0.5%. The Ro of 3.5% is regarded as a general criterion to identify ASDLs. High heat flow and more oil-prone kerogen are associated with shallow ASDLs. In addition, tectonic uplift of source rocks can significantly affect the depth of ASDLs. 21.6 billion tons of reserves in six representative basins in China and 52,926 proved oil and gas reservoirs in 1186 basins over the world are all distributed in the areas above ASDLs, showing the universal presence of ASDLs in petroliferous basins and their control on the vertical distribution of all fossil fuel resources, such as oil, gas, and coal. The core content of this chapter has been published in Earth System Science Data (Pang et al. 2020).

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Ping H, Chen H, Jia G. 2017. Petroleum accumulation in the deeply buried reservoirs in the northern Dongying Depression, Bohai Bay Basin, China: New insights from fluid inclusions, natural gas geochemistry, and 1-D basin modeling. Marine and Petroleum Geology, 80: 70-93. Rullkötter J, Leythaeuser D, Horsfield B, et al. 1988. Organic matter maturation under the influence of a deep intrusive heat source: a natural experiment for quantitation of hydrocarbon generation and expulsion from a petroleum source rock (Toarcian shale, northern Germany). Organic Geochemistry, 13(4-6): 847-856. Selley R C, Sonnenberg S A. 2014. Elements of petroleum geology. (Academic Press). Tissot B, Durand B, Espitalie J, et al. 1974. Influence of nature and diagenesis of organic matter in formation of petroleum. AAPG Bulletin, 58: 499-506. Tissot B P, Welte D H. 1978. Petroleum Formation and Occurrence, 1st ed. Springer, Berlin, 538 pp. Transocean. 2009. Deepwater Horizon Drills World’s Deepest Oil & Gas Well.: September 2. Retrieved June 22, 2018, from: https://web.archive.org/web/20100428004206; http://www.dee pwater.com/fw/main/IDeepwater-Horizon-i-Drills-Worlds-Deepest-Oil-and-Gas-Well-419C1. html?LayoutID=6. 2009. Wang C S, Chan E Z, Zhang S N. 1997. Potential oil and gas-bearing basins of the Qinghai-Tibetan Plateau, China. International Geology Review, 39: 876-890. Wang S, He L, Wang J. 2001. Thermal regime and petroleum systems in Junggar Basin, northwest China. Physics of the Earth and Planetary Interiors, 126(3-4): 237-248. Wang T G, Zhong N N, Wang C J, et al. 2016. Source beds and oil entrapment-alteration histories of fossil-oil-reservoirs in the Xiamaling formation basal sandstone, Jibei depression. Petroleum Science Bulletin, 01: 24-37. Wang Y, Yang R, Song M, et al. 2018. Characteristics, controls and geological models of hydrocarbon accumulation in the Carboniferous volcanic reservoirs of the Chunfeng Oilfield, Junggar Basin, northwestern China. Marine and Petroleum Geology, 94: 65-79. Wu S X, Jin Z J, Tang L J, et al. 2008. Characteristics of Triassic petroleum systems in the Longmenshan foreland basin, Sichuan province, China. Acta Geologica Sinica-English Edition, 82(3): 554-561. Xiao X M, Zhao B Q, Thu Z L, et al. 2005. Upper Paleozoic petroleum system, Ordos Basin, China. Marine and Petroleum Geology, 22(8): 945-963. Zhou J, Pang X Q. 2002. A method for calculating the quantity of hydrocarbon generation and expulsion. Petroleum Exploration and Development, 29(1): 24-27. Zhou Y, Littke R. 1999. Numerical simulation of the thermal maturation, oil generation and migration in the Songliao Basin, Northeastern China. Marine and Petroleum Geology, 16(8): 771-792. Zhu C, Hu S, Qiu N, et al. 2016. The thermal history of the Sichuan Basin, SW China: Evidence from the deep boreholes. Science China Earth Sciences, 59(1): 70-82. Zhu D, Liu Q, Jin Z, et al. 2017. Effects of deep fluids on hydrocarbon generation and accumulation in Chinese petroliferous basins. Acta Geologica Sinica-English Edition, 91(1): 301-319. Zhu G, Cao Y, Yan L, et al. 2018. Potential and favorable areas of petroleum exploration of ultradeep marine strata more than 8000 m deep in the Tarim Basin, Northwest China. Journal of Natural Gas Geoscience, 3(6): 321-337. Zhu Y M. 2011. Coal Mine Geology. Xuzhou, Jiangsu: China University of Mining and Technology Press.

Chapter 6

Unified Model for Oil and Gas Reservoirs Formation

New Understanding: The formation and distribution of oil and gas reservoirs have been controlled by three dynamic boundaries and three dynamic fields. The boundaries include the Buoyancy-driven Hydrocarbon Accumulation Depth (BHAD), Hydrocarbon Accumulation Depth Limit (HADL), and Active Source-rock Depth Limit (ASDL). A lot of geological factors influence the variation of these three boundaries, which jointly determine the formation and distribution of oil and gas dynamic fields in the WPS of a petroliferous basin. Different hydrocarbon reservoirs are formed and distributed in different hydrocarbon dynamic fields. In detail, Conventional oil and gas reservoirs are formed and distributed in the Free Hydrocarbon Dynamic Field (F-HDF) above the BHAD, unconventional tight oil and gas reservoirs are formed and distributed in the Confined Hydrocarbon Dynamic Field (C-HDF) between the BHAD and HADL, and the unconventional shale oil and gas reservoirs are formed and distributed in the Bound Hydrocarbon Dynamic Field (BHDF) within source rocks. Most of the proved oil and gas reserves both in China and over the world are discovered in the F-HDF, of which the original oil and gas amount provided by source rocks accounts for about 10%, indicating a limited amount of potential resources remained to be developed in future. Less than 25% of the discovered oil/gas reserves in China and over the world come from the C-HDF and the B-HDF accounting for more than 90% of original oil and gas amount provided by source rocks, implying much more oil and gas potential resources remained for exploration in future. The buried depth of three HDFs becomes shallower with increasing heat flow in basins. Besides, the changes in lithofacies and lithology could lead to the formation of different oil and gas reservoirs: the distribution of oil and gas in coarsegrained reservoir in F-HDF is favorable for the formation of conventional reservoirs, and the hydrocarbons expelled from source rocks in C-HDF are favorable for the formation of unconventional reservoirs. The tectonic movements could destroy the medium conditions and hydrocarbon components in HDFs, leading to the transformation of conventional reservoirs to unconventional ones or the unconventional to conventional ones.

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6.1 Introduction and Issue The large-scale exploration (Masters 1979) and development of unconventional oil and gas resources (Weinstein 2015) is one of the greatest advances in petroleum geology history, reshaping the global energy structure and geopolitics (Erbach 2014), which has changed the market structure of global oil and gas supply from conventional traps to continuous accumulations in deep basin centers (Masters 1979; Selley 1998; Law and Curtis 2002; Zou et al. 2013). Unconventional oil and gas resources have greatly contributed to the growth of global oil and gas reserves and production in recent 20 years, including tight oil and gas (Rose et al. 1986; Holditch 2006; Ghanizadeh et al. 2015), coal-bed methane (Rightmire et al. 1984), shale oil and gas (Claypool 1998; Curtis 2002), heavy oil and bitumen (Rubinstein et al. 1977; Richard et al. 2007). Gas hydrate has also been discovered, studied, and explored as a prospective fuel resource (Kim et al. 1987; Collett 1993; Clennell et al. 1999), which also facilitates the exploration and development of fossil fuel resources. The widespread existence of unconventional oil and gas resources led to a reevaluation of the global oil and gas resource potential (Gautier et al. 2009; Kerr 2011; USGS 2013), and also challenged existing oil and gas accumulation theories (White 1885; Levorsen 1956) and oil and gas reservoirs distribution pattern (Hu 1982; Magoon and Dow 1994) since they differ greatly from the conventional oil and gas reservoirs. Statistical analysis results show that the unconventional tight and shale oil and gas reservoirs are formed near to or within the source rocks (Spencer 1985; Law 2002; Law and Curtis 2002) and are generally controlled by reservoir layers surrounding source rocks with a range of maturity degree of Ro = 0.2–3.5%. However, the discovered conventional oil and gas accumulations are separated from their source rocks with a largest lateral distance of hundreds of kilometers (Pang 2014), and their formation and distribution are mainly controlled by oil and gas expelled from source rocks in F-HDF. Tight oil and gas reservoirs always have low porosity of 2–12% and low permeability of 0.01–1.0 mD, while the conventional oil and gas accumulations commonly occur in reservoirs with porosity of larger than 10% and permeability of larger than 1 mD. Unconventional oil and gas accumulations typically occur in negative structure units or in the depression center of a basin. The recently discovered shale oil and gas accumulations in North America mostly occur in source rocks (Masters 1979; Selley 1998; Law and Curtis 2002; Zou et al. 2013), they are not controlled by traps and have self-contained source-reservoir systems with a continuous distribution, showing obvious features of non-buoyancy-driven because many other forces reduce the effect of buoyancy, such as diagenetic trapping (Cant 1986), relative permeability jails (Masters 1979), lateral sealing of faults (Robert and Suzanne 2004), and critical pore throat (Berkenpas 1991). In addition, conventional oil and gas accumulations were typically discovered at the top and the margins of a paleo-uplift or a positive structure in the upper part of a basin. Anticline traps are commonly developed at structural highs, while lithology traps and stratigraphic traps tend to occur along the margins, so that oil and gas can migrate upward under buoyancy-driven to form conventional oil and gas reservoirs in those traps.

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The discovery of unconventional oil and gas reservoirs has triggered a series of thoughts. For example, why can large-scale unconventional oil and gas reservoirs occur in exploration forbidden areas suggested by classic petroleum geology? What differences and correlations do unconventional oil and gas reservoirs have with conventional ones in terms of formation and distribution? Will unconventional oil and gas resources eventually replace conventional oil and gas resources as the major energy source for the world economy in the future? Many studies attempted to answer these questions (Law and Curtis 2002; Law 2002; McGlade et al. 2013). Nonetheless, the genetic formation mechanisms of conventional and unconventional oil and gas resources and the relations between the two oil and gas reservoirs remain unclear, mainly because a complete theoretical model incorporating both types of oil and gas resources has not been established. This study proposes a unified genetic model based on three dynamic boundaries and three dynamic fields to address the differences and correlations between conventional and unconventional oil and gas reservoirs in their formation and distribution as well as to help evaluate their oil and gas resources in one framework.

6.2 Method and Workflow The research workflow are divided into four steps. The first step is to analyze the difference in geological characteristics and accumulation conditions of oil and gas in the six representative basins, and then to identify the conventional and unconventional oil and gas reservoirs. The second step is to analyze the differences of drilling results for oil and gas reservoirs in each basin to identify oil and gas dynamic boundaries and dynamic fields that control the formation and distribution of conventional and unconventional oil and gas reservoirs. The third step is to investigate the differences in the dynamic mechanism of the formation for conventional and unconventional oil and gas reservoirs and their relationship with the dynamic boundaries and dynamic fields, and then to establish the unified genetic model to address the difference and correlations of different oil and gas reservoirs in their formations and distributions. The fourth step is to apply the unified genetic model to solve problems challenging classical theory in oil and gas exploration. First of all, there are two assumptions of establishing the model. (1) All oil and gas available for reservoirs formation were generated by organic matter in source rocks. (2) The porosity and permeability of reservoir layers decrease with increasing depth. In addition, in some local area, tectonic movements and lithology variation would result in abnormal distribution and accumulation of oil and gas reservoirs, which will be discussed in the section of Discussion at the end of the chapter. The three hydrocarbon dynamic boundaries (HDB) and three hydrocarbon dynamic fields (HDF) are studied by both physical simulations and statistical analyses on drilling data from 12,237 exploratory wells in six representative petroliferous basins in China (Fig. 6.1). The geological conditions of the six representative petroliferous basins in China are very complicated, with different tectonic conditions and

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Fig. 6.1 Distribution of 19 major petroliferous basins in China. The representative basins used in the study are colored, the inset plots of a, b, and c show prospective resources, proved reserves, and exploration areas for 10 major petroliferous basins including the 6 representative basins

stratigraphic ages. Continental and marine strata are developed, including clastic and carbonate rocks, a large number of conventional and unconventional oil and gas reservoirs have been discovered in these basins. Therefore, the established model is applied to study reservoirs in other countries as its worldwide applicability confirmed through a systematic examination of 52,926 oil and gas reservoirs from 1186 petroliferous basins over the world (IHS Energy Group 2010). The data in China were collected from the China National Petroleum Corporation (CNPC), China Petrochemical Corporation (SINOPEC), and China National Offshore Oil Corporation (CNOOC). The global data was from the international petroleum exploration and production database at https://ihsmarkit.com/index.html.

6.3 Unified Genetic Model for Conventional and Unconventional Oil and Gas Reservoirs in the WPS 6.3.1 Concept of the Unified Model The unified genetic model is herein proposed to address the formation and distribution of different oil and gas reservoirs in the WPS of a petroliferous basin. In the model, three dynamic fields are separated by three dynamic boundaries from top to bottom, which jointly control the formation and distribution of conventional and unconventional oil and gas reservoirs in a basin (Fig. 6.2). All the related concepts are listed in Table 6.1. These three dynamic boundaries are named as the Buoyancy-driven Hydrocarbon Accumulation Depth (BHAD), the Hydrocarbon Accumulation Depth Limit (HADL), and the Active Source-rock Depth Limit (ASDL). Each boundary

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has different burial depths, generally, the depth of BHAD is less than that of HADL, and the HADL less than the ASDL. The three dynamic fields have been divided by these three boundaries and named as Free Hydrocarbon Dynamic Field (expressed in F-HDF), the Confined Hydrocarbon Dynamic Field (expressed in C-HDF), and the Bound Hydrocarbon Dynamic Field (expressed in B-HDF). Each field has the same reservoir medium conditions for oil and gas storage, the same driving force for oil and gas migration, and the same characteristics in oil and gas accumulations. The F-HDF on the top part refers to the shallow strata domain with large porosity and permeability above the BHAD, the C-HDF refers to the strata domain with low porosity and permeability between the BHAD and the HADL, and the B-HDF is divided into two subfields. The B1-HDF refers to the strata domain with ultra-tight medium below the HADL and the B2-HDF is in the strata domain within source rocks above the ASDL.

Fig. 6.2 The unified genetic model for three dynamic boundaries and three dynamic fields jointly controlling conventional and unconventional oil and gas accumulations. BHAD—buoyance-driven hydrocarbon accumulation depth; HADL—hydrocarbon accumulation depth limit; ASDL—active source-rock depth limit. C represents conventional oil and gas reservoirs formed in F-HDF (blue), including anticline trap reservoirs (C1), faulted block trap reservoirs (C2), lithology trap reservoirs (C3), stratigraphic trap reservoirs (C4) and hydrodynamic trap reservoirs (C5); U represents unconventional oil and gas reservoirs formed in C-HDF (pink) and in the B2-HDF (black), including tight trap oil and gas reservoirs (U1), tight deep-basin oil and gas reservoirs (U2), tight composite oil and gas reservoirs (U3), shale oil and gas reservoirs (U4) and coal oil and gas reservoirs (U5); R represents reformed oil and gas reservoirs formed by tectonic movement (deep yellow), including fracture-reformed oil and gas reservoirs (R1), vuggy-reformed oil and gas reservoirs (R2), fracturevuggy-reformed oil and gas reservoirs (R3), oxidation-reformed oil and gas reservoirs (R4) and pyrolysis-reformed oil and gas reservoirs (R5)

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Table 6.1 Summary table of abbreviations Abbreviation

Full name

BHAD

Buoyancy-driven hydrocarbon accumulation depth

HADL

Hydrocarbon accumulation depth limit

ASDL

Active source-rock depth limit

HDF

Hydrocarbon dynamic field

F-HDF

Free hydrocarbon dynamic field

C-HDF

Confined hydrocarbon dynamic field

B-HDF

Bound hydrocarbon dynamic field

B1-HDF

First subfield of B-HDF

B2-HDF

Second subfield of B-HDF

HGT

Hydrocarbon generation threshold

HET

Hydrocarbon expulsion threshold

HF

Heat flow

TG

Temperature gradient

F-HDZ

Free hydrocarbon dynamic zone

C-HDZ

Confined hydrocarbon dynamic zone

B-HDZ

Bound hydrocarbon dynamic zone

B2-HDZ

Second subfield of hydrocarbon dynamic zone

6.3.2 Identification and Prediction of Hydrocarbon Dynamic Boundaries (1) Identification and prediction of BHAD. The BHAD corresponds to the maximum depth for the formation and distribution of conventional oil and gas reservoirs. It is the critical conditions for the transformation driving force from buoyancy-domination to non-buoyancy-domination in the same reservoirs (Fig. 6.3). The BHAD is a dividing boundary between the conventional oil and gas reservoirs and unconventional oil and gas reservoirs in the WPS of a petroliferous basin, and also a force balance boundary in the reservoir layer that satisfies the force balance equation (Pang et al. 2012). There are two methods to identify and predict the critical conditions corresponding to the BHAD. The first method is through using the force balance equation. Critical parameters in force balance equation, such as porosity (Ø), pore throat radius (R), vitrinite reflectance (Ro ), can be calculated if sufficient geological data of the study area are obtained (Guo et al. 2017). By using this equation, the parameters relating to the BHAD of Cretaceous sandstone reservoir formation in the Songliao basin of China are calculated as porosity Ø = 10% ± 2%, pore throat radius R ≈ 1 µm, and Ro = 1.0% ± 0.1%. These parameters could also be determined by statistical analysis of oil and gas drilling results. Figure 6.3a illustrates the drilling results of the sandstone reservoir layers in the Ordos Basin, the probability of drilling

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gas-bearing reservoirs is less than 25% above the BHAD, but is more than 75% below the BHAD, which also confirms that unconventional gas reservoirs are much more widespread than conventional ones. The depth of the BHAD increases from 1500 to 3000 m with increasing particle sizes of reservoir layers, the Fig. 6.3b, c show two depth cross-sections of the Songliao Basin and the Junggar Basin, respectively. Above the BHAD, oil and gas migrate to positive structural traps by buoyancydriven to form conventional oil and gas reservoirs, however, below the BHAD, oil and gas accumulate continuously in reservoir layers connecting to sources rocks of deep depression areas. The same method is applied to six petroliferous basins in China, results show that the critical porosity of Ø = 10% ± 2%, pore throat radius of R ≈ 1.0 µm, and permeability of K ≈ 1 mD with the BHAD in the sandstone reservoirs are the same as the numerical simulation results, however, the depth corresponding to BHAD varies in a wide range, from 2100 m in the Songliao Basin in the east of China to 5000 m in the Tarim Basin in the west of China. (2) Identification and prediction of HADL. The HADL corresponds to the maximum depth of unconventional oil and gas reservoirs formed in a reservoir layer outside source rocks. Above the HADL, oil and gas are expelled from source rocks to form oil and gas reservoirs in the reservoir layers; while below the HADL, oil and gas are unlikely to form oil and gas reservoirs due to either few hydrocarbons can be expelled from source rocks, or no free pore space in reservoir layers available with increasing burial depth during the basin evolution. With increasing the burial depth

Fig. 6.3 Distribution of drilling results for oil and gas reservoirs in basins and the identification and prediction of buoyancy-driven hydrocarbon accumulation depth (BHAD). a The depth of BHAD identified by drilling results from Upper Paleozoic sandstone reservoir in the Ordos Basin are deeper with increasing grain size of sandstone reservoir layers; b The BHAD of Cretaceous sandstone reservoirs in the EW cross section of the Songliao Basin was identified by the distribution characteristics of conventional and unconventional oil and gas reservoirs; c The BHAD of Late Paleozoic and Mesozoic sandstone reservoirs in the EW cross section of Junggar Basin was identified by the distribution characteristics of conventional and unconventional oil and gas reservoirs

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of a reservoir layer, the effective porosity and permeability decrease to 0, and the bound water saturation in the reservoir layer increases to near 100%. There are three methods to determine the critical conditions or depth corresponding to the HADL. The first method is through statistical analysis of oil and gas drilling data at many different burial depth intervals from exploration wells. The reservoir layer at greater depth has lower porosity due to increasing compaction when the exploration wells is drilled into the same reservoir layer, the dry layer ratio in a certain depth interval will increases with increasing depth, the critical conditions corresponding to the HADL reached when the dry layer ratio reaches 100% as showed in Fig. 6.4a. This method is mainly used in mature exploration areas with many exploration wells, and the results would be reliable. The second method is to use statistical analysis and geological analogy to determine the HADL when no exploratory wells drilled or available. For this method, the variation of oil and gas drilling results in the reservoir formation as a function of porosity been first analyzed to determine the critical porosity corresponding to the dry layer ratio of 100% as showed in Fig. 6.4b. The method can remedy the deficiency of insufficient exploration well data, however, the results are of relatively low reliability. The third method is according to the relation of porosity with burial depth obtained from simulation. This method is applied to determine the maximum burial depth corresponding to the critical porosity with dry layer ratio of 100% (Fig. 6.4c). The method can be used in any area, and the reliability of results depends on the data number and representativeness of the exploration data used in the model. The joint application of the three methods in practical work can make up for each other’s shortcomings. These methods are used to study the HADLs of sandstone reservoirs in the six basins in China. It is found that the HADLs correspond to the sandstone reservoir layer with critical porosity of Ø = 2.0% ± 1.0%, pore throat diameter of R = 0.02 µm, and permeability of K = 0.01 mD, while the depths for the HADLs of sandstones at different basins vary from 5050 to 7990 m. This does not exclude the possibility to discover oil and gas reservoirs in the carbonate rocks below HADL because of their different oil and gas dynamic boundaries and dynamic fields. (3) Identification and prediction of ASDL. The ASDL or active source-rock depth limit, corresponds to the maximum depth at which the active source rock can no longer generate or expel hydrocarbons and becomes inactive. Other than burial depth, ASDL could expressed in thermal maturity and other parameters of the source rock. The oil and gas generation potential index of source rocks, which measures the potential amount of oil and gas generated by organic matters in the source rocks, is evaluated based on many parameters and applied to identify the existence of ASDL (Fig. 6.5). These parameters include the atomic ratio of hydrogen to carbon of H/C as showed in Fig. 6.5a, the oil and gas generation potential index of “S1 + S2 ”/TOC as showed in Fig. 6.5b, the residual oil and gas content index of “S1 ”/TOC as showed in Fig. 6.5c by Rock-Eval pyrolysis analysis, the residual oil and gas content index of “A”/TOC as showed in Fig. 6.5d by Chloroform extraction experiment, the oil and gas expulsion rate of Ve and so on. These parameters have been applied to study the ASDL for the major source rocks in the six representative basins. Our results show that their

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Fig. 6.4 Distribution of drilling results for oil and gas reservoirs in basins and the identification and prediction of hydrocarbon accumulation depth limit. a The HADL was determined by statistical analysis of drilling results for oil and gas reservoirs from Dongpu Depression of Bohai Bay Basin, eastern China, which corresponding to the depth with dry layer ratio tending to reach 100% with increasing burial depth. b The HADL is predicted by the dry layer ratio of 100% based on variation trend of dry layer percentage with decreasing porosity. c The correlation of critical parameters for HADL, such as depth, porosity, and the dry layer ratio

ASDL depths vary from 5280 and 9300 m with the corresponding thermal gradients ranging from 4.2 °C/100 m to 1.5 °C/100 m, but the corresponding thermal evolution degrees are almost the same with Ro ≈ 3.5% ± 0.5% for the six basins. Research results from different petroliferous basins show that the ASDL depth varies with the age of source rocks, the type of organic matters in source rocks, and the thermal gradient of the basins (Pang et al. 2020).

6.3.3 Division and Identification of Three Hydrocarbon Dynamic Fields The petroliferous basin was divided from the top to the bottom into three hydrocarbon dynamic fields, such as the F-HDF, C-HDF, and B-HDF, by three dynamic boundaries of BHAD, HADL, and ASDL. Different HDFs control the formation and distribution of different oil and gas reservoirs, therefore, the type of dynamic boundary, the porosity and permeability of reservoir layers, the types and distribution characteristics of proved oil and gas reservoirs have been used to identify and predict the HDFs as stated in Fig. 6.2.

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Fig. 6.5 Variation of different geochemical parameters from the major source rocks with increasing thermal maturity (Ro, %) in the six basins in China and the identification and prediction of ASDL. a Using the hydrogen and carbon atom ratio of H/C to determine the ASDL as maturity of Ro = 3.75%; b Using the oil and gas generation potential index from pyrolysis parameters of “S1 + S2”/TOC to determine the ASDL as maturity of Ro = 3.85%; c Using the oil and gas remaining amount index from pyrolysis parameter of “S1”/TOC to determine the ASDL as maturity of Ro = 3.9%%; d Using the hydrocarbon remaining amount index from chloroform extraction of “A”/TOC to determine the ASDL as maturity of Ro = 3.95%. By the method, the determined ASDLs in the six basins in China vary with different types of organic parent materials, the ASDL corresponds to maturity of Ro = 3.5% ± 0.5%

(1) Identification of F-HDF. The free hydrocarbon dynamic field of F-HDF was identified by the following geological characteristics. (1) The formation and distribution of conventional oil and gas reservoirs are controlled by 4 major factors, including the source rocks of S, the carrier bed of D, the cap rock strata of C and the trap of T. (2) There are at least five composite styles of these factors in reservoirs formation, including anticline oil and gas reservoirs, fault block oil and gas reservoirs, lithology oil and gas reservoirs, stratigraphic oil and gas reservoirs, and hydrodynamic oil and gas reservoirs. (3) All oil and gas reservoirs formed in F-HDF are characterized with 4 highs, such as oil and gas accumulated at high points of uplifts, stored in high porosity and permeability reservoirs, sealed by high position caprocks, formed in traps with high pressure. (4) The oil and gas reservoirs are separated from source rocks. (2) Identification of C-HDF. The confined hydrocarbon dynamic field of C-HDF was identified by the following geological characteristics. (1) The formation and distribution of unconventional oil and gas reservoirs are controlled by 4 major factors, such as the source rocks of S, widespread tight strata of L, low potential reservoir layer of D, stable and gently tectonic setting of W. (2) There are at least three composite styles of these factors in the formation of unconventional oil and gas reservoirs, including tight conventional oil and gas reservoirs (Pang et al. 2013), tight deep-basin oil and

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gas reservoirs (Zou et al. 2013), and tight continuous-composite oil and gas reservoirs (Pang et al. 2014). (3) The tight unconventional oil and gas reservoirs formed in C-HDF are usually characterized with 4 lows, such as reservoirs distributed in low depression, oil and gas accumulated in low position under water, stored in reservoirs with low porosity and permeability, and stable with in pressure. (4) Unconventional oil and gas reservoirs coexist with their source rocks. Some oil and gas reservoirs are formed near or closely connected to source rocks, and some are formed within source rocks (Rose et al. 1986; Curtis 2002; Holditch 2006; Zou et al. 2013; Ghanizadeh et al. 2015). (3) Identification of B-HDF. The bound hydrocarbon dynamic field of B-HDF was identified by the following three geological characteristics. (1) The major factors controlling the formation and distribution of shale oil and gas reservoirs in source rock are organic matter abundance of TOC, Kerogen type index of KTI, organic matter evolution maturity of Ro , source rock thickness of H, hydrocarbon remaining amount of Qr , pressure of fluids in source rock of P, and mineral component of N. (2) Two kinds of unconventional oil and gas reservoirs are formed within source rocks, including shale oil and gas reservoirs and coal seam oil and gas reservoirs. (3) Unconventional oil and gas reservoirs formed in B-HDF are usually characterized with extensive tightness of strata, continuous distribution of oil and gas, and coexistence of oil and gas reservoirs and source rocks in the same layer.

6.3.4 The Characteristics of Oil and Gas Accumulations in the Unified Genetic Model The characteristics of oil and gas accumulations in different HDFs are different and controlled by different driving forces, such as buoyancy (White 1885), hydrodynamics (Hubbert 1953), capillary force difference (Barker 1980), hydrocarbon diffusion (Stainforth and Reinders 1990), fluid pressure (Law et al. 1994), hydrocarbon inflation (Liu 1999), hydrocarbon/water molecular bonding force (Price 1976) and so on (Pang et al. 2012). Although there are many kinds of driving forces which make contributions to oil and gas migration and accumulation, only one or a few of driving forces play a leading role in one Hydrocarbon Dynamic Field. Conventional oil and gas reservoirs are formed in the F-HDF, expressed in blue colored area of the Fig. 6.2. In this field, the reservoir layers have a shallow burial depth and weak compaction, the capillary resistance force to hydrocarbon migration and accumulation is smaller than the buoyancy force, and the formation and distribution of oil and gas reservoirs are mainly dominated by buoyancy. Overpressure condition that commonly occur during hydrocarbon generation are also a significant factor to hydrocarbon migration, but they cannot change the basic characteristics of buoyancy-dominated migration and accumulation of conventional oil and gas reservoirs. This is mainly due to the following two aspects. Firstly, the overpressure in the source rocks can only affect the time and amount of oil and gas expulsion from

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source rocks. Secondly, the overpressure during secondary migration process will only accelerate oil and gas to enter the trap along the pressure relief channels. After entering the trap, the accumulations of oil and gas are still dominated by buoyancy. The combination of buoyancy and different geological conditions in F-HDF control the formation and distribution of different kinds of conventional oil and gas reservoirs (Liu 2019), such as anticlinal oil and gas reservoirs (C1 in the Fig. 6.2), fault blocked oil and gas reservoirs (C2 in the Fig. 6.2), lithologic oil and gas reservoirs (C3 in the Fig. 6.2), stratigraphic oil and gas reservoirs (C4 in the Fig. 6.2), hydrodynamic plugging oil and gas reservoirs (C5 in the Fig. 6.2), and so on (Pang et al. 2000). Unconventional tight oil and gas reservoirs are formed in the C-HDF (pink colored in the Fig. 6.2). As the buried depth of the reservoir layers is larger than the area in F-HDF and the compaction is stronger, the capillary pressure of oil and gas in the carrier bed is larger than the buoyancy, and the migration and accumulation of oil and gas are dominated by capillary pressure and other non-buoyancy driving forces. The combination of the non-buoyancy driving forces and different geological conditions in C-HDF control the formation and distribution of different kinds of unconventional oil and gas reservoirs (Pang et al. 2014), such as tight conventional oil and gas reservoirs (U1 in the Fig. 6.2), tight deep-basin oil and gas reservoirs (U2 in the Fig. 6.2), and tight composite oil and gas reservoirs (U3 in the Fig. 6.2). The tight composite oil and gas reservoir is a new type of superimposed and continuous unconventional tight oil and gas reservoir, which has been predicted based on the dynamic field controlling of oil and gas and confirmed by drilling results (Pang et al. 2014, 2019). Unconventional shales oil and gas reservoirs are mainly formed in the B2-HDF (black colored in the Fig. 6.2). In the B2-HDF, the reservoir has low porosity and ultra-lower permeability, so the oil and gas are generally unable to migrate from the outside into the source rock. Shale oil and gas reservoirs are formed by oil and gas remaining in source rocks and are controlled by the capillary force and fluid viscosity. The combination of remaining hydrocarbons and different geological conditions in B2-HDF control the formation and distribution of different shales oil and gas (Pang et al. 2014), such as shale oil and gas reservoirs (U4 in the Fig. 6.2), coal oil and gas reservoirs (U5 in the Fig. 6.2), and the like (Liu 2019). Tectonic movements can lead to the transformation of HDFs and the reformation of pre-existing oil and gas reservoirs. For example, in the C-HDF, the tight oil and gas reservoirs can be transformed into fracture reformed oil and gas reservoirs (R1 in the Fig. 6.2) by stress, tight oil and gas reservoirs into vuggy oil and gas reservoirs (R2 in the Fig. 6.2) by underground fluid dissolution, and tight reservoirs into fracture and vuggy reformed composite oil and gas reservoirs (R3 in the Fig. 6.2) by both of them. While in the F-HDF, the conventional oil and gas reservoirs can be transformed to heavy oil or asphalt (R4 in the Fig. 6.2) by oxidation and microbial degradation, the tight oil and gas reservoirs transformed to tight dry gas reservoirs (R5 in the Fig. 6.2) by increasing their temperature and cracking hydrocarbons, and so on (Pang 2014). The matching of different driving forces and different geological conditions determines the types and characteristics of oil and gas reservoirs. The oil and gas reservoirs formed dominantly by non-buoyancy forces are currently all called as unconventional

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oil and gas reservoirs, and the unconventional oil and gas reservoirs, compared to the conventional ones, feature more complex formation conditions and wider distribution areas.

6.4 Formation and Evolution Mechanism of the Unified Model 6.4.1 Formation Mechanism of the Unified Genetic Model in a Petroliferous Basin The compaction of sedimentary strata in petroliferous basins is the fundamental cause for the conversion of driving force of oil and gas migration and accumulation, the formation of hydrocarbon dynamic fields and the potential difference of oil and gas resources among these fields. With increasing the buried depth, the average porosity, permeability, and pore throat radius of reservoir layers generally decrease (Fig. 6.6a). The oil and gas migration resistance will also increase in the reservoir with smaller pore throat radius, porosity and permeability, and the characteristic differences for forming reservoirs gradually appear. Three essential geological factors taken into account in the establishment of the unified genetic model are the reduction of pore throat radius in the reservoir layers with increasing depth, the change of driving force for oil and gas migration and accumulation, and the change of hydrocarbon supplying potential from source rocks (Fig. 6.6b). The formations of three boundaries, the distribution of three HDFs and the resource potentials of different oil and gas reservoirs are determined by the matching relationship of these three essential factors in time and space. The conceptual model, as shown in Fig. 6.6b1, indicate that the average permeability of oil/gas- bearing reservoirs decreases with increasing burial depth, which determines the differences of oil and gas accumulation characteristics in shallow, middle, and deep strata in the basin. In the shallow burial condition of the F-HDF, the sandstone reservoir layers have large porosity of Ø > 10% ± 2%, larger pore throat radius of R > 1.0 µm, and large permeability of K > 1.0 mD. With further increase of burial depth beyond the certain point, the porosity, pore throat radius and permeability of sandstone reservoir layers decrease continuously to be in the range of 2% ± 1% < Ø < 10% ± 2%, 0.02 < R < 1.0 µm and 0.01 < K < 1 mD, respectively, and the oil and gas accumulations in this situation are distributed in the area of C-HDF. When the buried depth of sandstone reservoir layers continues to increase to Ø < 2% ± 1%, R < 0.02 µm and K < 0.01 mD, the hydrocarbon migration and accumulation is located in the area of B1-HDF, and the irreducible water saturation reaches 100%, indicating the ending of oil and gas accumulation in the sandstone reservoir layers. The conceptual model, expressed in Fig. 6.6b2, illustrates that the average pore throat radius of oil–gas bearing reservoir layer decreases with the increase of burial

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Fig. 6.6 Formation mechanism of hydrocarbon dynamic boundaries and hydrocarbon dynamic fields during evolution of petroliferous basins. a Porosity variation of sandstone reservoirs in six representative basins in China with increasing burial depth. b Three essential factors controlling the formation of three hydrocarbon dynamic boundaries and three HDFs in petroliferous basins: b1 Conceptual model for permeability variation of reservoir layers with increasing burial depth and division of the F-HDF, C-HDF and B-HDF by the BHAD, HADL and ASDL; b2 The variation of driving forces for oil and gas migration and accumulation in the reservoir layers with increasing depth, division of the F-HDF, C-HDF and B1-HDF by the BHAD, HADL and ASDL, Pe-hydrocarbon pressure, Pw-water column pressure, Pc-reservoir capillary pressure; b3 The variation features of the retained and expelled hydrocarbon amounts of source rocks with increasing burial depth, division of three types of original hydrocarbon amounts available for the formation of conventional oil and gas reservoirs (red), unconventional tight oil and gas reservoirs (yellow), and shale oil and gas reservoirs (green). BHAD—buoyance-driven hydrocarbon accumulation depth, HADL—hydrocarbon accumulation depth limit, ASDL—active source-rock depth limit

depth, which determines the difference of oil–gas accumulation dynamics in the shallow, middle, and deep layers of a basin. When the reservoir is shallowly buried and with high porosity and permeability, the capillary force and other resistance in the reservoir layer is smaller than the buoyancy force on the hydrocarbon migration, which forms the conventional oil/gas reservoirs. When the reservoir layer deeply buried and with lower porosity and permeability, the capillary force and other resistance are larger than the buoyancy force on the hydrocarbon migration, which forms the unconventional oil and gas reservoirs. The critical conditions for the transition from buoyancy-dominated to non-buoyancy-dominated correspond to the BHAD, which are characterized by the force balance equation (Eq. 6.1) among the capillary force (Pc), hydrostatic column pressure (Pw) and the oil–gas migration force (Pe): Pe = Pw + Pc

(6.1)

Conventional oil and gas reservoirs are formed in the F-HDF with buoyancy dominating oil and gas migration (Pe > Pc + Pw) above the BHAD. Unconventional tight oil and gas reservoirs are formed in the C-HDF with non-buoyancy forces dominating oil and gas migration (Pe < Pc + Pw) below the BHAD. The variation characteristics of Pe, Pc and Pw, their correlation and impacts on oil and gas accumulation have been discussed in an earlier paper (Guo et al. 2017). Figure 6.6b3 illustrates a conceptual model in which oil and gas generation and expulsion amounts from source rocks change with the increase of burial depth, which

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determines the difference of oil and gas resource potentials in the shallow, middle, and deep layers of the basin. The resource potentials formed in different HDFs are related to the original oil and gas amounts provided by source rocks in these three fields. The original hydrocarbon amount (green colored in the Fig. 6.6b3) remained in source rocks within the B2-HDF is available for the formation of unconventional shale oil and gas resources. The original hydrocarbon amount (red colored in the Fig. 6.6b3) expelled from source rocks in the F-HDF is available for the formation of conventional oil and gas resources. The original oil and gas amount (yellow colored in the Fig. 6.6b3) expelled from source rocks in the C-HDF is available for the formation of unconventional tight oil and gas resources. It is noted that the oil and gas resource amounts ultimately formed in different HDFs are also related to other conditions for reservoirs formation, including the oil and gas migration, accumulation, preservation, and reformation.

6.4.2 The Evolution of the Unified Genetic Model in a Petroliferous Basin The hydrocarbon dynamic boundaries and dynamic fields in a petroliferous basin change with different geological conditions. The hydrocarbon dynamic boundary and field distributions in the same reservoir layer are divided into three stages during their evolution (Fig. 6.7). The first stage is the earliest stage of the unified model in the basin evolution. At this stage, the reservoir layers are mainly formed in the F-HDF with oil and gas generated and expelled from source rocks (Fig. 6.7a1). Most of the oil and gas generated from the source rocks under or above the reservoir layer are retained in the source rocks. Under the dominance of buoyancy, the expelled hydrocarbons migrate long distance from their source rocks and accumulate in different traps to form different conventional oil and gas reservoirs such as the reservoirs of N1 and N2. The second stage is the middle stage of the unified model in basin evolution. In this stage, the burial depth of reservoir layer becomes deeper, corresponding to lower porosity and permeability, and the oil and gas expulsion efficiency from the source rocks reach their maximum (Fig. 6.7a2). During this evolution stage, most of the hydrocarbons generated from source rocks are expelled and a small amount retains in source rocks, the expelled hydrocarbons tend to form unconventional tight oil and gas reservoirs such as N4 under the domination of non-buoyancy driving forces. At the same time, the conventional oil and gas reservoirs of N1 formed earlier were buried deeper and transformed to tight oil and gas reservoirs of N3. The third stage is the late stage of the unified model in basin evolution. At this stage, the reservoir layer is at much greater depth with very low porosity and permeability. The amount of newly generated oil and gas from the source rocks is small, and the oil and gas retained earlier begin to be expelled (Fig. 6.7a3). In the case that abundant

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Fig. 6.7 The division of hydrocarbon dynamic fields and their transformation in the evolution of a basin. a Concept model for the evolution of HDFs and their controlling on oil and gas accumulation features in the same reservoir layer at different stages. a1 In the early stage, the reservoir layer is mainly in F-HDF forming conventional oil and gas reservoirs expressed in N1 and N2; a2 In the second stage, the reservoir layer is mainly transformed into the C-HDF forming tight conventional oil and gas reservoirs of N3 and tight deep basin oil and gas reservoirs of N4; a3 In the third stage, the depth of reservoir layer continues to increase but is still in C-HDF, forming some tight oil and gas reservoirs of N5, N6, and N7 and a new kind of superimposed continuous tight oil/gas reservoir of N8, and part of the reservoir layer is transformed to B1-HDF, which is not favorable for oil and gas to accumulate. b The evolution of HDFs and oil/gas accumulation features of the X2 Member sandstone reservoir layer in the West Sichuan Depression of Sichuan Basin, China. b1 Distribution of HDFs and oil and gas accumulation before 178 Ma. b2 Distribution of HDFs and oil and gas accumulation before 157 Ma. b3 Current division of HDFs and distribution of proved oil and gas reservoirs at present time (0 Ma). The time points of 178 Ma, 157 Ma and 0 Ma are the three major periods of the hydrocarbon generation, expulsion, and accumulation

oil and gas are provided by the source rocks, the new oil and gas reservoirs of N5, N6 and N7 are formed in this stage, the tight conventional oil and gas reservoirs of N3 and the tight deep-basin oil and gas reservoirs of N4 formed in the middle stage are combined or superimposed on each other to form widely distributed and superimposed continuous oil and gas reservoirs of N8. The fourth stage is the ending stage of the unified model in the evolution of a basin. At this stage, the reservoir layer becomes ultra-tight and most of them enter the B1HDF, becoming unfavorable for oil and gas accumulations. The internal capillary resistance of reservoir layer in B1-HDF is too strong, so the external oil and gas cannot migrate into them to form a new reservoir. The earlier accumulated oil/gas in

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the reservoir layers have been expelled due to compaction in this stage or become immovable “dead oil/gas” as the reservoir becomes too tight and impermeable (Bai 2017). As shown in Fig. 6.7b, the evolution of hydrocarbon dynamic filed affects oil and gas accumulation in the sandstone reservoir layer of the X2 Member in the West Sichuan Depression of Sichuan Basin, China. Before 178 Ma, the X2 Member in the study area was mainly in the F-HDF as shown by light blue area in the Fig. 6.7b1, and the trap structures are favorable for the formation of conventional oil and gas reservoirs. By the time of 157 Ma, most of the X2 Member had been transformed to the C-HDF as shown by light pink areas in the Fig. 6.7b2, and these areas were favorable for the formation of unconventional tight oil and gas reservoirs, implying that the earlier favorable trap structures charged with oil/gas by buoyance force can be recharged with oil and gas again by different non-buoyance-driven. Under current geological conditions, more than half of the study area has been converted into B1HDF as shown by light gray area in Fig. 6.7b3, which was not conducive to oil and gas accumulation. The proved oil and gas reservoirs are mainly distributed in the current C-HDF, especially in these areas as shown by green area in Fig. 6.7b3 with superimposition and combination of buoyancy-dominated hydrocarbon accumulations in F-HDF in the early stage (Yang and Pang 2012).

6.5 Application of the Unified Model for Oil and Gas Exploration The unified model can be applied to guide oil and gas exploration in following steps. The first step is to identify the hydrocarbon dynamic boundaries and HDFs of the target reservoir layers in a petroliferous basin. The second step is to analyze the correlation between oil and gas generation and expulsion characteristics of source rocks in HDFs, evaluate the oil and gas resource potentials in the different HDFs, then predict oil and gas resource types and the most favorable field for oil and gas accumulations. The third step is to investigate the oil and gas accumulation mechanisms and the occurrence styles of different oil and gas reservoirs in the same HDF controlled by different factors, then to predict their favorable area for exploration and select the most reliable drilling targets.

6.5.1 Evaluating Oil and Gas Resources by the Unified Model The unified model can be used to evaluate oil and gas resource potentials in different HDFs together with other geological data such as the characteristics of oil and gas generation and expulsion of source rocks. Total oil and gas resource potential is controlled by the oil and gas amount generated by source rocks in the basin, while

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different kinds of oil and gas resource potentials of conventional and unconventional oil and gas are determined by the oil and gas amounts generated and expelled by source rocks in different HDFs. The organic matters in different HDFs have different organic element compositions due to different thermal maturity, and the source rocks are of different lithological properties and surrounding conditions. All these factors contribute to the variable capabilities of the source rocks in generating, retaining and expulsing hydrocarbons, therefore, there are different oil and gas resource potentials for different hydrocarbon dynamic fields. Figure 6.8 shows the hydrocarbon generation and expulsion characteristics of the Paleogene and Neogene source rocks in different HDFs of the Zhanhua Depression in the Bohai Bay Basin of China, and the calculation results of the original hydrocarbon amounts available for the formation of three types of oil and gas resources are different. The oil and gas generation potential index of GPI varies with increasing the burial depth of source rocks (Fig. 6.8a), the oil and gas generation threshold (HGT), hydrocarbon expulsion threshold (HET), the expelled hydrocarbons amount (Qe ) and the depth of ASDL are determined by characteristics of their variation. Figure 6.8b illustrates the relationship between the distribution of main source rock strata in the depression and the discovered oil and gas reservoirs distribution in the major reservoir layers. Combined with the drilling results, the BHAD and HADL can be identified, and three HDFs of the F-HDF, C-HDF and B-HDF can be divided vertically. Figure 6.8c shows the vertical distribution of the original oil and gas amounts available for the formation of conventional oil and gas resources, unconventional tight oil and gas resources and unconventional shale oil and gas resources, which are provided by main source rocks in the Bohai Bay Basin of China. They are calculated by combining the distribution characteristics of source rocks and geological parameters, such as their thickness (H), organic matter content (TOC), Kerogen type index (KTI), organic matter maturity degree (Ro ), residual oil and gas amount (Qr ) in source rocks, and so on. Among original oil and gas amounts generated by source rocks, the ratios (Ki ) of oil and gas amounts for conventional resources, tight resources and shale resources to the total are 11.6%, 53.8%, and 34.7%, respectively. Similar studies have been conducted on the other five representative basins (Fig. 6.9). The oil and gas amounts expelled from major source rocks and available for forming conventional oil and gas resources in the F-HDFs are in an average of 10.3% of the total oil and gas amounts generated by the major source rocks, ranging from 8.7 to 11.8% (Fig. 6.9a). The expelled amounts of oil and gas available for forming tight oil and gas resources in C-HDFs are in an average of 45.3% of the total amount, ranging from 35.0 to 54.3% (Fig. 6.9b). The other 44.4% (ranging from 34.7 to 54.1%) are remained in the source rocks within the B2-HDFs and available for forming shale oil and gas resources (Fig. 6.9c). The original oil and gas amount for forming unconventional oil and gas resources is about 9 times of that for conventional oil and gas resources, implying the great potential for further exploration of unconventional oil and gas resources in the C-HDF and B2-HDF. The current total amount of recoverable hydrocarbon resources in China is about 104.04 billion tons of oil equivalent, the conventional oil and gas resources account to 43.23 billion tons or 41.6% of the total, tight oil and gas resources account for 36.93 billion tons

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Fig. 6.8 Hydrocarbon generation and expulsion in different HDFs and the evaluation of three types of oil and gas resources. a Variation of hydrocarbon generation potential index of (S1 + S2 )/ TOC for major source rocks with increasing depth and its correlation with hydrocarbon generation threshold of HGT, hydrocarbon expulsion threshold of HET, and expelled hydrocarbon amount of Qe and the depth of ASDL. b Distribution of proved oil and gas reservoirs in geological profile and the identification of BHAD. c Distribution of original hydrocarbon amounts generated from major source rocks in different HDFs with increasing depth and their relationship with three types of oil and gas resources. Pink—original hydrocarbon amount available for the formation of shale oil and gas resources; Red—original hydrocarbon amount available for the formation of conventional oil and gas resources; Yellow—original hydrocarbon amount available for the formation of tight oil and gas resources

or 35.5%, shale oil and gas resources account for 23.88 billion tons or 22.9%. The realistic recoverable unconventional resources (tight + shale) account for 58.4%, indicating that the major oil and gas resources for the current exploration are unconventional oil and gas resources. Besides, this ratio will continue to increase due to the following three reasons. Firstly, with the continuous improvement of exploration technology, the recovery rate for unconventional oil and gas will continue to increase. Current recovery rates for tight oil and gas and for shale oil and gas are only 3.0–18% and 4.0–7.0%, respectively, and these rates are expected to reach 30 and 15% by 2050 (EIA 2012; BP 2017). Secondly, more oil and gas in the F-HDF were destroyed than those in the C-HDF and B-HDF in the basin evolution process due to the relatively shallow burial depth of the oil and gas reservoirs and larger permeability of the reservoir layers in the F-HDF (Pang et al. 2018). The actual migration and accumulation efficiency coefficient of unconventional oil and gas in C-HDF is higher than that of conventional oil and gas in F-HDF. Thirdly, 77.8% of proved oil and gas reserves are conventional oil and gas resources in F-HDF of the six basins in China, and globally, 83.6% of discovered oil and gas reservoirs have been also distributed in F-HDF, implying that the proved ratios of conventional oil/ gas resources are much higher than those of unconventional ones. This suggests that there are much more unconventional oil and gas resources in C-HDFs and B-HDFs are yet to be discovered, while the undiscovered conventional oil and gas resources are much less. We estimate the potential amount of undiscovered unconventional oil and gas resources is more than 9 times of the undiscovered conventional oil and gas

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Fig. 6.9 Comparison among the ratios of original hydrocarbon amounts in different HDFs provided by major source rocks in the six representative basins. a Relative original hydrocarbon amounts expelled by major source rocks and available for forming conventional oil and gas resources in the FHDFs, accounting for from 8.7 to 11.8% with an average of 10.3%. b Relative original hydrocarbon amounts expelled by major source rocks and available for forming tight oil and gas resources in CHDFs, accounting for from 35.0 to 54.3% with an average of 45.3%. c Relative original hydrocarbon amounts retained in major source rocks and available for forming shale oil and gas resources within B2-HDFs, accounting for from 34.7 to 54.1% with an average of 44.4%. Statistical analysis results of 20 main petroliferous basins showed that the ratio of original hydrocarbons for forming the conventional, unconventional tight and shale oil and gas reservoirs accounts for about 10%, 40% and 50%, respectively

resources in the world. Clearly, unconventional oil and gas reservoirs in C-HDFs and B-HDFs are the future direction of petroleum exploration.

6.5.2 Predicting the Distribution of Potential Resources by the Unified Model In the 6 representative basins of China, about 168.6 × 108 tons reserves of oil (red) and 92.8 × 108 tons reserves of oil equivalent gas (yellow) have been discovered (Fig. 6.10a1). These reserves decrease with increasing burial depth. Estimation results showed that more than 50% of the remaining oil and gas resources are mainly distributed in petroliferous basins with their burial depth of more than 4500 m according to the distribution of hydrocarbon amount generated by major source rocks. All the 52,926 oil/gas reservoirs proved in 1186 basins over the world (Fig. 6.10a2) have the same distribution characteristics with increasing burial depths, and the same conclusion can be reached that more than 65% of the remaining oil and gas resource exist in basins with burial depth of more than 4500 m. The proved oil and gas reserves in China are about 33.95 billion tons, of which 82.7% are the conventional oil and gas resources distributed in the F-HDF, 12.3% are tight oil and gas resources distributed in the C-HDF, and the remaining 5.0% are shale oil and

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Fig. 6.10 Distribution of proved oil and gas reservoirs and reserves in different depths and their relative amounts in three different HDFs from petroliferous basins in China and over the world. a Distribution of proved 26.14 billion tons of oil equivalent reserve in different depths of 6 representative basins in China (a1) and proved 52,926 oil and gas reservoirs in different depths of 1186 basins over the World (a2); b Distribution of the relative amount for proved oil and gas reserves in different HDFs in China (b1) and the relative amounts of proved oil and gas reservoirs in different HDFs in the world (b2)

gas resources distributed in the B2-HDF (Fig. 6.10b1). About 544.02 billion tons of oil and gas reserves have been discovered in the petroliferous basins over the world (IHS 2010), of which 91.6% are distributed in the F-HDF, 3.1% in the C-HDF and 5.4% in the B2-HDF (Fig. 6.10b2). More than 90% of the discovered oil and gas reserves in the world come from the F-HDF, but the original oil and gas amount is only about 10% of the total hydrocarbons generated by source rocks, implying much fewer potential resources remained to be develop in future. While, less than 10% of the discovered oil and gas reserves in the world come from the C-HDF and the B2-HDF, but their original oil and gas amount is more than 90% of the total generated hydrocarbon amount, implying much more potential resources remained in deeper strata to be explored in future.

6.5.3 Quantifying Favorable Scope of Oil and Gas Reservoirs by the Unified Model The unified model is available to quantify the scope favorable for the formation and distribution of different oil and gas reservoirs in three HDFs, thus can help us to select the most reliable drilling target and identify the type of oil and gas reservoirs. The model was applied to the Kuqa Depression of the Tarim Basin of China to predict

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the formation and distribution of sandstone oil and gas reservoirs in the Cretaceous and Jurassic. The average depths of the BHAD, HADL and ASDL are confirmed to be 3500, 7990, and 9145 m. Then, three HDFs of the F-HDF, C-HDF, and B-HDF are divided for these sandstone reservoir layers in their evolutions (Jiang et al. 2015). The favorable scope for the formation of conventional oil and gas reservoirs and for tight conventional oil and gas reservoirs during three different geological times of 12, 5, and 0 Ma have been predicted. These oil and gas reservoirs are mainly located at the high positions of the positive structures in the study area. The favorable scopes for the formation of unconventional tight deep-basin oil and gas reservoirs and tight composite continuous oil and gas reservoirs at 12, 5, and 0 Ma are also predicted. These reservoirs are mainly located in the low depressions in the study area. The evaluation results of natural gas resources for these 4 types of oil and gas reservoirs in the Cretaceous sandstone reservoir layers of Kalasu structural belt of the Kuqa Depression is totally up to 10 trillion m3 , the ratio of conventional oil and gas resources, tight conventional oil and gas resources, tight deep-basin oil and gas resources, and tight composite continuous oil and gas resources account for 20.7%, 34.8%, 44.5%, and 26.4%, respectively. The total in-place resource amount of the four types of oil and gas reservoirs is consistent with the latest drilling results (Jiang et al. 2015) in the study area, and is five times higher than the previous evaluation results. Figure 6.11a illustrates the predicted oil and gas resource types and reservoirs distribution in sandstones reservoir layers of Jurassic in the Kuqa Depression of the Tarim Basin, China. The scopes favorable for different resources accumulation are expressed in different colors, of which red for conventional oil and gas reservoirs, yellow for tight deep-basin oil and gas reservoirs, and pink for tight composite oil and gas reservoirs. Due to the fact that the reservoir layers of Jurassic in this area are mainly distributed in the C-HDF, the formation and distribution of conventional oil and gas reservoirs in these layers are very limited. According to the prediction results, five scientific exploration wells been deployed for unconventional tight oil and gas reservoirs. In 2011, the Tarim Oilfield Company drilled the DX 1 Well, the DX1 Well is a great success, obtaining 590,000 m3 of gas and 68 m3 of oil per day in the sandstone reservoir layers of Jurassic sandstone. After that, a number of exploration wells were successfully drilled and the Dibei oil and gas field was discovered (Fig. 6.11b). The discovery of the Dibei oil and gas field is significant in three aspects. Firstly, the existence of predicted new type of tight oil and gas reservoirs has been confirmed, it is the superposition and combination of the conventional oil and gas reservoirs formed by buoyance-driven in the F-HDF at an earlier stage and the unconventional tight oil and gas reservoirs formed by non-buoyance-driven in the C-HDF at the late stage in the same reservoir layers. Secondly, the high position of the Dixi structure and the surrounding slope area are favorable for oil and gas accumulation, the Yinan 2 Well drilled in the Dixi area in 1998 obtained 100,000 m3 of gas, but the Yinan 4 Well and Yishen 4 Well drilled in 1999 at the structural peak north to the Yinan 2 Well failed due to destruction of the accumulated oil and gas reservoirs by structural movements. On the other side, the oil and gas in the low

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Fig. 6.11 Prediction of favorable scopes for the formation and distribution of four types of oil and gas reservoirs in the Jurassic Formation in the eastern Kuqa Depression and the optimization of drilling targets. a Prediction of favorable scopes for formation and distribution of three types of oil and gas reservoirs based on the HDF division and evolution, including tight deep-basin oil/gas resource (yellow), conventional oil/gas resource (red), and tight composite oil/gas resource (pink). Tight gas reservoirs of the Ahe Formation are widely distributed in this area, and the formation and distribution of conventional oil and gas reservoirs in this layer are very limited. Five scientific exploration wells were deployed according to the predicted result. b The DX1 Well (exploration well 1) was drilled based on the HDFs evolution results and obtained a high yield. The Dibei oil and gas field was discovered, confirming the existence of tight composite oil and gas reservoirs (Pang et al. 2019)

part of the Dixi structure was well preserved (Pang et al. 2019). Thirdly, the Eastern Kuqa Depression is favorable for the formation and distribution of tight oil and gas reservoirs, including tight conventional oil and gas reservoirs, tight deep-basin oil and gas reservoirs and tight composite oil and gas reservoirs, with an effective area for exploration of more than 30,000 km2 . Based on the same method, the oil and gas resource types and reservoirs distribution in the four reservoir layers of the Paleozoic Cambrian, Ordovician, Silurian and Devonian of the Tarim Basin as well as the Longwangmiao Formation of Sichuan Basin are predicted. The coincidence coefficient between predicted results and drilling results was more than 86%, reflecting the effectiveness and reliability of the unified model (Wang et al. 2020).

6.6 Discussion and Conclusion The unified model provides a new approach for understanding and interpreting the distribution characteristics of oil and gas reservoirs in the whole basin. Nevertheless, it is noted that the proposed unified model could not be applied to cover all kinds of situations locally existing in a petroliferous basin, so specific problems need to be analyzed in combination with actual geological conditions. Theoretically, all the geological conditions or factors that affect the three HDBs will affect the division and distribution of the three HDFs, which have been discussed in the previous section of this Chapter. In actual geological conditions, however, the most comprehensive

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and obvious geological factors influencing the three HDFs are heat flow difference of basins, variation of stratigraphic lithology and tectonic movement evolution.

6.6.1 The Increase of Heat Flow Leading to Shallower Depth of the HDFs As shown in the Fig. 6.12, the distribution of three HDFs varies with the heat flow (HF) and temperature gradient (TG) in petroliferous basins over the world. The depths of three HDBs, including the BHAD, HADL, and ASDL, are mainly affected by the HF and TG in a basin. In hot basins with HF > 60 mW/m2 , strong compaction and cementation result in a rapid decrease in pore size with increasing burial depth and result in shallower depths of the three HDFs. Oil and gas resources are buried in a shallow area, distributed in narrow regions with a maximum depth of less than 4500 m. In cold basins with HF < 40 mW/m2 , weak compaction and cementation result in a slow decrease in pore size with increasing burial depth, leading to larger depths of the three HDFs. Oil and gas resources are deeply buried and widely distributed, and the maximum burial depth reaches larger than 9000 m. In warm basins with HF = 40–60 mW/m2 , the compaction and cementation of strata is moderate, the burial depth of oil and gas resources are between 4500 and 9000 m.

6.6.2 Variation of Lithology Leading to Driving Forces Combination Diversity On the scale of whole petroliferous basin, the formation and distribution of oil and gas reservoirs are controlled by HDBs and HDFs, which can be characterized by the unified model. However, on the scale of HDFs or smaller zones, the formation and distribution of oil and gas reservoirs could be controlled by conditions such as local lithologic variation (Jia 2019). Figure 6.13 illustrates the local lithologic variation of Qingshankou Formation in the south-north section of the Qijiagulong Depression in Songliao Basin, China, which lead to the change of driving forces for oil and gas migration. The combination characteristics of different hydrocarbon dynamic zones (HDZ) and their controlling effects on different type of oil and gas reservoirs in the F-HDF are illustrated. The coarse-grained sandstones with high porosity and permeability constitutes the Free Hydrocarbon Dynamic Zone (F-HDZ) and are distributed in the shallow buried zone in the north of the depression, which is favorable for the formation and distribution of conventional oil and gas reservoirs (yellow area in the Fig. 6.13). The silty sandstones with low porosity and permeability constitute the Confined Hydrocarbon Dynamic Zone (C-HDZ) and distributed in the middle of the depression with moderate burial depth, which is favorable for the formation and distribution of unconventional tight oil and gas reservoirs (light yellow area in

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Fig. 6.12 The unified distribution model of three HDFs in petroliferous basins with increasing heat flow and temperature gradient. The three HDBs of sandstone reservoir layers in basins over the world have similar critical conditions for pore throat radius (r) and thermal maturity degree (Ro), the maximum depths of three HDFs increase with decreasing temperature gradient. Blue—F-HDF favorable for forming conventional oil and gas reservoirs; Yellow—C-HDF favorable for forming tight oil and gas reservoirs; Grey—B2-HDF favorable for forming shale oil and gas reservoirs

the Fig. 6.13). The mudstones with ultra-low permeability and rich organic matter constitute the Bound Hydrocarbon Dynamic Zone (B-HDZ) and are distributed in the deep buried area in the south of the depression, which is favorable for the formation and distribution of shale oil and gas reservoirs (blue area in the Fig. 6.13). The three HDZs of the F-HDZ, C-HDZ, and B-HDZ constitute a complete combination in the transverse direction as in the Fig. 6.13, which indicates that unconventional tight oil and gas reservoirs could also be formed in the local region in the F-HDF. Dynamic anomalies due to local changes in lithology are very common in the F-HDF. As shown in Fig. 6.12, the C-HDZ are represented by yellow dot coils around the source rocks, distributed locally and limited in the F-HDF. There are situations in which buoyancy cannot play a dominant role in the F-HDF of the basin, such as the variation of relative permeability in the reservoir layers (Masters 1979), the variation of diagenesis in the strata (Cant 1986), the capillary force inhibition in the oil and gas migrations (Berkenpas 1991), and the lateral fault blockage of oil and gas accumulations in the carrier layers (Robert and Suzanne 2004). The abnormal situations will also occur in the C-HDF, the conventional oil and gas reservoirs with high-porosity and permeability could be formed in a local

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Fig. 6.13 Combination characteristics of different HDZs in the F-HDF due to lateral lithology variation in the north–south section of Qingshankou Formation of Qijiagulong Depression in the Songliao Basin, China. The coarse-grained sandstones with high porosity and permeability constitutes the free hydrocarbon dynamic zone (F-HDZ) and is distributed in the shallow buried zone in the north of the depression, and favorable for the formation and distribution of conventional oil and gas reservoirs (yellow colored). The silty sandstones with low porosity and permeability constitute the confined hydrocarbon dynamic zone (C-HDZ), is distributed in the middle of the depression with moderate burial depth, and favorable for the formation and distribution of unconventional tight oil and gas reservoirs (light yellow colored). The mudstones with ultra-low permeability and rich organic matter constitute the bound hydrocarbon dynamic zone (B2-HDZ), is distributed in the deeply buried area in the south of the depression, and favorable for the formation and distribution of shale oil and gas reservoirs (blue area), modified after Jia (2019)

area of a stratigraphic reservoir body in the C-HDF dominated by non-buoyancydriven, forming “sweet point” enriched with oil and gas in the tight unconventional extensive continuous oil and gas reservoirs. The origin of reservoir rock with high porosity and permeability in the “oil and gas sweet point” has been extensively researched, the mechanisms include the deep burial of reservoir rock with high porosity and permeability (Higgs et al. 2007), under compaction of reservoir rock (Ole 2008), reconstruction of reservoir rock by fractures (Zhang et al. 2014), reconstruction of reservoir rock by dissolution (Van 2008), and recrystallization of carbonate reservoir rock (Billaultet al. 2003), etc. In the limited area of HDF, the concept of “abnormally dynamic zone” is used for the change of driven force for three reasons. (1) It should not confuse with the concept of hydrocarbon dynamic field (HDF) in the macroscale of petroliferous basin. (2) The variation of driving force for oil and gas accumulation in the local limit area of the HDF cannot change the macroscopic distribution characteristics of the oil and gas reservoirs. (3) The influence of local dynamic anomalies caused by lithology variation on the formation and distribution of oil and gas reservoirs in petroliferous basins has been included in the study on lithologic oil and gas reservoirs and stratigraphic oil and gas reservoirs.

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The distribution of driving force for hydrocarbon migration and accumulation in actual geological conditions is more complicated than illustrated in the Fig. 6.13. Based on the research of relevant situations of 6 representative basins in China, two categories and six types of oil and gas dynamic zone combinations are summarized for the changes in geological conditions in the local zones of HDFs (Fig. 6.14). The first category is the close combination of B2-HDZ and F-HDZ due to a sudden change in stratigraphic lithology which is conducive to the formation of conventional oil and gas reservoirs and shale oil and gas reservoirs. Hydrocarbons generated by source rocks form the shale oil and gas reservoirs within B2-HDZ by remaining some oil/ gas, and hydrocarbons expelled from source rocks form the conventional oil and gas reservoirs by buoyance-driven within F-HDZ. They can be subdivided into 3 types according to the relative position of the dynamic zones in vertical, including the combination of C-HDZ/F-HDZ/B-HDZ (a1 in Fig. 6.14a), the F-HDZ/B-HDZ/CHDZ (a2 in the Fig. 6.14a), and the B-HDZ/F-HDZ/C-HDZ (a3 in the Fig. 6.14a). A few oil and gas could accumulate to form unconventional tight oil and gas reservoirs in a2, but it is impossible to form tight oil and gas reservoirs in a1 and in a3 because of the capillary pressures of the reservoir layers in C-HDZ larger than that in F-HDZ. The second category is the close combination of B-HDZ and C-HDZ due to rhythmic changes in sedimentary strata, which is conducive to the formation of unconventional tight oil and gas reservoirs and shale oil and gas reservoirs. Hydrocarbons generated from source rocks form the shale oil and gas reservoirs within B2-HDZ by remaining some of oil and gas and the unconventional tight oil and gas reservoirs within C-HDZ are charged by oil and gas expelled from source rocks. They can also be subdivided into 3 types, including the combination of the F-HDZ/C-HDZ/B-HDZ (b1 in the Fig. 6.14b), the C-HDZ/B-HDZ/F-HDZ (b2 in the Fig. 6.14b), and the B-HDZ/CHDZ/F-HDZ (b3 in the Fig. 6.14b). A few oil and gas could accumulate to form conventional oil and gas reservoirs in b2 due to the tightly connection of source rock with the tight reservoir layer within F-HDZ, generally, it is impossible to form conventional oil and gas reservoirs in b1 and b3 because of the separation of source rock and F-HDZ by C-HDZ. The combinations of different dynamic zones play important roles in controlling the formation of different oil and gas reservoirs. The combinations need to be analyzed by integrating with specific geological conditions, and among these conditions, the influence of hydrocarbon supply from source rocks is particularly critical.

6.6.3 Tectonic Movement Leading to Reformation of the HDFs and Reservoirs Type Reformation of the HDFs by tectonic movements refers to the change of reservoir medium, the surrounding conditions, and hydrocarbon components, which destroy the combination of original HDFs and change the type of the oil and gas reservoirs. The shallow buried basins only develop F-HDF and mainly form conventional oil and gas reservoirs. In the basins that were once deeply buried but overlying strata

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Fig. 6.14 Combination characteristics of different HDZs in the F-HDF due to vertical lithologic variation in local region and its controlling effects on oil and gas accumulations above the BHAD. The combination of three HDZs are divided into two categories and six types. a The first category of HDZs combination favorable for the formation of conventional oil and gas reservoirs, including the C-HDZ/F-HDZ/B-HDZ (a1), the F-HDZ/B-HDZ/C-HDZ (a2), and the combination of B-HDZ/ F-HDZ/C-HDZ (a3). b The second category of HDZs combination favorable for the formation of unconventional oil and gas reservoirs, including the F-HDZ/C-HDZ/B-HDZ (b1), the C-HDZ/ B-HDZ/F-HDZ (b2) and the B-HDZ/C-HDZ/F-HDZ (b3)

currently denuded due to the uplift, only have C-HDF or B-HDF remained, and are only conducive to unconventional oil and gas exploration. In basins that were reformed by strong tectonic movements, the type of oil and gas reservoirs formed earlier has been transformed. The reformed oil and gas reservoirs can be divided into two types: one is the reformation of rock medium in reservoirs and the other is the reformation of hydrocarbon component. The medium reformation occurs in the following two scenarios. First, the tectonic stress is the major force to reform the medium, and results in a large number of folds, faults, and fractures in the original tight formation. The earlier formed oil and gas reservoirs are transformed into fracture reformed oil and gas reservoirs (Fig. 6.15a) and the oil and gas are accumulated at the high point of fault traps driven by buoyance (Pang et al. 2010). Secondly, the activity of underground fluid is the major force to reform the medium, which is manifested as the existence of unconformity and a large number of dissolution holes in the original tight formation (Fig. 6.15b). The oil and gas reservoirs formed earlier are transformed into vuggy reservoirs with oil and gas accumulated in high porosity and permeability along the unconformity (Zhao et al. 2015). Usually, both the tectonic stress and underground fluid activity are the major forces to reform the medium, so that the reservoirs formed earlier are transformed into fracture and cave reformed reservoirs with oil and gas accumulated in high-porosity and high-permeability (Han et al. 2006). The oil and gas component reformation also happens in two situations. First, deep burial in the study area leads to the increase of temperature and pressure, resulting in the cracking of hydrocarbons in the early formed oil and gas reservoirs and the formation of dry gas reservoirs (Fig. 6.15c) with low density, low viscosity

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Fig. 6.15 The changes of oil and gas reservoirs types and hydrocarbon resource phases after transformation of HDFs caused by external forces. a The C-HDF is modified and transformed to F-HDF by tectonic stress, then the continuous unconventional tight oil and gas reservoirs formed earlier in F-HDF are transformed into multiple discontinuous conventional oil and gas reservoirs separated by faulted blocks. b The C-HDF is modified by underground fluid activities and transformed to F-HDF with developed pores and vuggy. The low abundance unconventional tight oil and gas reservoirs formed early are transformed to multiple discontinuous high abundance conventional vuggy oil and gas reservoirs. c The conventional oil and gas reservoirs formed in F-HDF are transformed into discontinuous unconventional cracking gas reservoirs due to the increase in burial depth and strata temperature. d The conventional oil and gas reservoirs formed in F-HDF are transformed into unconventional heavy oil or bitumen reservoirs due to the denudation of overlying strata and the occurrence of biodegradation and oxidation

and high adamantane content (Hao et al. 2008). Second, an uplift of the basin or the study area resulted in the decrease of temperature and pressure and the increase of oxidation and biodegradation. The reservoirs formed earlier are transformed to heavy oil or bitumen reservoirs (Fig. 6.15d) with high density, high viscosity, and high holtane content (Cao et al. 2005).

6.6.4 Application Range of the Unified Model Commonly, the proposed unified model is applicable both to liquid oils and natural gas but with different dynamic boundaries and dynamic fields. Since with smaller size of gas molecules than oil, and different interfacial tension and wetting angle of gas from oil, the three dynamic boundaries of gas are different from those of oil. Generally, the BHAD of gas are similar to that of oil. The statistical analysis and numerical simulation results both indicated that the corresponding critical porosities of BHADs of oil and gas are 11–12% and 10–11%, respectively (Pang et al. 2012). The HADL of gas is much deeper than that of oil because the molecule size of gas is smaller than oil and thus can accumulate in smaller fractures and pores. In addition, gas accumulation can occur under higher temperature conditions, while

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liquid oil tends to cracking to gas and cannot enter extreme small fractures and pores to accumulate. The corresponding critical conditions of ASDL for gas exhibit obvious different features compared with that of oil. The liquid oil and natural gas correspond to the maturity degree of Ro ≈ 2.0% and Ro ≈ 3.5%, respectively. Although oil can be present at higher temperature under high pressure conditions, those situations are relatively rare (Pang et al. 2020). Theoretically, the established unified model can be used both in sandstone and carbonate oil and gas reservoirs. Practically, conventional oil and gas reservoirs were discovered in carbonate reservoir layers with much lower porosity and the same permeability (Ma et al. 2007; Ma 2020) and unconventional oil and gas reservoirs were discovered in carbonate reservoirs with much lower porosity and permeability (Wei et al. 2019). However, the preliminary study showed that the identification criteria for conventional and unconventional oil and gas reservoirs in sandstone reservoirs cannot be directly applied to carbonate reservoirs, because the critical permeability of 1 mD corresponds to the critical porosity about 12% for the BHAD of sandstone reservoir layers, while for that in carbonate reservoir layers it corresponds to the critical porosity of 7% and critical permeability of 1 mD (Wei et al. 2017). The genesis characteristics of carbonate oil and gas reservoirs are different from those of sandstone oil and gas reservoirs. Compared with sandstone oil and gas reservoirs, carbonate oil and gas reservoirs have stronger heterogeneity with poor correlation between porosity and permeability (Ahr et al. 2005; Al-Marzouqi et al. 2010). Carbonate oil and gas reservoirs are characterized by low porosity and high permeability, implying the carbonate reservoir layers may have better quality for oil and gas accumulation than sandstone reservoirs if both with similar porosity (Bloch et al. 2002). Generally, the porosities of carbonate and sandstone reservoirs both decrease with increasing burial depth, however, the regularity of physical properties of carbonate reservoirs is worse than that of sandstone reservoirs due to the different diagenetic mechanisms of the two (Houseknecht 1987; Lundegard 1992; Lander and walderhaug 1999; Paxton et al. 2002). Under some local conditions, the average porosity of carbonate reservoir changes complicatedly with burial depth, and even increases with increasing depth. Compared with sandstone reservoirs, carbonate reservoirs have more developed secondary pores and generally lower oil and gas recovery factors. Therefore, the BHADs and HADLs in carbonate reservoirs would require further studies rather than directly applying those of sandstone reservoirs.

6.7 Summary The discovery and large-scale exploration of unconventional oil and gas resources since the 1980s is considered to be the most significant progress in the history of petroleum geology. It has not only changed the balance of supply and demand in the global energy market, but also improved our understanding of the formation mechanisms and distribution characteristics of oil and gas reservoirs. However, the difference and correlations between conventional and unconventional oil and gas

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resources in petroliferous basins remain unclear, which are complex challenging issues and very critical for oil and gas resources assessment and exploration. This chapter focused on studying the relationship of the formations and distributions among different oil and gas reservoirs. The drilling results of 12,237 exploratory wells in 6 representative petroliferous basins of China and the distribution characteristics of 52,926 oil and gas accumulations over the world were applied to clarify the formation conditions and genetic relations of different oil and gas reservoirs in a petroliferous basin, and then to establish a unified model to address the differences and correlations between the conventional and unconventional reservoirs. In this model, conventional oil and gas reservoirs formed in F-HDF with high porosity and permeability located above the BHAD, the unconventional tight oil and gas reservoirs formed in C-HDF with low porosity and permeability located between the BHAD and the HADL, shale oil and gas reservoirs formed in the B-HDF within the source rock with low porosity and ultra-low permeability above the ASDL. More than 75% of the world’s proved reserves are discovered in the F-HDF, which is estimated to contain only 10% of the original generated hydrocarbons; most of the undiscovered oil and gas resources are distributed in the C-HDF and the B2-HDF, which contains 90% of the original generated hydrocarbons, suggesting a reasonable and greater promising future for hydrocarbon explorations. The buried depths of HDFs become shallower with increasing heat flow, and the potential oil and gas resources mainly exist in the deep area of “cold basin” with lower geothermal gradient. Lithology variation in the HDFs causes local anomalies in the oil and gas dynamic mechanism, resulting in the local formation of unconventional oil and gas reservoirs in the FHDF or the appearance of “sweet spots” with high oil and gas enrichment in the CHDF. The tectonic movements can destroy the medium conditions and hydrocarbon components, resulting in the transformation of conventional oil and gas reservoirs formed in F-HDF to unconventional oil and gas reservoirs or the transformation of unconventional oil and gas reservoirs formed in C-HDF to conventional oil and gas reservoirs. The core content of this chapter has been published in Geoscience Frontiers and Petroleum Science (Pang et al. 2021, 2023).

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Pang X Q, Zhou X Y, Dong Y X, et al. 2013. Formation mechanism classification of tight sandstone hydrocarbon reservoirs in petroliferous basin and resources appraisal. Journal of China University of Petroleum (Edition of Natural Science), 37(5): 28-37. Paxton S T, Szabo J O, Ajdukiewicz J M, et al. 2002. Construction of an intergranular volume compaction curve for evaluating and predicting compaction and porosity loss in rigid-grain sandstone reservoirs. AAPG Bulletin, 86(12): 2047-2067. Price L C. 1976. Aqueous solubility of petroleum as applied to its origin and primary migration. AAPG Bulletin, 60(2), 213-244. Richard F M, Emil D A, Philip A F. 2007. Heavy oil and natural bitumen resources in geological basins of the world. US Geological Survey. Rightmire C T, Eddy G E, Kirr J N. 1984. Coalbed methane resources of the United States: AAPG Studies in Geology series 17. Tulsa, Oklahoma: the American Association of Petroleum Geologists, 1–14. Robert M C, Suzanne G C. 2004. The origin of Jonah field, Northern Green River basin, Wyoming. John W R., Keith W S. Jonah field: case study of a tight-gas fluvial reservoir: AAPG Studies in Geology, 52. Rose P R, Everett J R, Merin I S. 1986. Potential basin-centered gas accumulation in cretaceous trinidad sandstone, Raton basin, Colorado. Oil and Gas Journal, 82: 190-197. Rubinstein I, Strausz O P, Spyckerelle C, et al. 1977. The origin of the oil sand bitumens of Alberta: a chemical and a microbiological simulation study. Geochimica et Cosmochimica Acta, 41(9): 1341-1353. Selley R C. 1998. Elements of Petroleum Geology, 2nd edition. Waltham: Academic Press: 470. Spencer C W. 1985. Geologic aspects of tight gas reservoirs in the Rocky Mountain region. Journal of Petroleum Geology, 37(7): 1308-1314. Stainforth J G, Reinders J E A. 1990. Primary migration of hydrocarbons by diffusion through organic matter networks, and its effect on oil and gas generation. Organic Geochemistry, 16(1-3): 61-74. USGS. 2013. World petroleum assessment. http://pubs.usgs.gov/dds/dds-0. Van K P C. 2008. Smectite-illite-muscovite transformations, quartz dissolution, and silica release in shales. Clays and Clay Minerals, 56: 66-81. Wang W Y, Pang X, Chen Z, Chen D, et al. 2020. Improved methods for determining effective sandstone reservoirs and evaluating hydrocarbon enrichment in petroliferous basins. Applied Energy, 261: 114457. Wei X S, Chen J P, Lv Q Q, et al. 2019. Quality difference between dolomite and sandstone tight reservoir. Oil & Gas Geology, 40(2), 294-301 (in Chinese with English abstract). Wei X S, Chen J P, Zhang D F, et al. 2017. Geological characteristics and reservoir forming conditions of large area tight carbonate gas in eastern Ordos Basin, China. Natural Gas Geoscience, 28(05): 677-686 (in Chinese with English abstract). Weinstein A L. 2015. Unconventional Oil and Gas Development’s Impact on State and Local Economies. Choices, 29(4): 554-554. White I C. 1885. The geology of natural gas. Science, 125: 521-522. Yang K M, Pang X Q. 2012. Formation mechanism and prediction method of tight sandstone gas reservoirs. Beijing: Science Press. Zhang H L, Zhang R H, Yang H J. 2014.Characterization and evaluation of ultra-deep fracture-pore tight sand stone reservoirs: A case study of Cretaceous Bashijiqike Formation in Kelasu tectonic zone in Kuqa foreland basin, Tarim, NW China. Petroleum Exploration and Development, 41(2):158-167. Zhao J Z, Yao G S, Yang G, et al. 2015. Genesis mechanism of the Sinian-Cambrian reservoirs in the Anyue Gas Field, Sichuan Basin. Natural Gas Industry B, 2(2-3): 127-135. Zou C N, Yang Z, Tao S Z, et al. 2013. Continuous hydrocarbon accumulation over a large area as a distinguishing characteristic of unconventional petroleum: The Ordos Basin, North-Central China. Earth-Science Reviews, 126: 358-369.

Chapter 7

Evaluation of Conventional Oil and Gas Reservoirs

New Understanding: The available hydrocarbon amount for accumulation and effective resources in a petroleum system are controlled by hydrocarbon thresholds in migration and accumulation, Hydrocarbon migration-accumulation threshold controlling reservoirs model is established according to accumulation-disperse balance principle, the available hydrocarbons accumulation and effective resource potential can be quantitatively evaluated by applying the model. The hydrocarbon reservoirs distribution in a petroleum system is primarily controlled by hydrocarbon thresholds of four functional elements with characteristics of independent and indispensable. The spatial–temporal combination model (T-CDPS) of these four functional element thresholds controlling reservoir formation and distribution is established according to their relationship. Four different types of conventional reservoirs in a petroleum system can be predicted and evaluated quantitatively by applying the model. The hydrocarbon enrichment degree of target strata or traps in a petroleum system is controlled by near source (SI), optimal reservoir facies (FI), and lower potential (PI). A comprehensive source–facies–potential thresholds controlling hydrocarbon enrichment model is established, and a comprehensive index (FPSI) is proposed to predict and evaluate hydrocarbon enrichment probability, hydrocarbon saturation and production capacity of the target strata or traps quantitatively by applying the model.

7.1 Introduction and Issue Petroleum is indispensable for modern industry and petroleum exploration has attracted the attention of scientists and governments in different countries throughout the world. As a subdiscipline of geology, petroleum geology is a comprehensive applied science that aims to explain the generation, migration, accumulation, and distribution of petroleum in the petroliferous basins and finally guides petroleum exploration. © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_7

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With large-scale discoveries and development of hydrocarbon reservoirs, the geological conditions for hydrocarbon exploration become increasingly complicated. Some classic petroleum geology theories and hydrocarbon reservoirs formation models meet significant challenges. Two cases in China petroleum exploration history demonstrate the necessity and urgency to address this problem. Case 1 refers to the world largest continental oil field, the Daqing Oilfield, which was discovered in the central uplifted zone of the Songliao Basin in eastern China. However, the hydrocarbon generation condition of the source rock in the vast area north of the central uplifted zone was quite good, and the favorable resource prospect area determined according to the effective source rock condition with total organic carbon (TOC) of greater than 0.5% is over 32,300 km2 with good reservoir-cap combination. Approximately 210 wells were drilled after three rounds of intensive hydrocarbon exploration in the area. There has been no significant discovery in the vast area beyond the neighborhood of the railway line (Wang et al. 2008). Case 2 refers to the Eocene petroleum system of the Qaidam Basin in western China. The main source rock has relatively low TOC. According to the empirical discrimination standard of effective source rock with TOC greater than 0.5%, it was predicted that the favorable resource prospect area was less than 500 km2 . However, the areas of hydrocarbon reservoirs discovered so far have exceeded 10,000 km2 (Pang et al. 2003). The two contrasting cases indicate that the existing petroleum reservoirs distribution models and theories need to be further improved and developed. The development history of petroleum geology and exploration subject has shown that they are being continuously improved and developed as new information and knowledge are enhanced. Before 1990’s, when the anticlinal reservoirs concept was proposed for petroleum exploration, the buoyancy as a dynamic mechanism for hydrocarbon migration and accumulation was considered (White 1885). This was followed by subsequent improved trap controlling reservoir concepts (McCollough 1934; Levorsen 1936, 1956, 1967), which identified the key areas for hydrocarbon exploration being uplift structures. The model guided hydrocarbon exploration to achieve higher success rate compared with hydrocarbon discoveries based on the hydrocarbon seepage tracing method. The source-controlled hydrocarbon accumulation theory (Tissot and Welte 1978; Hunt 1979) further focused on the key areas of hydrocarbon exploration within traps near the source kitchens. This again further improved the success rate of hydrocarbon exploration significantly. The concept of petroleum system (Dow 1974; Magoon 1988, 1992; Magoon and Dow 1994; Perrodon 1992) unified the trap controlling hydrocarbon accumulation and sourcecontrolled hydrocarbon generation, and laid the foundation for modern hydrocarbon accumulation theory, and provided a platform for the process analysis of favorable hydrocarbon accumulation and semi-quantitative evaluation of favorable accumulation zones. However, it cannot offer quantitative answers on whether hydrocarbon reservoirs could be formed within a system, or the hydrocarbon accumulation range, magnitudes of hydrocarbon resource potential and the hydrocarbon accumulation degree (saturation) in a trap (Fig. 7.1). The petroleum system analysis concept failed to meet challenges of in-depth hydrocarbon exploration. The proposed hydrocarbon thresholds controlling reservoirs research here attempts to enhance the petroleum

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Fig. 7.1 Classical hydrocarbon accumulation theory model applied in a petroliferous basin

system concept by quantifying various processes and elements and to meet the new challenges, and provide new insights and workflow for in-depth hydrocarbon exploration.

7.2 Concept of Hydrocarbon Threshold and Its Significance 7.2.1 Basic Concept of Hydrocarbon Threshold The occurrence of a geological event is a process of an accumulation of sequential changes that eventually led to a sudden transformation. This is also true for the hydrocarbon accumulation and reservoirs distribution process. Hydrocarbon threshold refers to the critical geological condition enabling the hydrocarbon reservoirs formation. Figure 7.2 illustrates a case study of methane gas hydrate formation in permafrost that is jointly controlled by dual critical conditions of temperature and pressure. It can be seen from the figure that, suitable temperature–pressure range is good for the formation of methane gas hydrate reservoirs, which is defined by the solid line (Fig. 7.2). The red area defined is generally called the favorable area for methane gas hydrate formation, boundaried comprehensively by temperature– pressure thresholds. In fact, hydrocarbon thresholds are present in all the steps of hydrocarbon generation, expulsion, migration, accumulation and a reservoirs formation. For example, Tissot and Welte (1978) found that the critical geological condition for mass hydrocarbon generation in source rocks was when vitrinite reflectance (Ro)

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Fig. 7.2 Methane hydrate stability zones for permafrost

reaches 0.5%. Figure 7.3 shows an objective critical geological condition controlling mass hydrocarbon expulsion from source rocks (Fig. 7.3a), critical geological and dynamics condition controlling mass hydrocarbon accumulation (Fig. 7.3b). Jin et al. (2003) found that the critical geological condition for small, medium, large, and super large gas reservoirs formation was that the gas generating strength is higher than 2 × 109 m3 /km2 in the source rocks. All these phenomena indicate that quantitative prediction and evaluation of hydrocarbon reservoirs formation can be realized through research on the hydrocarbon thresholds and their combination.

7.2.2 Hydrocarbon Threshold Controlling on Reservoirs Formation Reservoir’s formation in petroleum system is controlled by various geological elements, including source rock, reservoir, caprock, migration, accumulation and storage. This article is to investigate the formation mechanism of the discovered hydrocarbon reservoirs in mature exploration areas in China, including Qaidam Basin, Jiyang Depression, Liaohe Depression, and Jidong Depression in the Bohai Bay Basin, by characterizing the controlling geological elements. We studied the critical geological conditions of each single element for hydrocarbon reservoirs formation, and then investigated the spatial–temporal combination characteristics of the critical conditions for each controlling element. Researches on hydrocarbon thresholds controlling reservoir include the following three orders or levels.

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Fig. 7.3 Hydrocarbon thresholds and their control on the formation and distribution of reservoirs. a HC generation and expulsion thresholds from source rock and their controlling on hydrocarbon expulsion amount; b HC accumulation threshold for porosity and their change with depth; c HC dynamics threshold for capillary pressure difference and their relation to HC saturation; d reservoir distribution threshold for HC generation intensity and their relation to the reservoir size

First, hydrocarbon migration-accumulation thresholds based on a material balance approach should be determined to evaluate the resource potential in a petroleum system. Secondly, hydrocarbon distribution thresholds should be determined to predict the favorable hydrocarbon accumulation areas. Thirdly, hydrocarbon enrichment thresholds would be determined to evaluate the hydrocarbon saturation of traps, which will provide geological evidences for drilling targets optimization. Through the three stages and orders of research, we will gradually approach the target and realize the goal of discovering hydrocarbon reservoirs, from resources assessment to targets evaluation, and from whole petroleum system study to well

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drilling. To avoid the influence of human subjective factors and significantly reduced risks of decision making and promote efficiency of hydrocarbon exploration, a suite of comprehensive quantitative evaluation techniques has been performed in this paper.

7.3 Joint Controlling Model of Multi-factors for Oil and Gas Reservoirs 7.3.1 The Concept of Hydrocarbon Migration-Accumulation Threshold (HMAT) Hydrocarbon migration-accumulation threshold (HMAT) refers to the critical geological conditions or minimum loss required for hydrocarbons during expulsion, migration, and accumulation. After meeting all the losses during expulsion, migration and accumulation, the left part of total generated hydrocarbon constitutes the effective resources. Effective resources accumulation could been taken place only if generated hydrocarbon amount surpass three different hydrocarbon thresholds, namely the expulsion threshold, accumulation threshold and reservoir scale threshold, each of which corresponds respectively to a part of hydrocarbon losses during these three geologic processes.

7.3.2 The Discrimination Criteria of Hydrocarbon Migration-Accumulation Threshold Hydrocarbon generation threshold (HGT) refers to the critical geological conditions for hydrocarbon mass transformation from original organic matter in source rocks during burial and thermal evolution process. It varies with different types of organic matter and burial history. Hydrocarbon source rocks that were not able to enter into the HGT would not become effective (Tissot and Welte 1978). Under general geological conditions, the HGT could be discriminated by vitrinite reflectance (Ro ) in source rocks. If the thermal evolution degree of source rocks is larger than Ro = 0.5%, they will pass HGT and generate massive hydrocarbon. Then, they will become effective source rocks. Hydrocarbon expulsion threshold (HET) refers to the critical geological conditions when the hydrocarbons generated from source rocks begin to be expelled largely in free phases after satisfying various demands during burial process. Such HET varies with different hydrocarbon generation quantity, different residual hydrocarbon capacity and different components (Pang et al. 2005; Peng et al. 2016). Larger hydrocarbon generation quantity (Qp) is and smaller residual hydrocarbon quantity (Qr) is, source rocks will enter into HET earlier. For those expelled hydrocarbons, smaller the proportion of dissolved hydrocarbons i is, the proportion of hydrocarbon in free

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phases (Kes) would be higher. Discrimination and evaluation standard for effective source rocks is hydrocarbon expulsion quantity in free phases (Qe) larger than 0 (Qe = (Qp-Qr)·Kes > 0). Hydrocarbon generation rocks that couldn’t enter into the HET in the petroleum system couldn’t be effective too. Hydrocarbon migration threshold (HMT) refers to the critical geological conditions when the hydrocarbons expelled from source rocks in the petroleum system begins to migrate and form reservoirs in free phases after satisfying various demands (e.g. absorption, diffusion or retention) of loss during hydrocarbon migration process. Larger hydrocarbon expulsion quantity (Qe) from source rocks and smaller the hydrocarbon loss from migration (Qml), and larger available hydrocarbon quantity for accumulation (Qa) left, the larger the hydrocarbon quantity to form reservoirs in the petroleum system would be (Pang 2014a). Discrimination and evaluation standard for an effective petroleum system is that the available hydrocarbon quantity in free phases for accumulation is above zero (Qa = Qe-Qml > 0). Petroleum system with available hydrocarbons amount in free phases for accumulation below zero cannot form hydrocarbon reservoirs. Hydrocarbon reservoirs scale threshold (HRST) refers to the minimum reservoirs scale required for commercial exploitation (Qmin) in an exploration area. Hydrocarbon accumulation with magnitude below HRST would be meaningless. Geologically, Qmin varies with different hydrocarbon geological conditions in the target area, such as the oil and gas prices, the exploration costs and so on. At present, the lower limit for commercial hydrocarbon reservoirs (Qmin) required for China’s offshore is about 2 million tons of liquid hydrocarbon equivalent; Qmin in western China with relatively low prospecting degree is about 0.5–1 million tons, and Qmin in eastern China with high prospecting degree is about 100,000–200,000 tons (Pang 2015). Under the condition of same hydrocarbon accumulation quantity provided by a petroleum system, lower the Qmin is, higher the effective resource quantity would be. When the hydrocarbon accumulation quantity is unable to reach the lower limit of the minimum hydrocarbon scale (Qmin), there would not be hydrocarbon reservoirs with commercial value formed in the petroleum system, and then no effective resources potential.

7.3.3 Joint Controlling Effect of HMAT on Reservoirs Formation The combination of HGT, HET, HMT AND HRST collectively determines the magnitude of resource potential of petroleum system. In a petroleum system, only available generated hydrocarbons meeting all the hydrocarbon losses defined by the above thresholds could form effective resources. It then can be represented by the hydrocarbon accumulation-dispersal balance model (Fig. 7.4). As shown in Fig. 7.4, during the formation and evolution of the hydrocarbon accumulation system, the thresholds of hydrocarbon generation, expulsion, accumulation, and reservoir scale

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control significantly the times and amounts of hydrocarbons in generation, expulsion, accumulation, and reservoir formation individually. After determining the total hydrocarbon generation quantity (Qp) in a petroleum system (Pang et al. 1993; Peng et al. 2016), the residual hydrocarbon quantity in source rocks (Qrm) (Pang et al. 1993, 2007, 2005), the hydrocarbon loss during migration (Ql) (Pang et al. 2007), the non-commercial hydrocarbon accumulation quantity (Qmin) (Lee and Wang 1983; Pang et al. 2007) and the structurally destroyed hydrocarbon quantity (Qdes) (Pang et al. 2002, 2012) by various means, effective hydrocarbon expulsion quantity (Qe), hydrocarbon quantity available for accumulation (Qa) and resource quantity (Q) in the system can be calculated by the material balance approach. The establishment model of HC migration & accumulation threshold controlling reservoir formation may provide new thoughts and methods for prediction of favorable exploration area and evaluation of effective resource potential.

Fig. 7.4 Hydrocarbon threshold controlling reservoir characteristics and exploration and research technical process

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7.3.4 Workflow of Oil and Gas Resource Assessment by Using HMAT Resource quantity can be predicted based on the joint model of HMAT controlling reservoir formation from three key aspects. Firstly, the hydrocarbon generation quantity of source rocks and hydrocarbon generation history need to be determined by means of physical simulation and numerical modeling. This would enable the delineation of effective source rock evolution based on HGT and HET; Secondly, related geological parameters obtained by physical and numerical simulation experiment will be used to calculate hydrocarbon loss during migration and accumulation, including the hydrocarbon residual quantity in source rocks, loss quantity during migration, small-scale accumulation and non-commercial value quantity and destroyed hydrocarbon quantity by structure movement. Related geological parameters include hydrocarbon diffusion coefficient, hydrocarbon solubility in water, gas solubility in oil and absorption coefficient of hydrocarbon in subsurface medium (Pang et al. 2003); Thirdly, predicting the distribution range of effective source rocks based on the material balance model and calculating the effective hydrocarbon expulsion quantity (hydrocarbon generation quantity minus residual hydrocarbon quantity), predicting effective hydrocarbon accumulation system and calculating hydrocarbon quantity available for accumulation (hydrocarbon expulsion quantity minus hydrocarbon loss quantity during migration), and evaluating effective hydrocarbon resources quantity (hydrocarbon accumulation quantity minus small-scale valueless accumulation quantity).

7.3.5 Application Examples of HMAT Controlling Reservoir Formation Model This article studied total hydrocarbon generation quantity and various kinds of hydrocarbon losses in Jiyang Depression, Bohai Bay Basin, East China, based on hydrocarbon migration-accumulation threshold (HMAT) controlling reservoir model. Among 28 hydrocarbon accumulation systems, 22 were predicted as effective system, it means that they are favorable for hydrocarbon exploration, Wangjiagang-Bamianhe hydrocarbon accumulation system is one of them. Hydrocarbon accumulation system refers to the geological unit of hydrocarbon generation, expulsion, migration and accumulation, and generally the hydrocarbons generated from the source rocks inside the system couldn’t be migrated to the outside and the hydrocarbons generated and expulsed from the source rocks in outer system couldn’t enter either (Magoon 1988). Hydrocarbon migration-accumulation threshold (HMAT) research was conducted on Wangjiagang-Bamianhe hydrocarbon accumulation system. Before 2001, 96 million tons of oil had been discovered in Bamianhe exploratory area and according to the resource evaluation results at that time, the hydrocarbon of this area was mainly proposed to be came from immature oil and low-mature oil (Wang et al. 1997;

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Zhang et al. 1996), and almost no residual potential left after deducting the discovered hydrocarbon. It was predicted by hydrocarbon threshold controlling reservoir model from 2001 to 2004 that there was rich residual resource in the accumulation system of Wangjiagang-Bamianhe, and the absolute quantification comparison results of biological marker compound all indicated that the hydrocarbon of the research area was from the mature source rocks in Niuzhuang Sag source kitchen and Guangli Sag source kitchen (Pang et al. 2003, 2005; Li et al. 2003, 2005). This knowledge guided the drilling of 57 wells in this area and the discovery of three hydrocarbon reservoirs, with newly proven reserves of 31.64 million tons, which was increased by 230% compared with that of four years ago (Xu et al. 2006). The HMAT controlling reservoir formation model have been applied detailedly to other systems in Jiyang Depression. The favorable areas with more residual resources were predicted, and a lot of subtle reservoirs were discovered, and the prospecting well success rate was increased largely by 20% points in 3 years.

7.4 Prediction of Favorable Area for Oil and Gas Accumulation 7.4.1 The Concept of Hydrocarbon Distribution Threshold (HDT) Classic petroleum geology theory conclude six geological factors or elements from a lot of geological parameters, including source rocks, reservoir, cap rocks, migration condition, trap, and preserve condition, which control on hydrocarbon reservoir formation and distribution (Fig. 7.5). These 6 aspects are not independent of each other, and some elements can neither objective description nor quantitative characterization, thus, furthering hydrocarbon accumulation research is inconvenient. HDT refer to the critical geological condition that to control hydrocarbon reservoir formation and distribution. A lot of study show that hydrocarbon reservoirs formation and distribution were controlled by four independent elements. Through analyzing and studying 2068 hydrocarbon reservoirs in China, it was found that their formation and distribution were controlled by 4 independent elements, including effective hydrocarbon source rock, optimal-facies reservoir, regional caprock and low potential area (Fig. 7.5). Effective hydrocarbon source rock (S) provides material source for hydrocarbon reservoirs formation; optimal-facies reservoir (D) provides hydrocarbon accumulation with pore space; low-potential area (P) provides hydrocarbon migration and accumulation with power and trap; regional caprock (C) provides hydrocarbon reservoirs with protection. These 4 elements are mutually independent, and can conduct both objective description and quantitative characterization, and are essential to hydrocarbon accumulation, so they are called functional elements. In these 4 functional elements, low potential area (P) has 4 appearance forms in nature,

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Fig. 7.5 Four functional elements controlling hydrocarbon reservoir formation in a petroliferous basin

different low potential areas control the hydrocarbon reservoirs formation and distribution with different types. By combination with other three elements (Fig. 7.5): lower gravitational potential energy region of paleohighs (CDMS) mainly controls the formation and distribution of anticlinal reservoirs; lower pressure energy region (CDFS), where pressure releasing pathway of fault zone, mainly controls the formation and distribution of fault block-type hydrocarbon reservoirs; lower interfacial energy region (CDLS) with higher porosity and permeability strata, mainly controls the formation and distribution of lithologic hydrocarbon reservoirs; lower dynamics energy region (CDVS) at the basin margin or paleo uplift slope, mainly controls the formation and distribution of stratigraphic hydrocarbon reservoirs (Pang 2015; Guo et al. 2016).

7.4.2 Mechanism of HDTs Joint Controlling Reservoir Distribution According to the characteristics of 2068 hydrocarbon reservoirs of different types distribution in main petroliferous basins in China, it was found that source rock controls the formation and distribution of hydrocarbon reservoirs, more than 90% of reservoirs discovered are distributed in or around the hydrocarbon expulsion center of source kitchen (S). Farther to the center of source kitchen, the smaller probability for accumulation will be. The critical conditions of source-control hydrocarbon accumulation such as the distribution boundary, range, and probability of reservoirs

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formation, can be predicted by studying the relation between the source rock and the reservoirs. Reservoir stratum facies (D) controls the formation and distribution of hydrocarbon reservoirs, and more than 98% reservoirs are distributed in optimalfacies reservoir stratum with sediment particles neither too coarse nor too fine (0.1 mm ≤ diameter ≤ 1.0 mm). If the particle diameter in reservoir stratum becomes larger or smaller, the relative porosity and permeability of reservoir stratum will become worse, and the probability of hydrocarbon accumulation in the reservoirs strata will decrease. Regional caprock (C) controls the formation and distribution of hydrocarbon reservoirs, and more than 93% reservoirs are distributed under the caprock with effective thickness ranges from 25 to 600 m. If the thickness becomes smaller or bigger, the probability of hydrocarbon reservoirs formation will decrease. If the caprock is too thin, the caprock continuity in a plane will be easy to be destroyed by fault, which is not beneficial for hydrocarbon to accumulate to form a reservoir under caprock. If the caprock is too thick, the subsurface fluid will not migrate upward through pressure releasing pathway, so hydrocarbon is hard to accumulate to form a reservoir. Low potential area (P) controls the formation and distribution of hydrocarbon reservoirs. More than 96% of structural reservoirs are distributed in lower potential energy region (P1 = M) on the top of a buried mountain. Nearer to mountain high point, the lower potential energy would be, and the accumulation probability will be larger One hundred percent of lithologic hydrocarbon reservoirs are distributed in lower interfacial energy region with higher porosity and permeability (P2 = L). If the potential energy inside the reservoir is lower, and the peripheral potential difference (capillary force difference) is bigger, the probability of hydrocarbon reservoirs formation will increase. More than 90% of fault hydrocarbon reservoirs are distributed in lower-pressure energy region near to fault pressure-relief belt (P3 = F). If the distance to fault pressure-relief belt is shorter, and the fluid pressure is smaller, the probability of hydrocarbon accumulation will increase. In the regions with lower potential field, the power for hydrocarbon migration and accumulation is larger, and the probability of hydrocarbon accumulation is higher. Figure 7.6 shows the examples of critical conditions studies for hydrocarbon distribution controlled by four functional elements in offshore area of Bohai Bay Basin, east China. Major elements such as source kitchen (Fig. 7.6d), optimal-phaes reservoir (Fig. 7.6b), regional caprock (Fig. 7.6a) and palaeo-high (Fig. 7.6c) all have a critical conditions or geological threshold for hydrocarbon reservoir formation. In addition, these elements also determine if the hydrocarbon reservoirs can be formed and what their probability would be. For different petroliferous basins or petroleum systems, the critical conditions for hydrocarbon reservoirs distribution are different, but the hydrocarbon thresholds or their matching model of four function elements controlling on reservoirs formation are the same.

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Fig. 7.6 The research and statistical analysis results of functional elements controlling hydrocarbon reservoir distribution threshold in the sea area of Bohai Bay Basin. Relative distance to paleohigh = (absolute distance)/(the distance between the boundary and vertices of structural paleohigh)

7.4.3 Principle for Predicting Oil and Gas Reservoirs by Using HDTs According to research findings, a single functional element has strong affection on hydrocarbon reservoirs distribution, but cannot form hydrocarbon reservoirs. However, spatial–temporal combination of four functional elements can determine the formation and distribution of hydrocarbon reservoirs (Fig. 7.7). This regularity is termed as multiple-elements matching model for controlling reservoir distribution, which is represented by T-CDPS. T, C, D, P and S represent reservoir formation epoch, regional caprock, reservoir stratum facies, low potential region and source rock, independently. T-CDPS presents the multiple-elements matching model of functional elements in reservoir formation epoch. T-CDPS has three levels of meaning. Firstly, for the vertical direction, four major functional elements control the favorable accumulation strata when constituting orderly source-reservoir-potential-caprock combination (C/DP/S) vertically from bottom to top. If the combination relationship for each elements were not of the sequential order of “source-reservoir-potential-caprock”, which is constituted as the order of lower-generating hydrocarbon (S), upper-reservoir accumulating hydrocarbon (D) with low-potential energy (P), top-caprock preserving hydrocarbon (C), reservoirs will not be easily formed or the efficiency would be poor. Secondly, these four functional elements would appeare and be combined effectively (C/D/P/S) at a particular geological time (T), which is a large-scale period of reservoirs formation. If any functional elements were absent, or they did not appear over the same period, or they were not matching to each other when they appeared,

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Fig. 7.7 The prediction model of critical condition of functional elements controlling reservoir and elements combination controlling hydrocarbon distribution threshold

such hydrocarbon accumulations cannot be formed. Analysis of all hydrocarbon reservoirs discovered shows no exception. Thirdly, in the planar area, superimposed combination of boundary and range of four major functional elements controls the most favorable accumulation area. If the controlling ranges of all functional elements were not overlapped, hydrocarbon accumulations would not be formed. According to the spatial distributions of 603 structural reservoirs in the Tarim Basin, ranging from 80 to 94% of hydrocarbon reservoirs discovered so far are in the overlapping areas of four functional elements. While 5–17% of the reservoirs were found in areas with three superimposed functional elements; and only less than 5% of the reservoirs were found in areas with two elements or less superimposed. Under the actual geological conditions, combination of the source-reservoircaprock (S-D-C) and different lower potential fields Pi (i = M, F, L and V) will develop different types reservoirs. Reservoirs formation models for different potential energy can be expressed as four different forms, as T-CDMS, T-CDFS, TCDLS and T-CDLS. The four models can be used to predict and evaluate different hydrocarbon reservoirs including anticalinal reservoirs, fault reservoirs, lithologic reservoirs, stratigraphic reservoirs, respectively.

7.4.4 Workflow of Favorable Area Prediction Based on HDT controlling reservoirs models, the paper proposed new methods of predicting and evaluating favorable hydrocarbon accumulation area. Four aspects of work should be carried out if applying the above models to conduct quantitative

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prediction on hydrocarbon reservoirs distribution. Firstly, based on source rock expulsion history forward modeling and homogenization temperature measuring inversion for fluid inclusion, the stages and times of hydrocarbon reservoirs formation in petroleum system are determined. Secondly, through basin analysis, geological conditions of (S, D, P, C) controlling hydrocarbon reservoirs formation and distribution are restored to every large accumulation period. Thirdly, record the distribution features of current hydrocarbon reservoirs discovered, and establish quantitative relationships between hydrocarbon reservoirs and functional elements. Fourthly, apply functional element combination models of different forms (T-CDPi S) to predict the formation and distribution of hydrocarbon reservoirs of different types.

7.4.5 Application Examples Bohai Bay Basin is the largest hydrocarbon production base in China at present, whose offshore part is the main hydrocarbon producing area of China National Offshore Oil Corporation, having aroused general concern of scholars due to lower exploration degree. Hydrocarbon of Bohai Bay Basin mainly comes from deep buried Paleogene Shahejie Formation source rock and Dongying Formation source rock. Shahejie Formation, Dongying Formation and Guantao Formation from bottom to top are all their target stratums, in which caprocks are developed and fine reservoircap combination is composed. The hydrocarbon filling mainly occurs within nearly 20 Ma in the basin. Hydrocarbon reservoirs found so far are mainly controlled by positive uplift and traps, include anticline structure, fault zone, buried hill, less lithologic wedge out and stratigraphic overlaping. In Fig. 7.8, T-CDMS model is applied to predict the distribution of anticline hydrocarbon reservoirs of Guantao Formation in the offshore area of Bohai Bay Basin. The 4 small graphs around show the boundary and favorable range for reservoirs distribution of 4 functional elements including caprock, optimal-phases reservoir, paleo uplift, and source kitchen, respectively. Figure 7.8 shows the favorable area for reservoirs formation of anticline reservoirs determined by superimposed compounding of 4 elements affection. Nineteen favorable anticline reservoir accumulation area in Guantao Formation have been predicted. Among the 16 discovered hydrocarbon zones, 15 of them were distributed in the predicted favorable reservoir accumulation areas, and the inspection agreement rate reach at 95.5%. Actually, reservoirs formation models (T-CDPi S) of four different potential energy have been applied to Shahejie Formation, Dongying Formation and Guantao Formation, and two hundred and ninety favorable areas for reservoirs formation have been predicted and evaluated. Among 105 discovered hydrocarbon zones, one hundred of them were distributed in the predicted favorable areas, and the average inspection agreement rate reach at 95.2%. The research results have been applied by oil company to guide the exploration deployment and wells drilling, and about 8.6 × 108 m3 oil equivalent reserves were discovered. The average prospecting well success rate in period of research time (2007 ~ 2009) is 49%, which was increased

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Fig. 7.8 Functional elements combination prediction and evaluation results of structural reservoirs in the sea area of Bohai Bay Basin. The 4 minimal graphs around are critical conditions of hydrocarbon controlling reservoir distribution of 4 functional elements including C, D, M, and S respectively

by 20% points compared with the average prospecting well success rate 29% in the last three years (2004 ~ 2006) (Xia 2012; Wang et al. 2016).

7.5 Optimization of Drilling Targets for Oil and Gas 7.5.1 The Concept of Hydrocarbon Accumulation Threshold (HAT) Hydrocarbon enrichment threshold refers to the critical conditions for hydrocarbon enrichment. The controlling effect of hydrocarbon enrichment includes two aspects, one is the critical conditions controlled by geological factors and other is the critical conditions controlled by combination of geological factors. For the discovered hydrocarbon reservoirs in Jiyang Depression, their statistical analysis results of reservoir forming conditions show that the hydrocarbon-expulsion intensity of source rocks, reservoir porosity characteristics, and potential difference between the internal and external capillary force of the trap are three essential key elements for hydrocarbon enrichment (Fig. 7.9). Hydrocarbon source is the material basis for hydrocarbon

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enrichment, and is the first essential key element to affect the hydrocarbon enrichment degree of the trap. The discovered hydrocarbon reservoirs is mainly formed and distributed inside or around the source kitchen. The closer to the source kitchen center, the greater the hydrocarbon-expulsion intensity of source rocks will be, and higher the degree of hydrocarbon enrichment in the trap will be (Fig. 7.9). High porosity and permeability reservoir provides good space for hydrocarbon enrichment, which is the second essential key element. The greater the permeability and porosity of the reservoir are, the higher the probability of drilling commercial reservoirs will be, and higher the hydrocarbon saturation in porosity and the production of prospecting wells will be. Conventional reservoirs currently discovered mainly exist in thick sandstone, fine sandstone, fine siltstone and siltstone with better porous conditions, where formations consist of particles with the sizes of 0.1–1.0 mm, the porosity of generally greater than 12% and the permeability of higher than 1 mD (Fig. 7.9). The capillary potential difference between inside and outside of the traps provides driven force for hydrocarbon accumulation, and is the third key element for hydrocarbon enrichment in traps. The statistical analysis results of 13,980 reservoirs under the actual geological conditions in the Bohai Bay Basin show that, the prerequisite for the hydrocarbon enrichment in a trap is that the potential (capillary force) of surrounding rock outside the trap should be over 2 times higher than the potential energy (capillary force) of the reservoir inside the trap (Fig. 7.9). Traps with buried depth from 1000 to 3500 m have the largest internal–external potential difference and the strongest ability for hydrocarbon enrichment. It is showed that the degree of hydrocarbon enrichment in the trap is related to three elements, i.e., source condition, reservoir porosity and permeability, and potential difference between inside and outside of trap. It will be difficult for hydrocarbon to accumulate largely in the trap if any one of the three elements is invalid or missing, in fact it will lead to be poor of oil–gas in the trap.

7.5.2 Quantitative Model of HATs Joint Controlling Reservoirs Through statistic analysis and simulating modeling, the affection of geological factors on hydrocarbon enrichments are determined and quantitatively expressed, and three of them are very important and indispensable. Figure 7.10 shows the research results of He-8 member of Sulige area, Ordos Basin. Near-source enrichment of hydrocarbon is the basic characteristic of hydrocarbon accumulation. The relationship between hydrocarbon enrichment degree and source rock can be quantitatively represented in source index (SI). The closer of target strata to source rock, the larger the source index (SI) will be, and the higher the enrichment degree of hydrocarbon in target strata (Fig. 7.10a). Hydrocarbon enrichment in the optimal-reservoir-facies is another characteristic of hydrocarbon accumulation in target strata. The relationship between hydrocarbon enrichment degree and reservoir facies can be quantitatively

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Fig. 7.9 The main controlling factors of hydrocarbon enrichment and critical conditions as well as basic characteristics of each factor in the Jiyang Depression, Bohai Bay Basin

represented in facies index (FI). The larger the FI, the higher the enrichment degree of hydrocarbon in target strata will be (Fig. 7.10b). Hydrocarbon enrichment in Lower potential is the third characteristic. The relationship between hydrocarbon enrichment degree and ratio of outer capillary pressure to inter capillary pressure for target strata can be quantitatively represented in potential difference index (PI). The larger the PI is, the higher the enrichment degree of hydrocarbon in target strata will be (Fig. 7.10c).

7.5.3 Application of HATs Joint Controlling Oil and Gas Model A lot of research results for hydrocarbon enrichment in target strata or traps show that one single key element has strong affection on hydrocarbon enrichment, but cannot led to hydrocarbon enrichment. However, overlaying areas of three key elements controlling hydrocarbon enrichments determine the formation and distribution of hydrocarbon reservoirs. A comprehensive index characterizing the combination of these three elements was proposed to predict and evaluate the enrichments degree of hydrocarbons in the target strata or traps, it was named as facies-potential–source index (FPSI). Figure 7.11 shows the application of FPSI in He-8 member of Sulige area, Ordos Basin. The Ordos Basin is the largest petroliferous basin in central China. Its most remarkable petroleum geological characteristic is that unconventional tight hydrocarbon resources widely develop in the Triassic and Permian strata. The largest

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Fig. 7.10 The relationship between hydrocarbon saturation and the source-phase-potential index and its quantitative characterization of He 8 member of Sulige area, Ordos Basin

tight gas field is formed in Sulige area in this basin. Natural gas mainly accumulates in the sandstone reservoir of upper Paleozoic Shanxi Formation and Shihezi Formation, with the reservoir porosity ranging from 3.2 to 11.8%, averagely about 7%; permeability of less than 1 mD, averagely 0.5 mm and wide variation of gas saturation range from 10 to 80%. He-8 member is the main target layer section. Studies have shown that the natural gas of He-8 member in the Sulige area mainly comes from the source rocks developed in the lower Taiyuan Formation, Shanxi Formation and the lower Shihezi Formation (Fig. 7.11). The analysis and research results based on 280 prospecting wells before 2013 show that the gas bearing degree of He-8 member is closely related to the hydrocarbon-expulsion intensity of source rocks, the reservoir permeability and porosity, and the potential difference between the internal and external of reservoir. Based on these studies, Facies-Potential-Source Index (FPSI ≤ 1) is proposed to evaluate the hydrocarbon enrichment. The quantitative relationships between FPSI and hydrocarbon accumulation probability (Fig. 7.11), between FPSI and gas saturation in reservoir (Fig. 7.11), and between FPSI and the reservoir production capacity (Fig. 7.11) are established respectively. Based on the FPSI, plane change of gas bearing degree of the He-8 member have been predicted and evaluated, and preference drilling targets are selected in the Sulige area. It is showed that in the northern, middle, and southern sections of the research area, several areas with higher FPSI (FPSI > 0.75) without drilling are predicted. They are potential gasbearing areas that are expected to produce commercial gas yield in further deepening

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Fig. 7.11 The results of prediction and evaluation of oil–gas saturation of He 8 member of Sulige area, Ordos Basin

the exploration. The research results were applied by Changqing Oilfield Company to guide the drilling of 45 wells from 2013 to 2014, among which 38 obtained business gas yields, with prospecting well success rate of more than 86.7%, increased by 17% points compared to its average rate of previous three years. This indicates that the relative theoretical model, method and technology are feasible and reliable.

7.6 Summary The petroleum system concept unifies the trap-controlled reservoir effect and sourcecontrolled hydrocarbon accumulation effect, which laid the foundation for modern hydrocarbon accumulation theory and provided a workflow for hydrocarbon accumulation process analysis and accumulation area prediction. However, it fails to address the qualitative and subjective nature of the petroleum system during hydrocarbon

References

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reservoir distribution prediction. This article, based on the geologic feature analysis and accumulation process simulation of over 10,000 hydrocarbon reservoirs in matured exploration areas in China, proposes a concept model of hydrocarbon thresholds controlling reservoirs, which enable petroleum system analysis to be realized quantitatively. Hydrocarbon reservoirs formation in petroliferous basins are found to be controlled by three orders or levels of hydrocarbon thresholds: (1) hydrocarbon migration-accumulation threshold, (2) hydrocarbon distribution threshold, and (3) hydrocarbon enrichment threshold. The first threshold encompasses the critical geological conditions during hydrocarbon migration and accumulation, and controls the potential resources in petroleum system. The second threshold prescribes the critical geological conditions for hydrocarbon reservoirs distribution, and controls the distribution and types of hydrocarbon reservoirs. The third threshold represents the critical geological conditions for hydrocarbon enrichment, and controls the hydrocarbon enrichment targets distribution and their hydrocarbon saturation in traps. For a given petroleum system, determination of the hydrocarbon migration-accumulation, distribution, and enrichment thresholds can initially predict the effective potential resource, and then predict the favorable accumulation area and finally predict the favorable hydrocarbon enrichment target, respectively. It thus can realize three-levels of exploration from the large to small scale, and from outside to inside, and progressively reduce risks and promote exploration success. The hydrocarbon thresholds controlling reservoirs model has been applied to over 20 basins both in China and worldwide and helped the petroleum companies increasing their exploration success rate significantly. The model offers new sights and new methods for hydrocarbon exploration under complicated conditions.

References Dow W G. 1974. Application of oil correlation and source rock data to exploration in Williston basin. AAPG Bulletin, 58(7): 1253–1262. Guo J G, Xu J, Guo F T, et al. 2016. Functional-element constraint hydrocarbon distribution model and its application in the 3rd member of Dongying Formation, Nanpu Sag, Bohai Bay Basin, eastern China. Journal of Petroleum Science and Engineering, 139, 71–84. Hunt J M. 1979. Petroleum geochemistry and geology. San Francisco: W H Freeman. Jin Z J, Zhang Y W, Wang J. 2003. The mechanism and distribution law of hydrocarbon accumulation. Beijing: Petroleum Industry Press, 10–121. Lee P J, Wang P C C. 1983. Probabilistic formulation of a method for the evaluation of petroleum resources. Mathematical geology, 15(1): 163–181. Levorsen A I. 1956. Geology of Petroleum, 1st edition. W. H. San Francisco: Freeman and Company: 703. Levorsen A I. 1967. Geology of Petroleum, 2nd edition. W. H. San Francisco: Freeman and Company: 724. Levorsen A I. 1936. Stratigraphic versus structural accumulation. AAPG Bulletin, 20(5), 521–530. Li S M, Li M W, Pang X Q, et al. 2003. Geochemistry of petroleum systems in the Niuzhuang South Slope of Bohai Bay Basin-part 1: source rock characterization. Organic geochemistry, 34, 389–412.

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Li S M, Pang X Q, Li M W, et al. 2005. Geochemistry of petroleum systems in the Niuzhuang South Slope of Bohai Bay Basin: Part 4. Evidence for new exploration horizons in a maturely explored petroleum province. Organic Geochemistry, 36, 1135–1150. Magoon L B, Dow W G. 1994. The petroleum system from source to trap. AAPG Memoir, 60, 3–23. Magoon L B, 1988. Petroleum systems of the United States. US Geological Survey Bull. Magoon L B, 1992. The petroleum system: status od research and methods. U. S. Geological Survey Bulletin, 14(2): 98. McCollough E H. 1934. Structural influence on the accumulation of petroleum in California. In: Wrather, W.E., Lahee, F.H. (Eds.), Problems of Petroleum Geology. AAPG, Tulsa, 735–760. Pang X Q, Jiang Z X, Zuo S J. 2002. Study on destroyed hydrocarbon amount by tectonic event in superimposed basins[J]. Geological Review, 48(4): 384–390. Pang H, Chen J Q, Pang X Q, et al.2012. Estimation of the hydrocarbon loss through major tectonic events in the Tazhong area, Tarim Basin, west China. Marine and Petroleum Geology, 38: 195–210. Pang X Q, Li M W, Li S M, et al. 2003. Geochemistry of petroleum systems in the Niuzhuang South Slope of Bohai Bay Basin-part 2: evidence for significant contribution of mature source rocks to “immature oils” in the Bamianhe field. Organic geochemistry, 34: 931–951. Pang X Q. 2014a. Hydrocarbon migration and accumulation threshold and resources evaluation. Beijing: Science Press: 3–103. Pang X Q. 2015. Hydrocarbon distribution threshold and accumulation zone forecast. Beijing: Science press: 3–134. Pang X Q, Chen Z M, Fang Z K. 1993. Numerical simulation of hydrocarbon generation, remaining and expulsion of source rocks in geohistory and their quantitative evalution. Beijing: Petroleum Industry Press: 1–177. Pang X Q, Li M W, Li S M, et al. 2005. Geochemistry of petroleum systems in the Niuzhuang south slope of Bohai Bay Basin: Part 3. Estimating petroleum expulsion from the Shahejie formation. Organic Geochemistry, 36: 497–510. Pang X Q, Luo X R, Jiang Z X, et al. 2007. Hydrocarbon accumulation and dissipation mechanisms and its quantitative modeling in China’s superimposed basins. Beijing: Petroleum Industry Press: 24–38. Peng J W, Pang X Q, Shi H S, et al. 2016. Hydrocarbon generation and expulsion characteristics of Eocene source rocks in the Huilu area, northern Pearl River Mouth basin, South China Sea: Implications for tight oil potential. Marine and Petroleum Geology, 72: 463–487. Perrodon A. 1992. Petroleum Systems: Models and Applications. Journal of Petroleum Geology, 15(2): 319–325. Tissot and Welte. 1978. Petroleum formation and occurrence - a new approach to oil exploration. London: Elsevier Applied Science Publishers Ltd. Wang M, Pang X Q, Li H Q, et al. 2008. Hydrocarbon expulsion characteristic of hydrocarbon source rock and prediction of favorable region in Binbei area. Journal of Southwest Petroleum University (Science and Technology Edition), 30: 25–29. Wang T, Pang X Q, Hao F. 2016. The formation, enrichment and distribution prediction of oil and gas accumulation in the Bohai basin, Beijing: Geological Publishing Press. Wang T, Zhong N, Huo D, et al. 1997. Several Genetic Mechanisms of Immature Crude Oils in China. ACTA SEDIMEN TOLOGICA SINICA, 15(2): 75–83. White. 1885. The Geology of Natural Gas. Science, 42–44. Xia Q. 2012. Formation distribution and resource potential of oil and gas reservoirs in Bohai sea area. Beijing: Petroleum Industry Press. Xu Y W, Pang X Q, Li X, et al. 2006. Theory and Practice of Oil and Gas Exploration in The Continental Mature Basin: A Case Study and Application of Oil and Gas Accumulation in the Bamianhe Exploration Area, Bohai Bay Basin. Beijing: Petroleum Industry Press. Zhang L, Hong Z, Liao Y, et al. 1996. Analysis on Biomarkers and Carbon Isotope of Low Maturity Oil in Bamianhe Oil Field. Geological Geochemistry, 6: 73–76.

Chapter 8

Prediction and Evaluation of Tight Oil and Gas Reservoirs

New Understanding: (1) Continuous tight oil/gas reservoirs are widely developed in deep petroliferous basins, and their dynamic mechanism for oil/gas migration and accumulation is related to oil/gas generation and expulsion from their surrounding source rocks dealing with 5 types and 9 driving forces, including diffusion of oil/gas, thermal volume expansion of minerals and fluids, compaction of overlying strata, new products volume increasing, and capillary pressure difference (CPD) between the reservoirs and surrounding rocks. (2) Buoyancy-driving dominates the oil/gas migration and accumulation in reservoirs with high porosity and permeability, while capillary pressure difference (CPD) between surrounding source rocks and nearby reservoir layers is more important for oil/gas migration out of source rocks and accumulation in deeper and tighter reservoirs with increasing depth. (3) The effective CPD is the most important driving force for deep tight oil/gas reservoirs formation. The accumulative natural gas and liquid hydrocarbon expelled by per cubic meter of Cambrian source rocks in the Tarim Basin are 1.0–1.5 m3 and 0.5–1.0 kg, respectively. The contribution of CPD is the largest with an average of more than 50%, followed by compaction (10–40%), with the third of kerogen transformation and clay dehydration (5–30%), the fourth of thermal expansion of rock fluid (2–20%), and the least is the diffusion (< 10%). (4) Effective Capillary Pressure Difference, or the CPD subtract capillary resistance of oil/gas migrating in reservoirs, is the dominant driving force for oil/gas migration out of source rocks and accumulation in deep and tight reservoir layers, oil/gas saturation, daily production, proved reserve in reservoir layers and reservoirs number directly increases with increasing the value of ECPD. (5) Dynamic process of oil/gas accumulations in reservoirs during their burial and densification is divided into four stages: buoyancy are dominant driving forces in shallow stage; multi-driving forces including ECPD and buoyance are essential in middle stage; ECPD is the most important in deep stage; and the stress and geofluids activities control the reformation and adjustment of formed oil/gas reservoirs in final stage.

© Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_8

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8.1 Introduction and Issue Buoyancy has been regarded as major driving force for oil and gas to migrate upward through the carrier bed and accumulate in trap structures in petroliferous basins (White 1885; Levorsen 1967). Oil and gas reservoirs formed by buoyance show unique geological characteristics such as the oil/gas converging at the high point of a trap, capped with sealing strata at high position, accumulated in reservoir layers with high porosity of > 12%, bearing high pressure within the hydrocarbon fluids (Pang et al. 2020), the reservoirs are separated from their source rocks and the oil/ gas saturation increases with increasing porosity and permeability of the reservoir layers (Wang et al. 2020). These constitute the core content of the classical theory of petroleum geology, so far 14,645 × 108 t oil equivalent reserves in the world have been proved under guidance of the classic theory. However, more and more unconventional deep and tight oil and gas reservoirs have been proven in exploration-restricted areas in petroliferous basins since the discovery of continuous tight gas reservoirs in the deep depression of the Albert Basin in Canada in 1978 (Master 1979), which was once considered impossible to accumulate oil/gas by classical petroleum geology theory. These unconventional reservoirs also show unique geological characteristics, such as the oil/gas converging in low-depression regions, oil/gas position inversion with water being lower, oil/gas accumulation in reservoir layers with low porosity, oil/ gas reservoirs stable at low pressure and closely connected to source rocks in space, indicating that the formation and distribution of oil/gas reservoirs is not controlled by buoyancy and traps (Pang et al. 2020). So far, billion tons of oil and gas reserves have been discovered in tight reservoir layers with depth > 4500 m. The deep and tight oil and gas reservoirs are becoming more and more important in recent years to support the global industry, and up to 72.2 and 27.8% of recoverable oil and gas reserves have been proved in the deep and tight reservoir layers in 2019 (Tong 2018). The whole oil and gas industry has been shifting their exploration focus to deep tight reservoirs. Up to now, the maximum depth of drilled wells on the earth is 12,262 m (Popov 1999), and the proven deepest oil field in the ocean is 9146 m in depth including water thickness (Kaiser and Narra 2019) and the deepest one on land is more than 8000 m deep (Yu 2020). In the Tarim Basin of China, the average depth of exploratory wells over the past 10 years is larger than 6000 m (Fig. 8.1), and more than 92% of the newly proved reserves are from reformed deep and tight formations (Sun 2013). The test daily production in some wells is larger than 1 million cubic meters of gas equivalent from reservoirs with a porosity of less than 5% in the western basins of China (Wang 2018, 2020), showing enormous exploration potential in the deep and tight layers. Understanding dynamic mechanism of oil and gas accumulation and enrichment in deep and tight reservoir layers is of practical significance for predicting oil/gas reservoirs distribution and improving exploration efficiency. As deeper and tighter oil and gas reservoirs are discovered, more and more unusual phenomena are observed and cannot be explained by classic theories. Figure 8.2 illustrates the abnormal variations of drilling results from 67,944 reservoirs of 2938 exploration wells in the Bohai Bay Basin of China with increasing depth. The oil and

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Fig. 8.1 Distribution characteristics of proved reserve of oil and gas in the Tarim Basin. a The vertical distribution indicates that the 92% of proved oil and gas reserve are in the deep and tight reservoirs with depth larger than 4500 m. b The favorable exploration areas include three types, including in the area of complex structures in the foreland basin (red), deep carbonate rocks (pink), and lithology and stratigraphic reservoirs in the platform basin (green). All the discovered oil and gas reservoirs and 95% of proved reserve are distributed in the favorable exploration area

gas saturation and proved reserve, daily test production and number of reservoirs all increase with increasing depth and decreasing reservoir porosity and permeability from the surface to about 3000 m, it is very difficult to understand this kind of strange and abnormal situations because the migration and accumulation of oil/ gas in reservoir layers are dominated by buoyance. Given consideration of these reservoirs widely distributed in the tight reservoirs and are closely related to source rocks, most scholars believe that the hydrocarbon migration and accumulation in tight reservoir layers (Fig. 8.3) is driving by the non-buoyance forces directly caused by the hydrocarbon generation and expulsion from source rocks (Pang et al. 2021a). However, people do not understand what kind of non-buoyance is the most important for driving hydrocarbon to migrate and accumulate in deep and tight reservoirs to date, because there are 5 types and 9 driving forces related to them, such as compaction by overlying strata (Chen 1989), products volume inflation from organic matter transformation (Espitalie 1980) and clay minerals dehydrate (Magara 1975a), volume increase of mineral and fluids (water, oil and gas) in source rocks due to higher temperature (Olgaard 1997), hydrocarbon diffusion by concentration gradient (Leythaeuser 1982), and capillary pressure difference between surrounding source rocks and inner reservoirs (Berg 1975; Deroche 2019). A large number of previous studies have been carried out on the roles of the above various forces in the oil and gas transportation process, each driving force appears to play an important role in the processes of hydrocarbon expulsion from source rocks and oil/gas accumulation in tight reservoirs, but which kind of them is the most important in actual geological condition is still unclear to date. To reveal essential driving forces and quantitatively evaluate their contributions to oil and gas tight reservoirs formation in deep area is of practical significance for understanding the main controlling factors and basic

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Fig. 8.2 The drilling results of sandstone oil/gas reservoirs in the Tertiary Formation in the Nanpu Sag of the Bohai Bay Basin showing abnormal variation of the oil/gas saturation, daily production and number of reservoirs with increasing depth. a Variations of drilling results and reservoir porosity with buried depth. b Variations of reservoirs permeability with porosity. c Variations of oil/gas-bearing layers number and reserves percentage with increasing depth. d Variations of oil/ gas saturations and daily production with buried depth

laws of their distribution and reducing exploration risks. In this study, we focus on the differences and correlations of these driving forces in oil/gas expulsion from source rocks to quantify their relative contributions in a tight reservoir formation with increasing depth, and reveal the controlling mechanism of dominant factors on oil/gas expulsion and accumulation.

8.2 Method and Workflow 8.2.1 Identification and Classification of Driving Forces and Their Effects Previous studies have been carried out on the hydrocarbon expulsion by 5 types (T1– T5) and 9 driving forces (F1–F9), and sufficient evidences by each driving force were proposed. Figure 8.4 illustrates the differences of these driving forces in burial process of source rocks. Hydrocarbon diffusion (T1) following concentration gradient from source rocks to reservoirs is regarded as a type of driving force for hydrocarbon expulsion from source rocks (Leythaeuser 1982; Rose 2001; Qiao et al. 2019), expressed as F1. But the total expelled hydrocarbon amount is limited because the diffusion coefficient of hydrocarbons through rock medium is very small.

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Fig. 8.3 Distribution of deep and tight reservoirs and their relation to Buoyance-driven Hydrocarbon Accumulation Depth (Modified after Pang et al. 2021a). a Driving force for hydrocarbon migration is changed from buoyancy to non-buoyancy with increasing depth. BHAD refers to Buoyancy-driven hydrocarbon accumulation depth, b distribution of conventional and unconventional oil and gas resources, and their relation to BHAD, c decreases of maximum pore throat radius in the target layer result in transformation of hydrocarbon accumulation dynamic mechanism from shallow reservoir to deep and tight reservoirs

Fig. 8.4 The driving forces for hydrocarbon expulsion from source rocks confirmed by previous studies and the variation characteristics of the hydrocarbon expulsion amount under the action of each type of force with increasing depth

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Thermal expansion (T2) of minerals and fluids is considered as another type of driving forces for hydrocarbon expulsion from source rocks. This type of driving forces can be subdivided for the thermal expansion of mineral skeleton (F2), water (F3), liquid oil (F4), and nature gas (F5), respectively. The expelled fluids amount or hydrocarbon amount are mainly related to the total amount of minerals, water, oil and gas in the source rock and their thermal expansion coefficients (Magara 1975b). The driving force increases with the increase of burial depth and geothermal temperature, but may be mainly confined at the early and middle stages, because the residual pore fluids (water, oil, and gas) in the source rock are few at the late stage. In addition, the expelled hydrocarbon amount by mineral expansion is very limited because the thermal expansion coefficient of minerals is quite small and dispersed within the whole burial process of the source rocks. Compaction of source rocks (T3) by overlying strata is also regarded as a type of driving force for hydrocarbon migration; and the driving force is expressed as F6. Its contribution is manifested in two aspects: one is the discharge of a large number of dissolved hydrocarbons within the pore water; and the other is to reduce the porosity, the residual hydrocarbon saturation in the pores is increased and the free phase hydrocarbon is discharged in large quantities (Chen et al. 1989). The compaction may be mainly confined at the early stage of hydrocarbon expulsion in the argillaceous source rock, and may not be important at the middle and late stages with larger burial depth. In addition, its significance for hydrocarbon expulsion of water-soluble phase may be greater than that of other phase states; however, the expelled hydrocarbon amount by compaction is very limited because the solubility of oil and gas in water is very small, generally less than 200 ppm. Products volume expanse (T4) of organic parent material pyrolysis transformation (Espitalie et al. 1980) and clay minerals dehydration (Magara 1975a; Lindgreen 1985) is regarded as the fourth type of driving forces for hydrocarbon expulsion, and the driving forces are expressed as clays dehydration (F7) and kerogen transformation to oil/gas (F8). Experiment results showed that the density of kerogen change from larger than 1.2–1.3 g/cm3 to less than 1.0 g/cm3 after kerogen was converted to oil and gas. The montmorillonite per unit weight loses a large amount of interlayer water at 100–130 °C and is converted into illite, which can release 0.245-unit weight of water. This effect mainly occurs at the middle stage of hydrocarbon expulsion from source rocks, and may not be important at the early stage of smaller burial depth and the late stage of larger burial depth. In addition, it may be more significant for oil and oil-soluble gas than for free phase gas. The increase of minerals and fluids volume caused by higher temperature (Magara et al. 1975b) is regarded as a driving force for hydrocarbon expulsion; however, their contribution to hydrocarbon expulsion in source rocks may be very limited due to their small expansion coefficient and dispersion in each stage of burial process. Capillary pressure difference (T5) between surrounding source rocks and adjacent reservoirs is regarded as the fifth type of driving force for hydrocarbon expulsion from source rocks (Berg 1975), and is expressed as F9. Capillary forces in tight formations have been considered a resistance to hydrocarbon migration for a long time (Pittman 1992). However, the capillary pressure difference (CPD) in formations

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is realized as driving force for oil and gas migration, and its contribution remain controversial (Stainforth et al. 1990). Most studies believe the effect of CPD on hydrocarbon migration and accumulation is very limited and should be neglected due to its small value. Some believe the CPD plays a very important role, but limited to certain geological period in the evolution of source rocks when massive hydrocarbons generated and organic networks formed in a source rock (McAulife et al. 1979). The contribution is also thought to be confined in reservoirs with highly uneven pore structure characteristics, where the oil and gas are constantly adjusted from small capillary pores to larger pores, leading to a gradual enrichment of oil and gas (Jiang et al. 2017).

8.2.2 Workflow of Multi-forces Evaluation Basis on the above research, relevant technologies, and workflow of dynamics for hydrocarbon migration and accumulation are divided into 5 parts (Fig. 8.5). The first step is to investigate the characteristics of oil/gas deep and tight reservoirs in China and abroad, analyze the geological characteristics of deep tight oil/gas reservoirs and classify them. The second step is to perform statistical analysis of deep and tight reservoirs, and applied statistical analysis method to determine the dominant factors affecting the drilling results of exploration wells. The third step is to conduct physical modeling experiment to reveal mechanisms related to the major driving forces. The fourth step is to conduct numerical simulation to quantify contributions of each driving force. The fifth step is to establish the quantitative relationship between the oil/gas enrichment degree and the major factors such as the dominant driving forces, the burial depth, and others.

Fig. 8.5 The content and workflow of this study

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8.3 Evaluating Contributions of Driving Forces by Statistics 8.3.1 Data Sources and Research Principle Our statistical analysis of drilling results from 67,944 reservoirs of 2938 exploration wells in the Bohai Bay Basin of China confirmed Capillary Pressure Difference (CPD) as major driving force for oil and gas expulsion from source rocks and accumulation in deep tight reservoir layers. Capillary pressure (Pc) is the resistance to oil/gas migration, but the CPD between surrounding source rocks and the reservoir layers is essential driving force, and could be expressed as CPD = Pcs – Pcr , Pcs refers to capillary pressure in surrounding source rocks, and Pcr presents capillary pressure in reservoir layers. Theoretically, the critical condition for CPD driving oil/gas out of source rocks and into reservoir layers is the value of CPD exceeds the capillary resistance encountered in reservoir layers (Pcr ), which means the critical capillary pressure in surrounding source rock should be equal to or larger than twice of the capillary pressure in reservoir layer as Eq. 8.1: PC S ≥ 2 × PCr

(8.1)

Here, the CPD is driving force (F), and capillary pressure (f*) in reservoir layers is the critical resistance, their difference is defined as Effective Capillary Pressure Difference (ECPD), expressed as Eq. 8.2: EC P D = F − f ∗ > 0

(8.2)

It is the ECPD that drive oil/gas out of source rocks and into reservoir layers. The relationship between ECPD and oil/gas accumulations was confirmed by statistical analysis in this study, and the results provide geological model for physical modelling of oil/gas expulsion from source rocks and accumulation in connected reservoir layers.

8.3.2 Results and Analysis Statistical analysis results are illustrated in Fig. 8.6 by the relation of oil/gas drilling results to the ECPD and Capillary Pressure Ratio of CPR = Pcs /Pcr . Similar to ECPD, the Effective Capillary Pressure Ratio Difference (ECPRD) is defined as the difference between CPR and the critical capillary pressure ratio (CPR*), expressed as Eq. 8.3: EC P D = C P R − C P R ∗

(8.3)

8.3 Evaluating Contributions of Driving Forces by Statistics

247

Fig. 8.6 The relationship between the effective capillary pressure (ratio) difference and oil/gas accumulation in the tertiary formation in the Nanpu Sag of the Bohai Bay Basin with increasing depth. a Variations of interval travel time in shale rocks and in sandstone reservoir layers. b Variations of CPR, ECPRD and oil/gas accumulations. c Variations of ECPD and oil/gas accumulation. d Correlation of ECPD and oil/gas saturation

Figure 8.6a shows the variation of interval travel times in pure shale rocks and in pure sandstone layers at different depths, implying that the density, porosity and pore throat radius of mudstone and sandstone are different at different depths. Figure 8.6b illustrates the relation of CPR and the oil/gas accumulation as well as their variation with increasing depth, implying that oil/gas only accumulated in effective reservoirs with CPR greater than CPR* (blue line) and majorly distributed in the depth range of 250–6500 m. Within this range, the larger the ECPRD is, the more the oil/gas reservoirs and reserves are formed and proved. Figure 8.6c directly shows the relationship of oil/gas accumulation and ECPD with increasing depth, the larger the ECPD, the higher the saturation of oil/gas in reservoirs, the most favorable depth for the formation and distribution of oil/gas reservoirs is from 1500 to 4500 m with largest values of the ECPD and enrichment degree. Figure 8.6d shows the relation of oil/gas saturation and ECPD, oil/gas saturation increase with increasing the value of ECPD. The relationship of oil/gas accumulation and ECPD presents a three-stage change: The oil/gas accumulation and the value of ECPD in shallow layers with depth < 1000 m increase with increasing depth; They reach their maximum values in the meantime in the depth range of 1000–4500 m; Both of them decrease with increasing depth if beyond 4500 m, implying the ECPD is the essential and only major driving force for oil/gas migration from source rocks and accumulation in the nearby deep and tight reservoir layers because all other driving forces tend to be disappearing in this stage.

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

8.4 Evaluation Contributions of Driving Forces by Simulation 8.4.1 Principle Previous studies have proved that every each of the 5 categories and 9 driving forces can lead to hydrocarbon expulsion from source rocks, but none of them can fully explain the various complicated phenomena in the process, implying that 5 types and 9 driving forces all simultaneously exist but make different contributions at different stages. Based on the principle of material balance, the relative contributions of 9 forces are conducted by numerical simulation following five steps (Fig. 8.7). The first step is to study the evolution history of petroliferous basins and simulate the hydrocarbon generation, retention, and expulsion from source rocks (Peng et al. 2016). The second step is to estimate hydrocarbon expulsion amounts of four different phase states from source rocks and their changing histories (Johnson 1912). The oil/gas amounts (Qe ) expelled from source rocks in water-soluble phase (Qew ), in diffusion phase (Qed ) (Leythaeuser et al. 1982; Thomas and Clouse 1990), in oilsoluble phase (Qeog ) (Neglia 1979) and in free separated phase (Qes ) (Dickey 1975) are studied and simulated, respectively.

Fig. 8.7 Technologies for evaluating contributions of 9 driving forces to oil/gas expulsion from source rocks and the workflow. F1 is the diffusion force for hydrocarbons expulsion from source rocks. F2–F5 are the thermal expansion forces of mineral skeleton, water, liquid oil and nature gas. F6 is compaction stress from overlying strata. F7 and F8 are pressures from increasing fluid volumes caused by clay dehydrate and kerogen transformation to oil/gas. F9 is capillary pressure difference between surrounding rock to reservoir layer. ΔQf 2 ~ ΔQf 8 are fluid volumes expelled by the driving force 2–8. Qef 1 ~ Qef 9 are the oil/gas amounts expelled by driving force 1–9. Kj is the relative contributions of each driving force Fj, j = 1, 2, …, 9

8.4 Evaluation Contributions of Driving Forces by Simulation

249

The third step is to study oil/gas expulsion mechanisms by 9 driving forces and calculate the fluid volume (ΔQf , f = 1, 2, …, 9) expelled from source rocks by each driving force. The fourth step is to calculate the hydrocarbon amount (Qef , f = 1, 2, …, 9) expelled by 9 driving forces according to their expelled fluids volume, their relationship to oil/gas amounts expelled in 4 different phases. The expelled hydrocarbon amount in diffusion (Qed ) only related to F1, and those in water solution (Qew ) associated with F2–F8. The amount in oil-solution (Qeo ) and in free separate (Qes ) are together contributed by F2–F9. The total expelled hydrocarbon quantity (Qef ) by all driving forces is the sum of oil/gas amount expelled in four different phases, which could be denoted as Qef = Qedf + Qewf + Qeof + Qesf , f = 1, 2, 3, …, 9. The fifth step is to evaluate the relative contribution (K f ) of each driving force (f) to all oil/gas amount expelled from source certain ∑ rocks in different phases during a∑ depth interval, denoted as K f = Qef / (Qeif ), f = 1, 2, … 9. The value of (Qei ) refers to the sum of cumulative hydrocarbon amount expelled by 9 driving forces in 4 phases. The variations in Qef and K f with increasing burial depth of source rocks calculated in 250 m depth intervals during its burial.

8.4.2 Simulation for Hydrocarbon Expulsion from Source Rocks in Different Phases (1) Characterization of hydrocarbon expulsion. Numerical simulation method about hydrocarbon expulsion in 4 different phases from source rock, such as in water solution, oil-solution, diffusion and free phases, is based on the principle of material balance. First, the amounts of total hydrocarbons generated by organic matter in source rocks (Qp ) and retained in the source rock (Qr ) are calculated. Then, the amount of total hydrocarbons expelled from source rocks (Qe ) is acquired by subtracting the Qr from the Qp . After that, considering the relevant geological parameters, including solubility of oil/gas in water, diffusion coefficient of oil/gas in water, adsorption coefficient of oil/as on rock surface, the amounts of hydrocarbons expelled in each of the four phases are calculated, i.e. the amounts of the water-solution, diffusion, oil-solution, and free phase. Finally, combining the burial history and thermal evolution of source rock strata, other geological parameters are calculated, such as the potential, velocity, rate, and efficiency of hydrocarbon expulsion. The numerical simulation is based on the recovery of the burial history and thermal evolution of source rock, methods of which can be found in previous studies (Lerche 1990; Pang et al. 1993, 2003). The generated hydrocarbon amount (Qp ) from per cubic meter of source rock is related to organic matter content (TOC), Kerogen Type Index (KTI), thermal evolution degree (Ro) or buried depth (Z) and density (D) of source rocks, expressed in the Eq. 8.4.

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Q P = R P (R O , K T I ) · D(z) ·

TOC(R O ,K T I ) 100

(8.4)

where, the Qp is the total hydrocarbon amount generated from per cubic meter of source rock, in kg/m3 for oil or m3 /m3 for gas; Rp (Ro , KTI) refers to the hydrocarbon amount generated by per unit weight of organic matter measured currently, in kg/Ttoc or m3 /Tc , varying with Kerogen Type Index (KTI) (Lu et al. 2012) and thermal maturity degree of vitrinite reflectance of organic matter (Ro ). The quantitative relationship among them has been already established (Tissot et al. 1978; Hunt 1979; Peters et al. 1994). D(Z) is the density of source rock in ton/m3 , varying with increasing burial depth (Z) due to the compaction (Magara et al. 1981). TOC is the original total organic carbon content in weight percentage (wt, %), changing with Ro and KTI due to its transformation to oil/gas and oil/gas expulsion (Li et al. 2016). The generated hydrocarbon components are divided into three groups, liquid oil (Cn , n ≥ 6), heavy hydrocarbon gas (C2~5 ), and methane gas (C1 ). The calculation of remaining hydrocarbon amount in source rock are as follows Based on the statistical analysis of pyrolysis data “S1 ” or the hydrocarbon amount data “A” extracted from the source rock core by chloroform solvent (Behar et al. 2001), the quantitative relationship between the retained liquid hydrocarbon amount in the source rock and its major factors are established. The lost light hydrocarbons (C6~15 ) when the drilling core was taken from underground to surface and placed in the core reservoir for a long time are compensated (Chen et al. 2018). The final calculation model is corrected by compensation and calibrated by actual samples, and expressed as Eq. 8.5. Q r o = ρo · (ϕn + Δϕ) · (A0 + A1 · (T OC) + A2 · (T OC)) ·

ϕn 1 ' 2 e− D ( R O −R ) 1 − Bk

(8.5)

where, Qro refers to the total hydrocarbon amount remaining in per cubic meter of source rock, kg/m3 or m3 /km3 ; Fn is the porosity of source rock with normal compaction in %; ΔF is the extra porosity of source rock with abnormal compaction, %. Ro refers to the critical vitrinite reflectance corresponding to maximum value of residual hydrocarbon peak in %. ρo means the crude oil density in t/m3 . A0 , A1 , A2 , and D is constant value, which are determined by statistical analysis with the best fitness between the actual data “S 1 ” or “A” with calculation model in the study area. The Bk is the factor of light hydrocarbon compensation, the ratio of lost to residual light hydrocarbons, quantitatively related to major factors established before (Pang et al. 1993). The total residual gas amount in source rock is calculated by Eq. 8.6. Q rg = (Q rgb + Q rgo + Q rgw )

(8.6)

where, Qrg is the total hydrocarbon amount remaining in per cubic meter of source rock, kg/m3 or m3 /km3 . Including the adsorbed gas amount of Qrgb in per cubic meter of source rock (Qu et al. 2020), oil-dissolved gas amount of Qrgo in per cubic meter

8.4 Evaluation Contributions of Driving Forces by Simulation

251

of source rock, water-dissolved gas amount of Qrgw in per cubic meter of source rock (Li et al. 2018). In this study, the relative parameters such as rock adsorption coefficient, oil solution coefficient, and water solution coefficient are obtained from previous works, and the retained hydrocarbon components also are divided into the same three groups as liquid oil, heavy gas, and methane. Based on above, the expelled hydrocarbon amount from source rock in different phases can be calculated using Eq. 8.7. Q e = Re (R O , K T I ) · D(z) ·

TOC(R O ,K T I ) 100

(8.7)

where, the Qe is the total hydrocarbon amount expelled from per cubic meter of source rock, kg/m3 for oil or m3 /m3 for gas. The Re (Ro , KTI) is the hydrocarbon amount expelled by per unit weight of organic matter measured currently, kg/T toc or m3 /Tc, changing with KTI and Ro . Quantitative relationships among them have been already established (Pang et al. 2005; Jiang et al. 2016). The Hydrocarbon Expulsion Threshold (HET) of the source rock can be determined by the Eq. 8.8, which corresponds to the critical conditions where the generated hydrocarbon amount (Qp ) is equal to the residual hydrocarbon amount (Qrm ). Hydrocarbon amount expelled from source rock as 4 different phases can be calculated by Eqs. 8.9–8.12. Q P ≥ Q r m = Q r o + Q rg Q ew = Vw ·

4 ∑

qw (i )

(8.8)

(8.9)

1

Q ed =

4 ∑

t

∫ D(i, T, Φ) ·

1 0

Q eg = Q eo ·

4 ∑

dc dz

· dt

qo (i )

(8.10)

(8.11)

1

Q es = Q e − Q ew − Q ed − Q eog

(8.12)

where, Q ew is the hydrocarbon amount expelled as water-solution, kg/km2 or m3 / km2 , changing with the water volume expelled from source rock (V ew ), hydrocarbon component (i) and hydrocarbon solubility in water (qew ). The qew value is controlled by oil/gas component (i), temperature (T ), pressure (P) and water mineralization (X k ), and their relationships can be confirmed (Price et al. 1976). Qed refers to the hydrocarbon amount expelled as diffusion phase, kg/km2 or m3 /km2 , changing with source rock distribution areas (S), diffusion period time (t), and inside hydrocarbon composition (i), concentration gradient (dc/dz), and diffusion coefficient D (i, T, F). Relationships of diffusion coefficient with hydrocarbon components (i), temperature (T ) and medium porosity (F) are determined (Leythaeuser et al. 1982). Qeog means the gas amount expelled from source rocks as oil-solution phase, kg/km2 or m3 /km2 ,

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

changing with the expelled oil amount (Qpo ~ Qro ) and the solubility of gas in the oil (qo ). The relationships of qo and gas component (i), temperature (T ), pressure (P), oil density (ρo ) were determined by Bruce (1984). Qes is the hydrocarbon amount expelled as free phase, kg/km2 or m3 /km2 , changing with total hydrocarbon amount expelled from the source rock (Qp − Qrm ), the hydrocarbon expulsion amount as 3 phases, such as Qew , Qed , Qeog . The hydrocarbons amount expelled from the source rock as free phase is the most significant for oil/gas accumulation (Magara et al. 1978). The characteristics of hydrocarbon expulsion from source rock during its evolution can also be analyzed. These characteristics can be expressed as parameters including the velocity (V e ), rate (S e ), efficiency (Re ) of hydrocarbon expulsion and the source rock index (SRI). Their simulation calculations assume instantaneous hydrocarbon expulsion from source rock. Firstly, all features of source rock, such as the burial depth, temperature, thickness, and porosity are restored to a normal state at surface. Secondly, they are recovered to the corresponding depth with fixed intervals (ΔZ = 100 m) to calculate the total hydrocarbon amount expelled from the source rock (ΔQe ) and the four kinds of hydrocarbon ∑ amount (ΔQei ) expelled as four phases. For any different depth interval, ΔQe = ΔQei , i = 4. Then, the key parameters for hydrocarbon expulsion in different depth intervals are calculated by the Eqs. 8.13– 8.16. Vw =

ΔQ e ΔZ

Se =

(8.13)

ΔQ e H

(8.14)

Qe QP

(8.15)

Re = SRI =

× 100

Q es Qe

× 100

(8.16)

where, V e is the hydrocarbon expulsion velocity or hydrocarbon amount expelled by per square meter of the source rock, changing with ΔQe and depth. S e is the hydrocarbon expulsion rate, the hydrocarbon amount expelled from per cubic meter of source rock, changing with V e and the thickness of source rock (H). Re is the hydrocarbon expulsion efficiency or the percentage of the accumulative hydrocarbon amount (Qe ) expelled from the source rock to the total generated hydrocarbon amount (Qp ), changing with different depth of the source rock. SRI is source rock index, changing with the total oil/gas amount expelled from source rock as separated phase (Qes ) and the total oil/gas amount expelled in different phases (Qe ). The larger the SRI value is, the greater the contribution of source rock to oil/gas reservoirs formation will be. (2) Geological setting and geochemical data. The Tarim Basin is rich in deep-seated oil and gas resources. The oil and gas are mainly concentrated in the Paleozoic Marine

8.4 Evaluation Contributions of Driving Forces by Simulation

253

strata. The lithology of the target strata is mainly carbonate rocks, including limestone and dolomite. The maximum burial depth of the oil and gas reservoirs proved so far is more than 8800 m, and their formation and distribution are mainly related to fault zones, unconformities, and reconstructed reservoirs (Fig. 8.8). These oil and gas reservoirs are mainly reformed as the unconventional tight oil and gas reservoirs distributed above and below the source rocks or inside the source rocks after structural changes and reconstruction. The oil and gas from damaged reservoirs migrate again under the dominance of buoyancy, forming fractured oil and gas reservoirs or unconformity related reservoirs in traps. Therefore, it is of great practical significance to understand the formation mechanism and distribution law of deep reformed reservoirs by studying the process characteristics of oil and gas migrating from deep source rocks into surrounding tight reservoirs driven by various non-buoyancy forces. The Paleozoic Middle-Lower Cambrian and Middle-Upper Ordovician source rocks are realized as the main source rocks in the deep area of Tarim Basin (Li et al. 2010, 2015). During this study, the Cambrian source rocks was selected as a case. The source rocks are mainly developed marine carbonate rocks and mudstones. From the perspective of the thickness distribution of the source rock, the Cambrian source rock has a wide distribution range and is distributed throughout the basin, with a maximum thickness of up to 450 m, and mainly developed Type I and part of Type II kerogen. The Cambrian strata are deeply buried and have high thermal evolution maturity, the equivalent vitrinite reflectance data indicate that the source rock organic matter is currently in an over-mature stage, with Ro between 2.00 and 4.00%. The main distribution range of Cambrian source rock TOC ranges from 1.20 to 3.30%, up to 7.60%, indicating it is a set of high-quality source rocks.

Fig. 8.8 Distribution characteristics of Paleozoic Marine crude oil and its correlation to Ordovician and Cambrian source rocks in the Tazhong Uplift, Tarim Basin. a Plane distribution characteristics of oil and gas reservoirs, b the oil and gas reservoirs section along the northwest to southeast; c statistical results of geological and geochemical characteristics of Cambrian and Ordovician Marine source rocks

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

The driving forces for hydrocarbon expulsion and their relative contributions for the Cambrian source rocks are simulated. The simulations have related to a lot of geological parameters 5 of which are essential such as the source rock thickness (H), organic parent material abundance (TOC), parent material type (KTI), thermal evolution degree (Ro) or burial depth (Z) and the age of source rocks. Their variation characteristics are illustrated in Fig. 8.8. Under the given geological conditions, H changes at range of 0–450 m with an average of about 200 m; TOC changes from < 0.2 to > 3.3% with an average of 1.5%; KTI from 50 to 100 with an average of 85; equivalent Ro from 0.8 to 4.1% with an average of 1.8% and the age of source rock change from 520 to 585 Ma with an average of 555 Ma. The Monte Carlo simulation technique is applied to obtain different results and their probabilities distribution corresponding to these varying parameters. (3) Hydrocarbon expulsion in 4 phases from source rocks. Figure 8.9 illustrates a case study results of hydrocarbon expulsion from source rocks of the Tarim Basin in four different phases. Figure 8.9a shows the variation characteristics of hydrocarbon generation, retention, and expulsion with increasing depth for methane (A1), heavy gas (A2), liquid hydrocarbons (A3), and SRI (A4), clarifying the relationship of the generated, retained and expelled oil/gas amounts in a cubic meter of source rocks during its evolution. Figure 8.9b shows the variation characteristics of the hydrocarbon expulsion by a cubic meter of source rocks along with increasing depth. Oil/gas expulsion is characterized by 4 parameters, including the accumulatively expelled hydrocarbon amount (B1), the hydrocarbon expulsion velocity (B2), hydrocarbon expulsion rate during increased 100 m depth interval (B3) and the oil/ gas expulsion efficiency (B4). Figure 8.9c shows the variation of relative hydrocarbons amounts (%) from source rocks expelled in 4 phases during the same depth interval, including the methane gas, heavy hydrocarbon gas and liquid hydrocarbon.

8.4.3 Simulation of Relative Contributions for 9 Driving Forces to Oil/Gas Expulsion (1) Characterization of 9 driving forces and relative contribution to oil/gas expulsion. The amount of hydrocarbon expelled by driving force F1 is equal to the expelled hydrocarbons in diffusion phase (Qed ). The hydrocarbon amount expelled from source rock in water solution phase (Qew ) is controlled by the combination of seven type driving forces (Fi, i = 2–8). Contribution of each driving forces are related to fluids volume expelled from source rock by them. While the oil/gas amount expelled in oil-solution phase (Qeog ) and the oil/gas amount expelled in free phase (Qes ) are also related to these seven driving forces (Fi, i = 2–8) together with CPD (F9). According to corresponding relationships among these driving forces and oil/ gas amounts expelled in different phases, the hydrocarbons amount expelled from source rock by each nine driving forces can be calculated. The value of hydrocarbon

8.4 Evaluation Contributions of Driving Forces by Simulation

255

Fig. 8.9 A case study of numerical simulation results on hydrocarbon generation, retention, and expulsion in 4 different phases for source rock in the Tarim Basin with essential parameters of TOC = 0.5%, KTI = 85, Ro = 1.36%, H = 300 m, GT = 2.5 °C/100 m. a Variation of hydrocarbon generation, retention and expulsion by a cubic meter of source rock with increasing depth for methane (a1), heavy hydrocarbon gas (a2), liquid (a3) and source rock index (SRI). b Variation of hydrocarbon expulsion characteristics, including hydrocarbon expulsion amount (b1), hydrocarbon expulsion velocity rate (b2), hydrocarbon expulsion rate (b3), hydrocarbon expulsion efficiency (b4). c Variations of relative oil/gas amounts expelled in 4 different phases from source rocks, including methane (c1), heavy gas (c2), liquid (c3). The W, D, O and F are the relative amounts of hydrocarbons expelled from source rocks in water-solution, diffusion, oil-solution, and free phase, respectively

amount expelled from source rock can show the relative contributions of each driving forces for hydrocarbon accumulations in tight reservoirs. Calculation of liquid fluid volume expelled from source rocks by 7 driving forces can be conducted as follows. Volumes of fluid expelled by each of the 7 driving forces are denoted as the ΔV fi , i = 1, 2, …, 8. The fluid volume (ΔV f2 ) expelled by F2 from stage 1 to stage 2 is calculated by Eq. 8.17.

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

  V f 2 = K sr2 − K sr1 · (1 − Φ0 )

(8.17)

where, Ksr is related to the expansion coefficient of the skeleton content (1 − F0 ) at stage 1 and stage2 (David et al. 1997). The fluid volume (ΔV f3 ) related to F3 from stage 1 to stage 2 is calculated by Eq. 8.18, which is related to the change of source rock porosity (F) and the change of water expansion coefficient (K hw ) (Barker 1984). Volume of fluids (ΔV f4 ) driven by F4 is calculated by the Eq. 8.19, which is related to the variation of the source rock porosity (F), the oil expansion coefficient (K ho ) and oil saturation (So) in source rocks (Magara 1976). ΔV f5 is calculated by the Eq. 8.20, relating to the variation of the source rock porosity (F) and the gas expansion coefficient (K hg ) (Magara 1976). ΔV f6 is calculated by the Eq. 8.21, which is related to the change of porosity (F), thickness (H) (Lee et al. 2018). ΔV f7 is calculated by the Eq. 8.22, which is related to TOC, density of source rock (D) and the volume increase coefficient (K v ) (Vernik et al. 1996). ΔV f8 related to F8 is calculated by the Eq. 8.23, associated with the total content of clay minerals (C lay ) and secondary illites (I m ) formed by clay diagenesis and volume increase coefficient (0.245) (England 1987).    0− ϕ2 V f 3 = K hw2 − K hw1 · ϕ1−ϕ − 2

ϕ0− ϕ1 1−ϕ1

  0− ϕ2  V f 4 = K ho2 − K ho1 · ϕ1−ϕ − 2

ϕ0− ϕ1 1−ϕ1

  0− ϕ2  V f 5 = K hg2 − K hg1 · ϕ1−ϕ − 2

ϕ0− ϕ1 1−ϕ1

Vf6 =



ϕ0− ϕ2 1−ϕ2

−

ϕ0− ϕ1 1−ϕ1



 

 (8.18)

· SO

(8.19)

· SG

(8.20)

·H

(8.21)

V f 7 = (D1 − D2 ) · (T OC2 − T OC1 ) · K v

(8.22)

  V f 8 = 0.245 · Clay2 − Clay1 · (Im2 − Im1 ) · (D1 − D2 )

(8.23)

The inverse calculation of driving forces for fluids expulsion from source rock follows the improved Darcy’s law (Germann 2018), using the Eq. 8.24. The fluid viscosity (μi) is replaced by water viscosity because the water volume is the highest among the expelled fluid volume, accounting for 70% (Zheng et al. 2020).  Fi = d Vi · μw ·

H dkw ·dt



× 1012 (i = 2, 3, . . . , 8)

(8.24)

The ninth driving force (F9) is calculated by Eqs. 8.25 and 8.26. F9o = PcW/O = 2 · δW/O · cos θ ·

1 r

−

1 R



(8.25)

8.4 Evaluation Contributions of Driving Forces by Simulation

F9g = Pc WG = 2 · δ WG · cos θ ·

257

1 r

−

1 R



(8.26)

where, Pc refers to the capillary pressure in source rock. r refers to the throat radius of surrounding rocks. R refers to the throat radius of reservoirs. θ refers to the wetting angle of hydrocarbon/water. The value of θ is set as 0 in calculation, and the capillary pressures for oil (F 9o ) and for gas (F 9g ) in rocks are calculated separately, as denoted in the Eqs. 8.25 and 8.26. The oil/gas amount expelled from source rock by the 9 driving forces can be sequentially calculated. The hydrocarbon amount of Qed is contributed by F1 , denoted as Qe1 , which is calculated by Eq. 8.27, changing with diffusion coefficient (D), hydrocarbon concentration gradient (dc/dz), diffusion area (S), porosity of source rock (ϕ) and diffusion period (t). The oil/gas amount (Qei ) expelled by each of other 8 driving forces is calculated ∑ by Eq. 8.28. Related oil/gas amount (Qew ) are expelled by the combination of Fi, i = 2, 3, … 8, ∑ and the oil/gas amount of Qeog and Qes which is contributed by the combination of Fi, i = 2, 3, … 9. Q el = D · Q ei =

Q es +Q eog Fi

+

·

dC dZ

Q ew j Fj (

1−ϕ0 1−ϕ2

· s · ϕ2 · Δt

= 2, 3, . . . , 8; i = 2, 3, . . . , 9)

(8.27) (8.28)

Finally, the relative contributions by each of the 9 driving forces are obtained by the ratio of the hydrocarbon amount by each driving forces to total hydrocarbon amount by 9 driving forces, expressed by the Eq. 8.29. Ri =

Q ∑9 ei i=l Q ei

(i = 2, 3, . . . , 8)

(8.29)

Geological parameters used in the above equations are obtained from experiments, previous works and actual data collected in the study area. These parameters include rock heat expansion coefficient (Magara et al. 1975b), hydrocarbon heat expansion coefficient (Magara 1975a), hydrocarbon diffusion coefficient (Leythaeuser 1987), natural gas adsorption coefficient (Danial et al. 2007), hydrocarbon dissolution coefficient in water (Price, 1976), dissolution coefficient of gas in oil (Neglia et al. 1979), volume expansion coefficient of kerogen products (Espitalie et al. 1980), and clay minerals dehydration (Dickinson et al. 1966). (2) Simulation results and relative of 9 driving forces to oil/gas expulsion. Figure 8.10 illustrates the variation characteristics of total water, natural gas (methane and heavy HC gas) and liquid oil expelled by a cubic meter of source rock by 9 driving forces with increasing depth. Figure 8.10a shows the variation characteristics of expelled water amount, expressed in instantaneously amount in 100 m depth interval burial (a1), relative amount (a2) and cumulative amount (a3). Figure 8.10b show the variation characteristics of expelled gas amount, expressed in instantaneously amount in 100 m depth interval burial (b1), relative amount (b2) and cumulative amount (b3). Figure 8.10c shows the variation characteristics of expelled liquid oil

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8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

amount characterized by instantaneous amount (c1), relative amount (c2) and cumulative amount (c3). The total expelled water amount from source rocks is mainly related to compaction (50%), clay dehydrate (35%), kerogen transformation (6%) and the thermal expansion of rock skeleton and fluids (9%). The compaction (F6) makes the largest contribution to water expulsion, while, the CPD makes the largest contribution to expelled gas amount with > 80%, and then they are the diffusion with 5%, the clay and Kerogen transformation with 5%, compaction (4%) and the thermal expansion of rock skeleton and fluids (< 5%), the contributions of 9 driving forces to expelled oil amount are almost the same to expelled gas amount, mainly controlled by CPD (> 85%), compaction (7%), clay and kerogen transformation (5%) and the thermal expansion of rock skeleton and fluids (< 3%). As showed by a large number of simulation results with varies of geological parameters, the CPD contributes more than 50% to the total expelled oil/gas amount with TOC > 0.5% and Ro > 0.5%, its relative contribution increases with increasing depth, implying a dominant role in the formation and distribution of deep and tight oil/gas reservoirs. (3) Variation of relative contribution for 9 driving forces to oil/gas expulsion with increasing depth. Dynamic process for hydrocarbon expulsion from source rocks is divided into 4 stages with increasing depth, showing that different forces driving hydrocarbons with different phase to expel from source rocks at different stages, and make different contributions for oil and gas accumulations in deep and tight reservoir layers (Fig. 8.11). The first stage is from deposition of source rocks at surface to the hydrocarbon expulsion threshold (HET) in free phase from source rocks in the underground, dominating by compaction of overburden strata. Most of oil/gas were expelled in water-solution and diffusion phases, and the relative contributions of compaction (F6), diffusion (F9), thermal expansion (F2–F5) and products volume expansion (F7–F8) is about 40, 25, 20, and 15%. It is unfavorable for oil/gas migration and accumulation in reservoir layer because the generated oil/gas amount was not sufficient to satisfy the retention of oil and gas in source rocks and oil/gas could not be expelled massively in free phase. The accumulative expelled oil/gas amount in this stage is less than 10% of total amount majorly for the low solubility of oil/gas in water, small diffusion coefficient of oil/gas through rocks, and very limit oil and gas amount generated by source rock. The second stage is from HET to the liquid hydrocarbon expulsion depth (LHED), both oil and gas were expelled from source rocks in 4 different phase states. Most of them (65–85%) were expelled in free phase with some gas migrating in oil-solution, dominated by multi-driving forces such as the CPD, thermal volume expansion, products volume expansion, and others. Their relative contributions to oil/gas expulsion are 40, 30, 20, and 10%. The source rock distribution area with the development of sapropel-type organic parent material is conducive to the formation of pure oil reservoirs in which natural gas is dissolved. The source rock distribution area with the development of humic-type organic parent material is favorable for the formation of pure gas reservoir. The distribution of source rocks with transitional-type organic parent material is favorable for the formation of oil and gas reservoirs.

8.4 Evaluation Contributions of Driving Forces by Simulation

259

Fig. 8.10 Numerical simulation results on fluids expulsion of water, oil and gas by 9 driving forces from source rocks and their relative contributions with increasing burial depth. a Variation characteristics of expelled water amount from source rock, including its instantaneous amount (a1), relative amount (a2), and accumulative amount (a3). b Variation characteristics of expelled gas amount, including instantaneous amount (b1), relative amount (b2), and accumulative amount (b3). c Variation characteristics of expelled oil amount, including instantaneous amount (c1), relative amount (c2), and accumulative amount (c3). F1 is the diffusion of hydrocarbons. F2–F5 are the thermal volume expansion of mineral skeleton, water, liquid oil, and nature gas. F6 is compaction by overlying strata. F7–F8 are the products volume expansion induced by clays dehydration and kerogen transforming to oil/gas. F9 is capillary pressure difference

The third stage begin with source rocks entering LHED and lasted to the active source rock depth limit (ASDL), which indicates the end of hydrocarbon generation and expulsion (Pang et al. 2020). All the gas with little liquid oil are expelled from source rocks in free phase. More than 50% of natural gas was expelled in this stage by the CPD, and the relative hydrocarbons amount expelled in diffusion, by thermal volume expansion of rocks and fluids and by compaction of overlying strata are less than 5%, 10%, and 15%, respectively.

260

8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Fig. 8.11 Dynamic model of hydrocarbon expulsion in 4 phase states from source rock and the stage division by the variation characteristics of driving forces’ contributions with increasing depth

In summary, the CPD is the most important driving force for hydrocarbons expulsion from effective source rocks. Its relative contribution is more than 50% for sandstone reservoir layers with porosity < 10 ± 2%, and increases with increasing depth. While, the other 8 driving forces are important for hydrocarbon expulsion but limited by the evolution stage of source rocks and phase states of hydrocarbons in expulsion. Their total contributions to hydrocarbon expulsion are less than 50% and show decreasing trend with increasing depth. These imply that the deeper of source rocks, the more important of CPD for tight hydrocarbon reservoirs accumulation.

8.5 Confirming Contribution of the CPD by Physical Experiments 8.5.1 Principle and Conditions A physical modeling experiment was performed to reveal the dynamic mechanism of oil and gas expulsion and accumulation driven by ECPD. The source rock was represented by an oil-saturated sands body with fine particle size (d) of silica grains, and the reservoir layer was represented by a water-saturated sands body with large particle size (D) of silica grains. In order to eliminate the influence of other forces, the water-saturated sands body was surrounded by oil-saturated sands body. The experiment was performed in a transparent glass box for the ease of observation. The D value was set as a constant, while the d value was varied to adjust the ratio of D/ d, which changed the ECPD. Four sets of experiments were carried out with four different D values (0.1, 0.25, 0.5 and 1.0 mm). In each set, the D/d values were set to 0.5, 1, 1.5, 2, 4, 6, 8, and 10. The surrounding sands body was filled with colored oil before experiment, and the status of oil migrating and accumulating in reservoir

8.5 Confirming Contribution of the CPD by Physical Experiments

261

sands body were recorded every 2 h since the experiment began. The experiments were considered as finished when the oil saturation in the reservoir sands body D showing no visible color change.

8.5.2 Results and Analysis Figure 8.12 illustrates the experiment results of one set with D = 0.5 mm. Figure 8.12a illustrates the variations of oil saturation in each sands body for the 4 groups of experiment at three different times (0, 39, and 72 h) with D = 0.5 mm and D/d = 10/ 1, 8/1, 6/1 and 4/1 in group (a), (b), (c) and (d), respectively. At the initial time (0 h), no oil migrated and accumulated in the reservoir body. After 39 h, all 4 sands bodies are filled with oil, but the oil saturations in them are different. The sands bodies with larger D/d values are darker, indicating higher oil saturation. After 72 h, the color of 4 sands bodies become much deeper, indicating much more oil accumulated in them. Figure 8.12b illustrates the variations of oil saturation in each sands body for another 4 groups of experiment at three different times (0, 39, and 72 h) with D = 0.5 mm and D/d = 2, 1, 1/2 and 1/4 in the group (a), (b), (c) and (d), respectively. At initial time (0 h), no oil migrated and accumulated in the reservoir bodies. After 39 h, three sands bodies (b, c and d) are not filled with oil but one of them (a) with D/d = 2 is filled with a little few oil. After 72 h, the color of these 4 sands bodies remains almost the same. Figure 8.12c, d compare all results from the four sets of physical modelling experiments, which clarified the following three basic issues.

Fig. 8.12 Physical modeling results of oil migration and accumulations in different sand bodies driven by ECPD. a Variations of oil saturations in 4 sand bodies at three different times (0 h at initial-A1, 39 h later-A2, and 72 h later-A3) with the particle size of D = 0.5 mm and D/d = 10, 8, 6, 4 in the group (a), (b), (c) and (d), respectively. b Variations of oil saturation in 4 sand bodies at three different times (0 h at initial-B1, 39 h later-B2, and 72 h later-B3) with D = 0.5 mm and D/ d = 2, 1, 1/2, 1/4 in group (a), (b), (c) and (d), respectively. c Relationship between oil saturation in D and ratios of D/d in all the 4 sets of experiments, with D = 0.1, 0.25, 0.50 and 1.0 mm and different D/d values under the same experiment conditions. d Relationship between the ECPD and oil saturation at constant D

262

8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Firstly, CPD can drive oil migrating from source rock to accumulate in nearby reservoir layer if the CPD is large enough. Each group results clearly show that oil can migrate from the surrounding finer sands body into the coarser sands body driven by ECPD. Capillary pressure in the reservoir is the resistance to oil migration, but the ECPD is the essential driving force for oil migration and accumulation if the ECPD is larger than 0. The details of the results of the physical modelling experiments are in relevant literature (Pang et al. 2013). Secondly, the minimal critical value of CPD* is needed to drive oil out of source sands body and into reservoir sands body. The minimal critical value of driving force corresponds to the particle size ratio of D/d ≈ 2, which is consistent with theoretical calculation result that oil migration will takes place only when the capillary pressure in the surrounding rocks exceeds twice of that in reservoir layers, also consistent with the statistical analysis results of the drilling data that the CPD can drive oil out of source rocks and into nearby reservoir layers if the CPR of Pcn /Pcs is equal to or larger than 2 at ground surface (Fig. 8.12b). Thirdly, larger ECPD leads to higher saturation of oil in reservoir sands body. Figure 8.12c illustrates the controlling of D/d on oil migration and accumulation. When D is constant, larger D/d or ECPD lead to higher saturation of oil in the reservoir; When D/d is constant, smaller grain size of D or larger ECPD also lead to higher oil saturation in reservoir layers. For example, the oil saturation in reservoir layer with D = 0.01 mm and D/d = 10 is 30%, while the oil saturation with D = 0.5 mm and D/d = 10 is only 9%, this is because the ECPD of the former with smaller D (0.01 mm) can reaches 450 Pa, while the latter with larger D (0.5 mm) is only about 30 Pa, indicating that it is the ECPD between surrounding source rocks and inner reservoir layers rather than the grain size of reservoir layers that controls hydrocarbon migrating out of source rocks and accumulating in nearby tight reservoir layers, and the Fig. 8.12d shows that oil saturation directly increases with increasing ECPD.

8.5.3 Dynamic Model for Oil and Gas Accumulation in Deep Reservoirs Sandstone reservoir layers and mudstone source rocks are composed of clastic particles with different sizes. The grain size of sandstone generally varies from 0.01 to 2 mm, and that of mudstone is less than 0.01 mm (Morad 2010). According to physical modelling results in a previous study (Chen 1984), the compaction rate of mudstone reaches 70% and the sandstone is about 20% under the same pressure of 500 kg/cm2 , and the difference of their compaction rates varies up to 5 times if the overlying pressure change up to 900 kg/cm2 . The numerical simulation results (Table 8.1) show that the thickness of mudstone and sandstone with initial thickness of 100 m in the Bohai Bay Basin changes to 60.8 m and 79.6 m, 48.4 m and 60.0 m, 46.9 m and 55.0 m when buried at depths of 1000 m, 3500 m and 5000 m, respectively; the porosity

8.5 Confirming Contribution of the CPD by Physical Experiments

263

changes from 45% of the original state to 18.0% and 32.6%, 2.70% and 9.24%, 1.69% and 4.36%, respectively; and the pore throat radius also changes accordingly. Test experiments of displacement pressures for sandstone reservoir samples from different depths in the Bohai Bay Basin were conducted, their results correspond to the distribution characteristics of pore throat radius and capillary pressures in reservoir layers, confirmed the correlation between the differential compaction rates and differential capillary pressures (Table 8.2). Based on the statistical analysis of drilling results and the physical simulation results of ECPD driving oil migration and accumulation, a comprehensive dynamic model (Fig. 8.13) is established to address the relationship between oil/gas accumulations and the value of ECPDs, the ECPDs and differential compaction rates of shale source rocks and reservoir layers, and their variation with increasing depth. Figure 8.13a1 illustrate the differential compaction rates of shale source rocks and reservoir layers, Fig. 8.13a2 shows their thicknesses and porosity, and Fig. 8.13b1 their pore throat radius, Fig. 8.13b2 the replacement pressures of reservoir layers and Fig. 8.13c1 the hydrocarbon accumulation saturations. The whole evolution process of hydrocarbon migration and accumulation in deep and tight reservoir layers are divided into 4 stages (Fig. 8.13c2). The first stage (I) lasts from surface to hydrocarbon expulsion threshold (HET). The differential compaction is the largest driving force and most of hydrocarbons are expelled in water solution and diffusion, no of them are expelled in separate phase state, oil/gas could migrate upward from deeper source rocks into different traps to form conventional reservoirs by buoyancy-driving, and the oil/gas saturation and daily production of reservoir layers are small due to smaller ECPD. The second stage (II) lasts from HET to Buoyance-driven Hydrocarbon Accumulation Depth (BHAD). Hydrocarbon migration and accumulation are controlled by multi-driving forces as buoyancy, ECPD and others. The ECPD and the hydrocarbon expulsion rate from source rocks increase with increasing depth and reach their maximums, while the proportion of oil/gas reservoirs formed by buoyance-driving decreases with increasing depth. It is the most favorable stage for oil/gas migration and accumulation with their saturation > 60% and daily production at their highest. The third stage (III) lasts from BHAD to the Active Source-rock Depth Limit (ASDL). Because of tighter reservoirs and higher capillary resistance, oil/gas migrates and accumulate dominantly driven by ECPD to form continuous unconventional reservoirs. The proportion of oil/gas reservoirs formed by ECPD is larger than 50% and increase with increasing depth, meanwhile, the oil/gas saturation in reservoir layers, daily production, proven reserve and reservoirs number begin to decrease with increasing densification. The fourth stage (IV) goes below the ASDL or after third stage. The ECPD no longer exists between the inside and outside of the reservoir layers, hydrocarbon migration and accumulation are dominated by external forces as tectonic stress and activity of geofluids. The oil/gas reservoirs formed earlier are reformed or destroyed in this stage. Secondary oil/gas reservoirs might be formed in special geological conditions such as in fractures due to strata faulting and folding, but the reservoirs scale is very limited.

45.00

18.00

11.30

8.50

7.50

4.70

3.50

3.10

2.70

2.40

2.25

1.69

1.41

1.12

0

1000

1750

2000

2150

2550

3000

3200

3500

4000

4500

5000

5500

6000

6500

Porosity of mudstone (%)

Depth

2.23

2.78

4.36

5.71

7.43

9.24

10.33

11.40

14.97

20.63

24.50

29.20

32.60

45.00

Porosity of sandstone (%)

46.08

46.39

46.94

47.62

47.87

48.39

48.86

49.18

50.46

51.88

52.63

53.77

60.81

100.00

Compressed volume of mudstone

51.99

53.66

55.03

57.05

58.99

59.95

60.75

62.08

64.68

67.67

68.9

71.78

79.6

100

Compressed volume of sandstone

53.92

53.61

53.06

52.38

52.13

51.61

51.14

50.82

49.54

48.12

47.37

46.23

39.19

0.00

Mudstone compression ratio

48.01

46.34

44.97

42.95

41.01

40.05

39.25

37.92

35.32

32.33

31.1

28.22

20.4

0

Sandstone compression ratio

3.79

3.81

3.86

3.92

3.94

3.98

4.02

4.04

4.15

4.27

4.33

4.42

5.00

Mudstone height

3.45

3.47

3.52

3.57

3.64

3.71

3.76

3.80

3.96

4.25

4.46

4.76

5.00

Sandstone height

257.46

66.29

34.33

21.84

15.72

12.80

8.84

6.91

6.11

4.97

4.39

4.05

3.73

3.03

2.00

Critical ratio

3.08

3.52

4.07

4.76

5.67

6.89

8.59

9.96

11.08

14.50

19.23

21.67

27.03

68.22

112.19

Mudstone pore throat radius (nm)

794.16

233.41

139.61

103.98

89.08

88.13

75.92

68.80

67.67

72.08

84.50

87.72

100.76

207.04

260.10

Critical pore throat radius (nm)

Table 8.1 Numerical simulation on variation of source rock and reservoir layer of 100 m thickness with increasing depth from surface to the depth of 6500 m

264 8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Unit

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

No.

1

2

3

4

5

6

7

8

9

10

11

12

13

B28

B25

B25

B25

B25

B20

B20

B17

B14

B13

B13

B13

B13

Well

1659.14

1234.86

1277.51

1291.94

1243.61

1913.63

1903.40

1448.80

1773.01

1588.88

1584.58

1514.66

1812.64

Depth (m)

0.21

0.09

0.19

0.29

0.07

0.21

0.12

0.17

0.61

0.54

0.70

10.00

0.82

Displacement pressure (mPa)

0.21

0.29

0.21

0.21

0.18

0.39

0.29

0.11

0.19

0.88

0.75

0.73

0.53

Shaliness (%)

104

103

102

101

100

99

98

97

96

95

94

93

92

No.

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang sag

Qikou sag

Qikou sag

Unit

X16

X16

X16

X16

X16

X16

X16

X16

X16

X16

X16

BS68

BS68

Well

2648.92

2653.91

2670.00

2694.00

2717.20

2636.35

2586.90

2584.90

2618.20

2607.65

2607.60

4245.90

4245.88

Depth (m)

0.02

0.81

2.31

1.78

0.01

1.08

0.05

0.05

0.02

0.02

0.31

11.82

3.51

Displacement pressure (mPa)

Table 8.2 Test experiments for displacement pressures of Tertiary sandstone samples in continental petroliferous basins in eastern China

(continued)

2.10

3.00

11.50

3.00

4.80

10.50

1.40

3.00

9.60

1.70

/

53.00

23.95

Shaliness (%)

8.5 Confirming Contribution of the CPD by Physical Experiments 265

Unit

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

No.

14

15

16

17

18

19

20

21

22

23

24

25

B38

B38

B37

B37

B31

B31

B31

B28

B28

B28

B28

B28

Well

Table 8.2 (continued)

2302.07

2298.17

819.67

1472.46

1950.70

2816.96

2396.01

1733.42

1688.37

1688.30

1662.53

1694.50

Depth (m)

0.99

0.78

0.02

0.29

14.15

12.73

3.23

0.15

0.13

0.13

0.51

0.08

Displacement pressure (mPa)

0.51

0.42

0.28

0.16

0.99

0.98

0.75

0.59

0.50

0.50

0.33

0.22

Shaliness (%)

116

115

114

113

112

111

110

109

108

107

106

105

No.

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Jiyang depression

Unit

X16

X16

X16

X16

X98

X98

X98

X98

X98

X98

X98

X16

Well

2690.00

2681.50

2717.60

2618.00

2572.54

2587.03

2550.55

2553.62

2560.54

2493.31

2485.83

2597.38

Depth (m)

11.71

0.12

11.26

4.01

0.00

1.75

0.00

0.17

0.25

0.00

0.14

0.10

Displacement pressure (mPa)

(continued)

/

26.00

21.50

6.80

1.90

5.30

1.10

2.00

1.40

1.20

4.20

7.40

Shaliness (%)

266 8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Unit

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Beier sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

No.

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

G205

YJ1

ZH63

XJ1

x9

x4

x4

x4

x4

x4

HS2

HS2

HS2

HS2

D5

B53

B53

B53

B53

Well

Table 8.2 (continued)

1383.39

1350.58

1301.76

1274.06

2613.08

2781.56

2897.33

2464.04

2582.68

2782.02

1384.00

1053.93

1399.95

1382.14

922.44

3002.08

2899.34

3002.08

2901.21

Depth (m)

0.03

0.08

0.08

0.04

0.34

1.33

1.10

0.32

0.95

1.14

8.07

1.14

0.17

0.16

0.04

0.84

0.61

0.84

0.42

Displacement pressure (mPa)

5.00

8.60

9.40

7.20

0.30

0.32

0.30

0.20

0.19

0.12

0.83

0.64

0.53

0.27

0.57

0.29

0.22

0.21

0.18

Shaliness (%)

135

134

133

132

131

130

129

128

127

126

125

124

123

122

121

120

119

118

117

No.

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Jiyang depression

Jiyang depression

Jiyang depression

Unit

1940.80 2274.78

M39 × 1

3303.91 M7

3383.87 M108 × 1

3573.70

NP401 × 33 B10

2833.08

3178.80

3172.27

3557.05

NP1–22

L21–5

NP1–37

L12

3054.11

3052.64

LP1

2066.01

L3 × 3

1070.43

M22

M25

2917.51

2475.18

M8 × 1 G3101

2103.93

2571.30

2569.65

2656.00

Depth (m)

NP208

X98

X98

X16

Well

0.25

0.44

3.11

1.57

0.17

0.18

0.41

0.62

0.38

0.44

0.97

0.38

0.28

0.48

0.04

0.10

0.02

0.00

6.78

Displacement pressure (mPa)

(continued)

0.00

22.83

46.16

47.71

31.75

25.20

25.80

8.79

16.94

5.18

18.30

13.38

0.00

7.22

54.98

23.34

2.10

/

29.60

Shaliness (%)

8.5 Confirming Contribution of the CPD by Physical Experiments 267

Unit

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

No.

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

B834-3

B875

Z14-1

G330

Q129

G374

KG8

Q107

B837

G339

B63

ZH68

Q74

B57

Q127

Q124

G22-1

G205

GG1-1

G205

YJ1

Well

Table 8.2 (continued)

3021.40

2914.19

2871.40

2857.40

2852.80

2826.11

2818.50

2813.50

2705.86

2700.80

2694.60

2665.83

2657.04

2584.01

2289.30

2263.50

2197.98

2148.22

1788.10

1632.59

1398.21

Depth (m)

2.92

1.01

8.59

0.25

16.30

5.47

22.14

12.33

0.11

2.29

0.12

2.84

15.63

0.15

4.85

14.00

4.60

0.04

5.85

0.10

0.06

Displacement pressure (mPa)

28.39

6.10

70.65

7.70

76.00

44.28

78.00

68.00

5.40

22.73

8.90

17.06

62.32

3.90

70.19

75.00

35.39

6.00

60.00

10.10

6.50

Shaliness (%)

156

155

154

153

152

151

150

149

148

147

146

145

144

143

142

141

140

139

138

137

136

No.

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Unit

NP1–5

NP5–4

NP509

NP5–6

NP5–10

3962.80

3340.50

3344.36

3448.30

3625.90

2633.02

2851.72

M28 × 1 NP4–51

3511.50

2540.84

3119.20

2807.90

2303.00

2355.01

NP2–52

NP206

G23

M15

M24

M30

3196.30

3137.12

B6

3589.36

B6 × 1

2448.60

3899.50

3338.25

1849.50

3637.13

Depth (m)

G3105

G49

G3106

Pg1

L21–2

G3104

Well

0.04

0.03

0.19

0.63

2.82

3.18

0.48

0.53

0.80

0.52

0.33

0.13

0.80

0.78

0.85

0.82

0.89

2.06

2.03

0.02

0.30

Displacement pressure (mPa)

(continued)

0.00

24.98

13.80

31.48

32.39

54.57

35.93

14.31

14.23

26.09

40.96

49.85

30.20

47.11

31.97

6.40

5.64

36.52

56.53

7.81

23.51

Shaliness (%)

268 8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

Unit

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

No.

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

T19

Gs30

Q129

DC1

BS51

BS16

BS72

BS25

DG1

Gs19

GX57

Gs18-1

Gs18

BS18

B40

B65

Bai20-2

Gs9

Gs68

G580

BS39

Well

Table 8.2 (continued)

3815.00

3797.55

3778.20

3758.20

3705.47

3672.06

3670.10

3669.08

3540.33

3521.20

3477.10

3272.60

3263.33

3251.40

3201.71

3187.17

3176.20

3156.80

3126.20

3066.04

3037.38

Depth (m)

18.09

0.74

15.36

3.92

0.74

0.15

0.50

0.99

19.12

6.63

9.37

4.19

9.88

1.26

4.03

0.28

5.54

3.78

3.21

0.25

0.07

Displacement pressure (mPa)

65.00

7.10

59.00

55.00

7.80

7.30

6.10

6.00

72.00

44.61

49.70

50.99

45.79

15.12

4.30

6.70

29.22

25.93

18.71

4.70

5.60

Shaliness (%)

177

176

175

174

173

172

171

170

169

168

167

166

165

164

163

162

161

160

159

158

157

No.

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Unit

B3

B5

M5

M12

M1

NP1–4

G62

G3102

LPN1

G4

2776.61

4221.35

2768.36

2288.60

3432.04

3387.84

4054.60

3424.50

2647.78

2667.61

2633.49

2074.94

B32 × 1 L15

2362.90

M11

2678.70

3579.24

M10

4539.81

M38 × 1

4246.74

3055.50

NP5–81

NP1

LP1s

3445.43

3307.65

NP5–6

3975.40

M28 × 1s

Depth (m)

NP4–51s

Well

1.66

4.25

3.77

11.80

7.65

4.57

1.31

0.57

0.26

4.46

0.24

0.11

0.72

0.49

0.64

0.79

0.59

0.56

0.83

1.34

0.59

Displacement pressure (mPa)

(continued)

63.80

35.89

51.21

0.00

65.83

52.19

34.72

6.65

6.33

32.65

45.94

10.13

51.19

30.31

48.93

0.00

43.96

7.23

57.41

59.24

42.16

Shaliness (%)

8.5 Confirming Contribution of the CPD by Physical Experiments 269

Qikou sag

Qikou sag

Qikou sag

Qikou sag

Qikou sag

87

88

89

90

91

Q129

Gs14

Gs21

Gs67

Gs15

Well

4098.48

4045.19

3897.94

3846.10

3845.16

Depth (m)

15.28

0.18

1.09

1.50

0.26

Displacement pressure (mPa)

56.30

4.60

5.80

23.72

3.90

Shaliness (%)

181

180

179

178

No.

Nanpu sag

Nanpu sag

Nanpu sag

Nanpu sag

Unit

B7

M17–1 3597.58

2735.27

2707.31

4132.70

B22 × 1 B13

Depth (m)

Well

4.12

0.77

0.87

3.29

Displacement pressure (mPa)

38.68

19.32

28.01

58.04

Shaliness (%)

Results Test experiments for displacement pressures of tertiary reservoir sandstone samples in continental petroliferous basins in eastern China, samples are mainly from Beier Sag in Hailar Basin and Qikou Sag in Bohai Bay Basin

Unit

No.

Table 8.2 (continued)

270 8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

8.6 Discussion and Conclusion

271

Fig. 8.13 A dynamic model and stage division for hydrocarbon migration and accumulation in clastic sedimentary strata driven by the ECPD between surrounding source rocks and inner sandstone reservoirs due to differential compaction rates during their burial history and tightening process

8.6 Discussion and Conclusion 8.6.1 The CPD is the Most Important Driving Force for Tight Reservoirs Formation This is related to four characteristics of CPD: (1) always coexists with source rocks and surrounding reservoir layers due to the difference of their pore throat radius; (2) always is in action continuously and uninterruptedly to oil/gas expulsion from source rocks and accumulation in nearby reservoir layers; (3) irreversible migration direction from source rocks with smaller throat radius to the reservoir layers with larger throat radius; (4) irreplaceable role in the migration and accumulation of oil/gas in deep and tight reservoirs where the effects of other driving forces greatly becoming weak and almost disappearing. The established model (Fig. 8.13) represents the dynamic characteristics of hydrocarbon accumulation under general geological conditions, can be applied to understand and predict oil/gas resources formed in reservoir layers during their burial process and densification, but there are several special situations that need to be noted.

8.6.2 Special Conditions for Abnormal Oil and Gas Accumulation in Deep Reservoirs Different understandings may appear under the following special circumstances. In case one, the source rock is contacting with tight surrounding strata up and down such as salt or other strata, then there is no CPD between them. Most of the hydrocarbons generated in source rock could not be expelled, and majorly accumulate to

272

8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

form shale oil or gas resource in place with high degree of thermal evolution (Liu et al. 2017; Zhang et al. 2019). In case two, the source rock is contacting to reservoir layers up and down with high porosity and permeability, then there is large CPD between them. Most of oil and gas generated in source rocks is expelled smoothly and the oil and gas retained in the source rock is very small to form effective shale oil or gas resources. Most of oil and gas expelled from source rocks migrate driven by buoyance to form conventional oil and gas resources in traps (Pang et al. 2021a). In case three, the hydrocarbon expulsion dynamic characteristics and contributions of each driving force in the deep burial process may deviate from the relevant model established in this paper when the source rocks with abnormal characteristics are contacted to reservoirs with abnormal characteristics. For example, the contribution of compaction to oil and gas expulsion will be improved when most of pore water in source rock is released at a late period (Chen et al. 1989). The lower salinity of groundwater will increase the contribution of diffusion to hydrocarbon expulsion (Leythaeuser 1982; Rose 2001; Qiao et al. 2019); and the change of mineral wettability in the source rocks and the reservoirs will result in CPD hindering hydrocarbon expulsion (Li 2004), and so on.

8.6.3 Tectonic Movements and Reservoirs Reformations Tectonic movements would change the dynamic process of oil/gas expulsion from source rocks and the type of oil and gas reservoirs (Pang et al. 2016), which are mainly manifested in two aspects. First, tectonic movement will form a large number of fractures in the reservoir by stress action and secondary pores because of underground fluid activities; or produce a large number of dissolution pores because of the existence of unconformity surface, further increasing CPD and its contribution to hydrocarbon expulsion; Second, tectonic movements have reformed the tight oil and gas reservoirs formed early around the source rocks, result in the formation of “sweet point” in deep and tight oil and gas reservoirs due to the development of fractures caused by strata folding and faults (Ghaderi et al. 2011). Exploration results in the Tarim Basin have demonstrated that the 92% of proved reserves are distributed in the deep tight reservoirs developed with factures and pores under the unconformity surface. These large amount of oil and gas accumulations are formed because of the huge difference between internal and external capillary force. The favorable exploration area predicted based on these include three types, including in the area of complex structures in the foreland basin, deep carbonate rocks, and lithology and stratigraphic reservoirs in the platform basin. All the discovered oil and gas reservoirs and 95% of proved reserve are distributed in the favorable exploration area.

8.6 Discussion and Conclusion

273

8.6.4 The Abnormal Low Saturation of Oil and Gas in Shallow Layers The low oil/gas saturation in shallow reservoirs with high porosity is related to smaller ECPD, and also related to the large thickness of irreducible water molecular layers on mineral surface due to adsorption (Hu 2004). The irreducible water thickness on mineral surface decreases with increasing depth and temperature (Miler 1985; Wang 2002). At higher temperature, oil/gas molecules move more actively, and their absorption to rock surfaces becomes weaker, Tong et al. (2016) studied the change of irreducible water saturation with increasing temperature by using the unsteady state test method and obtained a similar conclusion, the irreducible water saturation can be decreased from 40 to 10% with temperature rising from 20 to 100 °C, the effect of attenuated water film at higher temperature on oil/gas saturation cannot be omitted.

8.6.5 The Critical Minimum Driving Force for Oil and Gas Accumulation When the mineral composition and wettability of the source rock and sandstone reservoir are identical, the critical minimum driving force for hydrocarbon migration and accumulation is PCS /PCR ≥ 2, but for the composition of shale source rock with quartz and feldspar and the reservoir layer with carbonate calcite and dolomite, the critical minimum driving force may be different, because their capillary resistances are different due to different interfacial tension and wetting angle with oil and gas. For example, in the Tarim Basin, the critical minimum porosity and permeability of sandstone reservoirs for oil/gas migrating from shale source rocks to accumulate are about 2% and 0.01 mD, respectively, while of the carbonate reservoirs are as low as 0.5% and 0.001 md, respectively (Shen 2015). These indicate that the understanding based on the study of sandstone reservoirs cannot be fully applied to carbonate reservoirs and vice versa.

8.6.6 The Most Favorable Depth Range for Oil and Gas Accumulation Special attention should be paid to following four situations when the dynamic model be applied to predict the most favorable depth range for hydrocarbons accumulation. (1) Oil/gas accumulated earlier in the most favorable depth range can be preserved to be in shallower depth or be buried to deeper area in some abnormal conditions. (2) Special combination of surrounding source rocks and inner reservoir bodies with abnormal pore structure can continue to accumulate oil and gas even buried to be in deeper areas. (3) Oil/gas migration and accumulation could take place again in very

274

8 Prediction and Evaluation of Tight Oil and Gas Reservoirs

tight unconventional reservoirs to form oil/gas “sweet point” with high production if the reservoir layers are reformed by fractures and secondary pores due to tectonic movements and geofluids activities, driven by ECPD or buoyance or combination of multi-driving forces, whether the tight reservoir layers are below or above the most favorable depth range.

8.6.7 The Maximum Depth for Oil and Gas Accumulation The maximum depth of oil/gas reservoirs has long been a controversial and unsolved problem, researchers who advocate inorganic origin of petroleum thought oil/gas accumulation is beyond the depth of petroliferous basins themselves and could even reach the upper mantle (Kolesnikov 2009; Huang 2017), and those who advocate organic genesis believe that oil/gas accumulations could not exceed the maximum buried depth of the source rocks in a basin (Robinson 1966). From our study, the maximum burial depth of deep tight oil/gas reservoirs is depended two critical conditions, one is the active source-rock depth limit, which is identified by the thermal evolution degree of Ro = 3.5 ± 0.5% (Pang 2020), and the other one is the hydrocarbon accumulation depth limit, corresponding to the sandstone porosity of 3 ± 1%, permeability of K ≈ 0.01 md, pore throat radius of R ≈0.025 μm, or the maturity of Ro = 2.75 ± 0.25%.

8.7 Summary Buoyancy has been regarded as major driving force for oil and gas to migrate upward through the carrier bed and accumulate in trap structures in petroliferous basins. These constitute the core content of the classical theory of petroleum geology, so far 14,645 × 108 t oil equivalent reserves in the world have been proved under guidance of the classic theory. However, more and more unconventional deep and tight oil and gas reservoirs have been proven in exploration-restricted areas in petroliferous basins since the discovery of continuous tight gas reservoirs in the deep depression of the Albert Basin in Canada in 1978, which was once considered impossible to accumulate oil/gas by classical petroleum geology theory. These unconventional reservoirs also show unique geological characteristics, indicating that the formation and distribution of oil/gas reservoirs is not controlled by buoyancy and traps. So far, billion tons of oil and gas reserves have been discovered in tight reservoir layers with depth > 4500 m, showing enormous exploration potential in the deep and tight layers. Understanding dynamic mechanism of oil and gas accumulation and enrichment in deep and tight reservoir layers is of practical significance for predicting oil/gas reservoirs distribution and improving exploration efficiency. Given consideration of these reservoirs widely distributed in the tight reservoirs and are closely related to source rocks, most scholars believe that the hydrocarbon migration and accumulation in tight reservoir

References

275

layers is driving by the non-buoyance forces directly caused by the hydrocarbon generation and expulsion from source rocks. However, people do not understand what kind of non-buoyance is the most important for driving hydrocarbon to migrate and accumulate in deep and tight reservoirs to date, because there are 5 types and 9 driving forces related to them, such as compaction by overlying strata, products volume inflation from organic matter transformation and clay minerals dehydrate, volume increase of mineral and fluids (water, oil and gas) in source rocks due to higher temperature, hydrocarbon diffusion by concentration gradient, and capillary pressure difference between surrounding source rocks and inner reservoirs. In this study, we apply three methods, including statistical analysis, numerical simulation and physical modelling experiment, to study on the differences and correlations of these 9 driving forces in oil/gas expulsion from source rocks to quantify their relative contributions in a tight reservoir formation with increasing depth, reveal the controlling mechanism of dominant driving force and establish the dynamic model of oil/ gas expulsion and accumulation during tightening of reservoir layers.

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Chapter 9

Evaluation of Unconventional Shale Oil and Gas Resource

New Understanding: (1) There are significant differences between continental shale and marine shale in mineral composition, bedding structure, and lithofacies distribution, which determine the lower mobility of continental shale oil than that of marine shale oil. (2) The continental shale oil content increases with the thinning of sedimentary facies laminae, the increase of internal pore throat radius, and the enhancement of surrounding rock sealing. The retained oil content reaches the maximum when the burial depth is moderate and the thermal evolution degree is Ro ≈ 1.20%. (3) The physical simulation results of NMR displacement of artificial cores show that the moveable oil ratio of shale increases with the increase of porosity and permeability, the decrease of clay mineral content, oil viscosity, and kerogen content. (4) The obtained parameters such as the movable oil ratio and recovery factor, the volume method and Monte Carlo simulation technology are used to evaluate the recoverable shale oil resources in the Sha-3 member in the Gaoliu area in the range of 950–1000 × 104 t.

9.1 Introduction and Issue 9.1.1 Shale Oil Exploration Showing Broad Development Prospects The United States was the first country to explore and develop marine shale oil and gas resources on an industrial scale. Since 2000, when breakthroughs were made in horizontal drilling and completion, hydraulic fracturing, and other technologies, shale oil and gas output increased year by year (Fig. 9.1). In 2018, 49% of proved crude oil and condensate reserves and 81% of proved natural gas reserves came from shale formations. Shale oil and gas industries in the USA, Australia, and Europe have also boomed in recent years (Rogner 1997; Jiang et al. 2012; Hu et al. 2017; Ma and © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_9

279

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9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.1 USA shale oil production distribution since 2005

Xie 2018). The recoverable resources of shale oil and shale gas worldwide are 1501.3 × 108 t and 456.2 × 1012 m3 , respectively (EIA 2011; IHS 2014; Zou et al. 2015). Global shale oil production is expected to rise to more than 400 million tons by 2030 (BP 2015). The Chinese government has placed high expectations on shale oil and gas development. It has carried out a fundamental research project (973) at the national level, set up relevant subjects in major special studies, and made breakthroughs in exploration and development practices (Dong et al. 2012). Preliminary studies show that China’s shale oil resource potential is as high as 200.88 billion tons (Hu et al. 2020). They are mainly distributed in Songliao Basin, Ordos Basin, Sichuan Basin, and Bohai Bay Basin and have broad exploration and development prospects (Zou et al. 2013a). Some experts predict that China’s annual shale oil production will reach 80 billion to 100 billion tons by 2030 (He 2017).

9.1.2 Continental Shale Oil Widely Distributed but Controlling Factors Very Complex The first shale gas field was discovered in 1914 in the United States. The commercial development of Barnett shale gas was realized in 1981. The focus of oil and gas exploration and development in the world has gradually shifted to unconventional oil and gas resources (Curtis 2002; Jarvie 2012; Jiang et al. 2012). The shale oil and gas resources in the USA are widely distributed in more than 50 shale formations in 20 states: The Marcellus and New Albany shale of the Ordovician in the Appalachian Basin, the Mississippian Barnett shale of the Fort Worth Basin, The Devonian Woodford shale in the Anadarko Basin and the Eagle Ford shale in the

9.1 Introduction and Issue

281

Western Gulf Basin, and so on (Dawson 2009; Xiao et al. 2013; Chen et al. 2019). Canada is the second country in the world to realize the commercial exploitation of shale oil and gas resources. Its shale oil and gas resources are widely distributed and multi-layered, mainly concentrated in the Lower Cretaceous, Jurassic, Triassic and Devonian systems in British Columbia and Alberta (Shirley 2002; Chalmers and Bustin 2007; Bustin et al. 2008). The Posidonia shale is a vital shale formation in the Yorkshire Basin, Saxony Basin in Germany, and Paris Basin in France (Han et al. 2017; Song et al. 2017; Stock et al. 2017). The results show that the shale oil mainly comes from marine strata and has the characteristics of high thermal evolution degree, good parent material type with kerogen of type I, light crude oil density, large area continuous distribution of strata, and high brittle mineral content. However, continental shales are mainly developed in China, characterized by low thermal evolution degree, parent material type of Kerogen II–III, heavy crude oil density, strong formation heterogeneity, and high clay mineral content. These differences have led to the current low efficiency in exploration and exploitation as well as big challenges in technology development.

9.1.3 Evaluating Quantitatively the Movability of Continental Shale Oil Difficult For shale oil exploration and development, it is necessary to evaluate not only the total amount of retained oil in shale formations but also how much of retained oil is movable (Zhang et al. 2012; Wang et al. 2013, 2015a; Li 2014; Wu et al. 2015). Therefore, determining the ratio of movable oil in shale is the core content of shale oil resource evaluation. In recent years, important progress has been made in the quantitative characterization of movable and adsorbed oil in marine shale. Predecessors have developed five methods and technologies: One is the oil saturation index method (S1 /TOC) (Pepper and Corvi 1995; Lopatin et al. 2003; Jarvie 2012; Jarvie and Daniel 2012; Xue et al. 2015; Li et al. 2016); The second is the combination of Nuclear Magnetic Resonance (NMR) and centrifugal/displacement analysis (Wang et al. 2010; Li 2014; Wu et al. 2015; Li et al. 2016); The third is the gradual pyrolysis/heating release method (Li et al. 2016); Fourth, solvent step extraction/swelling method (Ritter 2003; Ertas et al. 2006; Cai et al. 2007; Li et al. 2017); Fifth, molecular dynamics simulation method (Fathi and Akkutlu 2012; Mosher et al. 2013; Lin et al. 2015; Wang et al. 2015a). These methods lay a good foundation for studying the amount and ratio of movable hydrocarbons in shale.

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9 Evaluation of Unconventional Shale Oil and Gas Resource

9.1.4 There Lacking Mature Technology for Evaluation of Continental Shale Oil China’s continental shale oil resources have huge potential, which is expected to form major support for long-term self-sufficiency in exploration and development (Zou et al. 2013b; Zhao et al. 2018). However, not all shale oil is technically available for commercial development, and only some of the sweet spots can be targeted for efficient exploration and development (Yang et al. 2015). Different scholars have used different methods to predict and evaluate shale oil sweet spots, mainly including comprehensive information superposition method (Zou et al. 2013b; Ning et al. 2015; Yang et al. 2019; Zhang et al. 2020; Zhao et al. 2020a), drilling and seismic integration method (Pan et al. 2018; Gao et al. 2019; Guo et al. 2019; Dong et al. 2020), comprehensive index evaluation method (Zhao et al. 2020b; Zhou et al. 2020). The comprehensive information superposition method is only suitable for the early stage of shale oil exploration. The combination of drilling and seismic method relies on constructing a seismic-geological characterization model to predict the distribution of shale oil reservoirs (Gao et al. 2019). The comprehensive index evaluation method considers many factors, often leading to the failure of the best matching between geological and engineering sweet spots (Li et al. 2015). These methods all have different disadvantages, which show the immaturity of the evaluation of continental shale oil, mainly in the following three aspects: First, a large number of previous studies have been carried out on shale oil reservoirs, especially on pore structure, but most of the studies do not consider the heterogeneity of continental shale reservoirs, but treat shale with different lithofacies as a whole; Second, the resource potential evaluation of continental shale oil mostly belongs to the total amount of shale oil, without considering their mobility and recovery. Thirdly, the ratio of movable oil is a crucial parameter for evaluating continental shale oil resources, but the current research methods are relatively simple, and the understanding is similar that of marine shale. How to overcome these problems and improve applicability and reliability of shale oil evaluation is the focus of this study.

9.2 Principle and Workflow of Shale Oil and Gas Evaluation Taking the Tertiary Sha-3 shale in Bohai Bay Basin, eastern China, as an example, this study explores the main controlling factors of oil retention in shale with different lithofacies. A physical simulation experiment was applied to reveal the formation mechanism of movable oil and establish the quantitative relationship between it and the main controlling factors. Finally, the practicability and reliability of the research results are illustrated based on a case study of recoverable shale oil resource evaluation.

9.2 Principle and Workflow of Shale Oil and Gas Evaluation

283

9.2.1 Main Contents and Technical Ideas Studies are carried out in four steps (Fig. 9.2). The first step is to determine the oilbearing characteristics of shale through organic carbon test, rock pyrolysis analysis, chloroform asphalt extraction, and vitrinite reflectance measure. In the second step, lithofacies of shales in the third member of Shahejie Formation in the Gaoliu area, Nanpu Sag, Bohai Bay Basin was divided based on thin sections and X-ray diffraction analysis. In the third step, the shale of different lithofacies was observed by scanning electron microscope, gas adsorption test, high-pressure mercury injection, and nuclear magnetic resonance test, respectively, to clarify the pore structure characteristics of shale with different lithofacies and its influencing factors. Artificial cores were prepared under different pressure conditions, clay mineral content, kerogen content, and crude oil viscosity. NMR displacement experiments were carried out to study the changing rules of movable oil under different factors and its main controlling factors. The fourth step is to predict the amount of recoverable oil resources of shales in the third member of Shahejie Formation in the Gaoliu area of Nanpu Sag according to the oil content and movable oil ratio obtained from shale analysis, to provide theoretical guidance for shale oil exploration and development in the future.

Fig. 9.2 Technical ideas and workflow of shale oil research on hydrocarbon retention and mobility evaluation

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9 Evaluation of Unconventional Shale Oil and Gas Resource

9.2.2 Key Study Area Selection and Regional Geological Survey The Bohai Bay Basin (Fig. 9.3a) is selected as the focus of this paper for five main reasons. First, the proven oil and gas reserves are large, and the remaining resource potential is enormous. Secondly, abundant shale oil resources have been found in Tertiary source rocks. Thirdly, many research results and data have been accumulated after years of exploration (Hou 2014; Cheng and Chen 2015; Xu and Ji 2015). Fourthly, many independent fault depressions are developed in the basin with similar geological and reservoir forming conditions. It is beneficial to understand the whole basin by studying a single fault depression. Fifth, the evolution history of the basin is simple (Chen et al. 2007; Zhang et al. 2007). The Sha-3 member of the Shahejie Formation was deposited during the early rift expansion period (Zhang et al. 2007). During the sedimentary period of Sha-2–Sha-1 member, fault activity weakened, and the transformation of new faults was tiny (Tang and Wang 2008). During the sedimentary period of the Dongying Formation, the main basement faults stopped activity (Lei and Duan 2006; Tang and Wang 2008). During Neogene and Quaternary period, the sag sank and formed regional sag with weak fault activity (Yan et al. 1980). In this study, the Sha-3 member of Tertiary Shahejie Formation in Dongpu Sag and Nanpu Sag is the key analysis object. The research results and new understanding are used to predict and evaluate the distribution of movable oil sweet spots in the shale.

Fig. 9.3 Oil and gas exploration in Bohai Bay Basin, China, and geographical location of key research areas. a Oil and gas exploration situation in Bohai Bay Basin and the location of key research areas; b Tectonic zoning and distribution of Tertiary shale in Dongpu Sag, Bohai Bay Basin

9.3 Sedimentary Lithofacies and Types of Shale Rocks

285

Bohai Bay Basin is in the east of China. Dongpu Sag is in Linqing Depression in the southwest, an independent fault depression extending NNE and wide in the south and narrow in the north. Tertiary deposits are mainly developed on the paleo-Mesozoic sedimentary base, covering an area of about 5300 km2 (Zhang et al. 2017a, b). It is divided into five sub-tectonic units from west to east (Du et al. 2008; Zhou et al. 2010): western slow slope belt, western depression belt, central uplift belt, eastern depression belt, and steep slope belt (Fig. 9.3b). Nanpu Sag is in the central part of Bohai Bay Basin, at the southern edge of the Yanshantai fold belt in the northeast corner of the Huanghua Depression. It is a compound half-graben structure of “north fault and south overpass,” with a total area of 1932 km2 (Zheng et al. 2007; Zhu et al. 2013). Nanpu Sag can be divided into four secondary structural zones (Mei et al. 2008; Wang et al. 2011).

9.2.3 Samples and Analysis Shale oil samples were obtained from exploration Wells in Dongpu Sag and Nanpu Sag. The depth of some samples is less than 1777 m, and the vitrinite reflectance (Ro) is 0.46%, which is in the immature stage. The samples are typical saline-lacustrine shale, containing organic-rich and organic-poor laminae frequently interbedded, with total organic carbon (TOC) content of 2.13%. The organic matter is mainly with kerogen type I and a small amount of kerogen type III. Shale samples were collected from 10 Wells, including G19-10, L68X1, G80-12, G83-10, G18, G3101, L22, G651, G5, and G23, in the Gaoliu area of Nanpu Sag, with a total of 130 pieces of shale samples; Most of shale samples and shale oil samples are from Wells in Dongpu Sag as illustrated in Fig. 9.3b. The samples are from the middle and lower part of the Sha-3 member of the Paleogene Shahejie Formation.

9.3 Sedimentary Lithofacies and Types of Shale Rocks Combined with the organic geochemical test results, 76 shale samples from the Sha-3 member of Shahejie formation in the Gaoliu area of Nanpu Sag were screened for XRD analysis, and the characteristics of mineral composition, laminated structure, and shale lithofacies were analyzed.

9.3.1 Mineral Composition Characteristics of Shale The mineral composition for shale is mainly quartz and feldspar, but the clay content is high. Quartz and feldspar range from 13 to 76%, averaging about 40%; Clay minerals are next, accounting for 14–59% with an average of about 41%. Calcareous

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9 Evaluation of Unconventional Shale Oil and Gas Resource

minerals have the lowest content of 1–63%, with an average of only 19%, showing strong heterogeneity. The content of calcareous minerals in most wells of the Sha-3 member in the Gaoliu area of Nanpu Sag is less than 30%. The samples with more than 30% calcareous mineral content were mainly from Wells G80-12, G18, and G19-10, with the highest range of more than 60%. The ratio of Aemon mixed layer in clay mineral composition is high. Clay minerals mainly include kaolinite, illite, chlorite, illite mixed layers, and almost no montmorillonite. The proportion of illite mixed layers is up to 89%, with an average of about 73%. The other three minerals are lower, with a total of less than 30%. The average kaolinite, chlorite, and illite proportions are about 11%, 8%, and 7%, respectively. In the early diagenetic stage, the montmorillonite is transformed into illite in large quantities, and the interlayer water in the montmorillonite begins to extricate in large amounts. At the same time, organic matter in mudstone and shale gradually enters the low maturity—maturity stage, with the formation of many organic acids such as acetic acid and glycolic acid and dissolution of surrounding carbonates and other substances.

9.3.2 Bedding Structure Characteristics of Shale Continental shale is mainly developed in the lacustrine basin with rapid facies change and has rich bedding structure (Liang et al. 2012; Wang et al. 2013, 2016; Ning 2015; Ning et al. 2017). The laminated structure is developed, mainly composed of interbedded organic clay laminae and gray or silty laminae (Fig. 9.4). The thickness of single lamination is generally less than 1 mm, and it is flat and continuous with light and dark colors. The dark lamina is composed of organic clay, and the light lamina is gray (calcite) or sand (quartz and feldspar). The calcite is mostly microcrystalline and cryptocrystalline, and the sand is primarily silty and fine sand (Wang et al. 2016; Ning et al. 2017). If the relative percentage of organic clay lamina is more than 50%, the shale is mostly calcite mudstone, and the lamination thickness is less than 0.01–0.1 mm (Fig. 9.4a–c). Suppose the relative percentage of the gray or silty lamina is greater than 50%, in that case, the shale is argillaceous limestone or argillaceous siltstone, and the lamination is relatively wide, up to 0.1–1 mm thick (Fig. 9.4d–e). Laminated shales are usually formed in quiet water bodies with a low sedimentation rate, saline reduction environment (Yang et al. 2015). Shale oil is mainly concentrated in shale of this kind of laminated structure (Wang et al. 2016; Ning et al. 2017). Some laminae are narrow at the top and wide at the bottom (Fig. 9.4e), some develop laminated fractures (Fig. 9.4e), and some are even crumpled and deformed (Fig. 9.4g, h). All these result from the early laminae being subjected to the later water environment changes or tectonic activities. The wide thickness of lamellar structure reflects the strong hydrodynamic conditions. Single-layer thickness is usually more than 1 mm (Fig. 9.5a–b), with light and dark colors. Layers are not straight and continuous enough (Fig. 9.5c, d), the

9.3 Sedimentary Lithofacies and Types of Shale Rocks

287

Fig. 9.4 Laminated structure of the Sha-3 member shale in the Nanpu Sag, Bohay Bay Basin, China

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9 Evaluation of Unconventional Shale Oil and Gas Resource

boundary between layers is not apparent, and some layers are even distributed in disorder (Fig. 9.5e, f). For shale with stratified structure, the lithologic heterogeneity is strong, and the content of gray or sandy is high. The calcite or debris is lenticular and banded. The content of clay lamination is low, and the lamination is narrow, and most of them are argillaceous limestone or siltstone, marl, or siltstone. Shale with stratified structure is mostly formed in the environment with relatively turbulent hydrodynamic force and rapid sedimentation rates. Its organic matter content is lower than that of laminated shale.

Fig. 9.5 Stratified structural characteristics of shales in the Tertiary Sha-3 member in the Gaoliu area, Nanpu Sag, Bohai Bay Basin. a G18-5; b G18-5; c G19-10-10; d G19-10-20; e G19-10-11; f G3101-6

9.3 Sedimentary Lithofacies and Types of Shale Rocks

289

Fig. 9.6 Massive structural characteristics of Tertiary Sha-3 shale in the Gaoliu area, Nanpu Sag, Bohai Bay Basin. a G18-1; b G83-10-3; c G83-10-6; d G83-10-7

The massive structure is developed, and no lamina reflects the sedimentary environment of shallow water turbulence. The organic matter, argillaceous matter, gray matter, and sandy matter in the massive structural shales are usually dispersed without laminae. According to mineral components, shale with a massive structure can be divided into argillaceous siltstone (Fig. 9.6a), sand-bearing mudstone (Fig. 9.6b), calcareous mudstone (Fig. 9.6c), and calcium-bearing mudstone (Fig. 9.6d). They are mainly formed in shallow water environments under strong hydrodynamic conditions, with rapid deposition rates and high impurity content without apparent differentiation. Organic carbon content is the lowest among the three stratified structural shales.

9.3.3 Characteristics of Shale Sedimentary Lithofacies The sedimentary facies of shale are divided into four categories. Lithofacies refers to rocks or rock assemblages formed in a particular environment and indicate sedimentary processes and environments (Loucks and Ruppel 2007). The shale with the same lithofacies has the same geochemical characteristics, sedimentary structure, mineral composition, mechanical properties, and oil–gas bearing property (Kale

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9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.7 Triangulation of lithofacies classification of shales in Tertiary Sha-3 member of Nanpu Sag, Bohai Bay Basin. A—Siliceous shale area; B—Calcareous shale area; C—Clayey shale area; D-Mixed shale area

et al. 2010; Aplin and Macquaker 2011). Many lithofacies classification schemes have been proposed by researchers (Hickey and Henk 2007; Loucks and Ruppel 2007; Abouelresh and Slatt 2011, 2012; Dong et al. 2015). Among these schemes, obtaining mineral composition by XRD analysis is currently the most effective and commonly used lithofacies division scheme (Furmann et al. 2014; Jiang et al. 2016). The Shahejie Formation in Bohai Bay Basin is divided into four lithofacies based on XRD results (Fig. 9.7). One is siliceous shale, its siliceous mineral content ≥ 50%; The second is calcareous shale, its calcium mineral content ≥ 50%; The third is the clay shale, its clay mineral content ≥ 50%; The fourth is mixed shale, three kinds of mineral content are less than 50%. The formation environment of continental shale is roughly classified into three types of lacustrine deposits (Fig. 9.8). Firstly, calcareous shale’s TOC and TS values are highest in deep lacustrine facies. The organic matter is mainly type I, formed in the depositional environment of partial reduction. TOC and TS values of mixed shale are distributed from low value to high value and gradually increase with the increase of calcium mineral content, and the decrease of siliceous mineral content, the kerogen type of mixed shale is very different. With the rise in detrital input, kerogen type gradually changes from type I to type III. The siliceous and clay shales have low TOC and TS values, kerogen of type II or III, high terrigenous clastic content, and low calcium mineral content, indicating that terrigenous clastic input is strong and the shales deposited in shallow lacustrine facies with shallow water and partial oxidation.

9.4 Variation and Controlling Factors of Retained Oil in Shale

291

Fig. 9.8 Sedimentary environment characteristics of different lithofacies shales in the Tertiary Sha-3 member of Nanpu Sag, Bohai Bay Basin. a The relationship between TOC and TS; b The relationship between TOC and calcium mineral content; c The relationship between TOC and siliceous mineral content; d Relationship between TOC and clay mineral content

9.4 Variation and Controlling Factors of Retained Oil in Shale The retained hydrocarbon of shale can be divided into free hydrocarbon and bound hydrocarbon, the former flows freely, while the latter is controlled strongly by lithofacies, pore structure, surrounding rock conditions, and burial depth (Sun et al. 2019; Hou et al. 2021; Hu et al. 2022; Xu et al. 2022).

9.4.1 The Retained Oil Amount in Shale is Controlled by Lithofaces The amount of retained oil in organic-rich shale lithofacies is higher than that in organic-poor shale lithofacies (Fig. 9.9). The amount of retained free hydrocarbons in organic-rich lithofacies is 0.32–12.62 mg/g, with an average of 2.55 mg/g. The

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9 Evaluation of Unconventional Shale Oil and Gas Resource

amount of retained bound hydrocarbons is 0.08–19.64 mg/g with an average of 3.60 mg/g, 1.52 times that of free hydrocarbons. The amount of retained free hydrocarbons in the organic-poor lithofacies is 0.01–0.58 mg/g, with an average of 0.16 mg/ g. The amount of retained bound hydrocarbons is 0–0.49 mg/g with an average of 0.10 mg/g, 0.25 times that of free hydrocarbons. In the organic-rich lithofacies, the highest free hydrocarbon and bound hydrocarbon occur in the laminated clay shale. The influence of lithofacies on the amount of retained hydrocarbon is mainly shown in two aspects: One is the control of mineral composition, and the other is the influence of organic composition on the amount of retained hydrocarbon. The retained oil amount of inorganic minerals in shale is mainly controlled by pore size and clay content. Mud shales contain many clay minerals and water content of maximum 80–90% without obvious compaction (Bernhard et al. 2003; Schieber 2011). The increase of clastic quartz and carbonate minerals will reduce the porosity of shale (Ross and Bustin 2007; Chalmers and Bustin 2008), then the storage space of free oil and gas is reduced. In terms of mineral composition, marine shale is characterized by a high quartz and carbonate minerals content. The rigid framework formed by marine shale preserves certain pore space and provides conditions for shale oil storage (Zhang et al. 2014; Liu et al. 2019). Clay minerals generally have a layered structure and a large specific surface area, enabling hydrocarbon molecules

Fig. 9.9 Test results and comparison of retained hydrocarbon content in different lithofacies belts of Sha-3 member in Bohai Bay Basin. a Relationship between free hydrocarbon content and lithofacies; b Relationship between bound hydrocarbon quantity and lithofacies; c The relationship between the ratio of bound and free hydrocarbons in lithofacies

9.4 Variation and Controlling Factors of Retained Oil in Shale

293

to adsorb on the external surface of clay minerals (Zhao and Zhang 1990; Wang et al. 2015b). The oil retention capacity of inorganic minerals is about 0.20–3.13 mg/ g, and the oil retention capacity of clay minerals is greater than that of carbonate minerals (Zhang et al. 2015). The ability of clay minerals to retain oil is related to their lamellar crystal structure and electrical properties (Zhang et al. 2015). Illite and montmorillonite are composed of two silicon oxide tetrahedral wafers and one aluminum oxide octahedral wafer (Fig. 9.10). Al3+ in montmorillonite structure is easily replaced by divalent cations such as Mg2+ or Fe2+ . Al3+ easily replaces Si4+ in the structure of illite. Thus, the adsorption capacity of illite to soluble organic matter is greater than that of montmorillonite (Ross and Bustin 2007). The retained hydrocarbons amount and types are related to the type and quantity of organic parent materials. Organic matter is the source of retained hydrocarbon

Fig. 9.10 Crystal structure model and SEM images of clay minerals (Li et al 2020a, b), SEM images of kaolinite and illite are obtained from New Albany shale and montmorillonite from Tununk shale

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9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.11 Correlation between oil retention and organic matter abundance and lithofacies of Tertiary Sha-3 shale in Bohai Bay Basin. a The amount of retained hydrocarbon in shale is correlated with TOC; b The free hydrocarbon content of shale is correlated with TOC; c The bound hydrocarbon content of shale is correlated with TOC; d Correlation between pyrolysis S1 and TOC of shale extract samples; e Shale bound oil content is correlated with TOC

in shale, and the amount of retained hydrocarbon increases with the increase of organic matter abundance (Fig. 9.11). The organic-rich lithofacies mainly comes from deep lake to semi-deep lake deposits in saltwater, and planktonic algae mainly supply the organic matter, primarily type I organic matter. The organic matter is structurally composed of many aliphatic chains and a small number of aromatic rings. The organic-poor lithofacies is mainly from shallow lake sediments, mainly type II or type III kerogen. On the one hand, many aliphatic chains of type I kerogen fractured and generated crude oil during thermal evolution, while type III kerogen produced much few liquid hydrocarbons than type I kerogen due to aromatic ring condensation during maturation. On the other hand, due to the structural similarity between crude oil and type I kerogen, the two are more likely to combine in a mutually soluble state. The hydrocarbons can be dissolved in the organic matter in the mud shale. The hydrocarbons with dissolution index similar with that of kerogen are more likely to remain in the kerogen (Ritter 2003). The pyrolysis S1 of the extracted samples can reflect the hydrocarbons and organic solvents bound by kerogen in shale. The difference of pyrolysis S2 of the extracted samples represents the bound hydrocarbons that cannot be released at 300 °C in shale. The cross plot between the kerogen and TOC can reflect the hydrocarbon retention capacity of the kerogen. Compared with the sample containing type II–III kerogen, the S1 of the sample dominated by type I kerogen increases more obviously with the increase of TOC, indicating that the hydrocarbon retention capacity of type I kerogen is stronger.

9.4.2 The Retained Hydrocarbon Amount in Shale is Controlled by Pore Structure Shale pore structure is divided into four basic types, includes intragranular pore, fracture and organic pore, different pore structures have different genetic mechanisms (Fig. 9.12). Intergranular pore refers to the pore space between mineral particles,

9.4 Variation and Controlling Factors of Retained Oil in Shale

295

usually composed of primary pores, controlled by compression (Loucks and Reed 2014). The pore size of siliceous shale is more than 50–200 nm, while the pore size of clay shale is usually less than 50 nm (Fig. 9.12). Intragranular pores are formed inside mineral grains, and the pore size ranges from 10 nm to 10 µm, mainly composed of reformed secondary pores (Fig. 9.12). Fractures are elongated pore spaces usually formed by stress modification and source rock compaction diagenesis (Fig. 9.12). The varying range of fractures is much more lager (Jiu et al. 2013; Wang et al. 2015a; Zhang et al. 2017a, b). Organic pore refers to the pore space formed and distributed in organic matter, developed by the thermal evolution of organic matter (Fig. 9.13). Organic pores in the shale of the Sha-3 member in the Gaoliu area of Nanpu Sag are classified into three types (Ko et al. 2016) such as primary organic pores (Fig. 9.13a), secondary organic pore (Fig. 9.13b, c), and organic hole shrinkage joints (Fig. 9.13d). Primary organic pores are inherent in primary organic matter and dispersed in clusters in organic matter. In thermal cracking, secondary organic pores are formed after hydrocarbon migration to intergranular pores or interlayer fractures of inorganic minerals (Fig. 9.13b, Loucks and Reed 2014). The dissolution of calcareous minerals formed dissolution pores by organic acids (Fig. 9.13c). Organic shrinkage cracks are generally developed between organic matter and surrounding mineral particles, usually not naturally formed but related to sample preparation (Fig. 9.13d, Ko et al. 2016). Pore structure characteristics for three types of lithofacies shales are quite different (Fig. 9.14). Their characteristics of lithofacies, parameters of pyrolysis and retained oil are list in Table 9.1. The average pore volume, specific surface area, and pore size of clayey shale were 0.17 cm3 /100 g, 9.60 m2 /g, and 8.53 nm, respectively. The pore volume of siliceous shale is 1.23 cm3 /100 g, the specific surface area is 5.85 m2 /g, and the average pore size is 10.78 nm. The pore volume of clay shale is 0.95 cm3 / 100 g, the specific surface area is 2.10 m2 /g, and the pore size is 18.89 nm. There are two peaks of pore size near 3 nm and 10–20 nm, respectively. The shale with high content of carbonate minerals and high abundance of organic matter has larger main peak pores distributed around 10–20 nm and the secondary peak about 3 nm, with a high amount of retained hydrocarbon. The main peak of shale with low carbonate content and low organic matter abundance is smaller, distributed around 3 nm. The secondary peak is around 10–20 nm, and the retained hydrocarbon amount is low. N2 adsorption and desorption curve of unextracted shale samples reflect the controlling effect of pore structure on retained hydrocarbon quantity. Shale pores are characterized by multimolecular adsorption and many macropores. A comparative analysis of adsorbed hydrocarbon volume-relative pressure (Fig. 9.15) and the relationship between pore diameter and pore volume can be determined. Parallel slit pores are mainly developed in shale reservoirs, and multilayer molecular adsorption occurs. The amount of adsorbed hydrocarbon increases with relative pressure, and retained hydrocarbon amount is more in shale with high pressure. The pore difference between extracted and unextracted shale samples reflects the movable oil ratio in shale. Compared with unextracted samples, the pore volume of extracted samples increased to 1.2–3.4 times, the specific surface area increased by 1.01–1.35 times, and the average pore size decreased to 57–88%, indicating that

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9 Evaluation of Unconventional Shale Oil and Gas Resource

9.4 Variation and Controlling Factors of Retained Oil in Shale

297

◄Fig. 9.12 Pore development characteristics of inorganic minerals in Tertiary Sha-3 shale in Nanpu Sag, Bohai Bay Basin. a Siliceous minerals such as quartz and feldspar grains often develop intergranular pores, and a few intergranular pores are developed in quartz grains (G19-10-11, siliceous shale); b Common dissolution pores are developed in feldspar particles, forming intergranular pores with surrounding clay minerals (L68X1-11, clayey shale); c Intergranular pores and microfractures associated with calcareous minerals (G19-10-23, calcareous shale); d Intergranular pore and intergranular pore (G83-10-5, mixed shale); e Dissolution pores and microfractures are developed in calcareous minerals (G19-10-20, calcareous shale); f Dissolution pores developed in feldspar (G19-10-21, mixed shale); g Dissolution pores are developed in calcareous minerals (G19-10-20, calcareous shale); h Incomplete dissolution of pores in calcareous minerals (G80-12-7, calcareous shale); i Clay mineral development interlayer fractures (L68X1-11, clay shale); j Pyrite development grain pore (G18-9, calcareous shale); k Structural microfractures (G19-10-27, mixed shale); l Structural microfractures are partially filled with asphalt (G83-10-12, clayey shale)

Fig. 9.13 Organic pore development characteristics of shales in the third Member of Shahejie Formation in Nanpu Sag, Bohai Bay Basin. a Primary organic pores (L68X1-11, clayey shale); b Secondary organic pores associated with clay minerals (L68X1-11, clayey shale); c Secondary organic pores associated with calcareous minerals (G19-10-27, mixed shale); d Organic shrinkage fracture (G19-10-16, siliceous shale)

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Fig. 9.14 Pore size distribution characteristics of 24 unextracted shale samples in the Tertiary Sha3 member of Dongpu Sag, Bohai Bay Basin. Experimental results of N2 adsorption and desorption on shale samples. An isothermal N2 adsorption–desorption experiment was carried out in liquid nitrogen using Micromeritics ASAP2420 automatic specific surface and pore size analyzer, BET model (Brunauer-Emmett-Teller) was used to calculate specific surface area, BJH model (BarrettJohner-Halenda) was used to calculate the pore volume and pore size distribution. a–f represents six different lithofacies: a Horizontal lamellar calcareous shale; b Lenticular laminated calcareous shale; c Laminated clay shale; d Massive clay mudstone; e Laminated siliceous shale; f Massive siliceous mudstone

more small pores were exposed. The peak amplitude of pore volume distribution curve with pore size less than 10 nm increases significantly. The corresponding pore size position of the peak value changes little, reflecting that the pore value with pore size smaller than 10 nm is poorly connected, which belongs to “bound pore volume” and is filled with immovable “dead oil.” The peak of pore volume with pore size larger than 10–20 nm moves to the right, indicating that the larger the pore size, the better the oil mobility, and they are clearly reflected after extraction. Accordingly, the amount of oil and gas trapped in shale can be divided into three types: Bound unconnected “dead oil”, pore size less than 10 nm; Locally connected with “potentially movable

9.4 Variation and Controlling Factors of Retained Oil in Shale

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Table 9.1 Pyrolysis parameters of unextracted and extracted samples and retained oil of the Sha-3 member in the Dongpu Sag, Bohai Bay Basin, the locations of wells are illustrated in Fig. 9.3b Sample Wells number names

Depth (m)

Unextracted sample

Extracted sample Amount S1 (mg/ S2 (mg/ Tmax S1 (mg/ S2 (mg/ Tmax of g) g) (°C) g) g) (°C) retained oil (mg/ g)

1

Hu82

4216.8

0.32

0.8

447

0.04

0.72

450

32.26

2

Wen210

3848.2

1.39

2.27

444

0.05

1.38

446

2.09

3

Wen75

4226.79 2.31

2.22

436

0.03

0.72

443

0.4

4

Wen210

3778.5

1.07

1.96

442

0.05

0.89

442

1.75

5

Hu96

3885.29 3.22

8.82

441

0.04

3.83

444

0.01

6

Wei20

2641.57 1.18

16.23

431

0.21

12.81

434

8.21

7

Wen26

2967.5

3.92

18.66

435

0.23

13.24

436

0.98

8

Wei79-1

3349.8

1.89

13.49

440

0.14

9.35

440

0.07

9

Hu7-18

2120.8

0.43

12.42

435

0.24

10.76

436

0.02

10

Wei42

3277

0.09

0.48

437

0.05

0.43

435

0

11

Hu83

4187

1.25

0.89

421

0.18

0.39

438

0.27

12

PS13

4905.01 0.02

0.05

516

0.02

0.05

499

0.02

13

PS13

5011.01 0.01

0.05

509

0.02

0.06

470

0.02

14

Hu12-20

1777.71 12.62

33.23

434

0.78

13.59

432

1.03

15

Hu83

4318.3

0.12

440

0.06

0.14

435

3.23

16

Wen75

4215.31 2.94

7.8

447

0.13

5.62

450

2.28

17

PS4

4414.9

0.02

0.08

504

0.03

0.08

501

2.14

18

PS18

4076.64 0.24

0.26

454

0.08

0.23

449

9.34

19

Hu96

4040.58 0.49

1.47

445

0.06

0.98

444

3.81

20

Wen200-6 3729.4

2.05

2.22

443

0.07

1.04

446

5.12

21

PS12

4588.57 0.07

0.11

461

0.02

0.11

459

4.6

22

Wei42

3461.65 1.04

18.05

444

0.14

14.3

445

0.14

23

PS4

5193.7

0.03

0.04

467

0.07

0.05

422

4.79

24

PS6

4653

0.58

1.07

450

0.02

0.62

444

6.03

0.03

oil” aperture between 10 and 30 nm; Freely connected “movable oil” with pore diameter over 30 nm. The N2 adsorption–desorption curve of the extracted samples can reflect the actual pore structure (Fig. 9.16). Compared with the unextracted sample, the extracted sample exposes more pores, especially the microscopic pores occupied by hydrocarbons. The hysteresis of the N2 adsorption–desorption curve of the extracted samples changed significantly earlier than the extracted samples (Fig. 9.17), indicating more ink bottle like pores are exposed, and the increased pore space reflects the volume of movable shale oil under geological conditions.

300

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.15 N2 adsorption–desorption curve of unextracted shale samples from the third member of Shahejie Formation of Tertiary in Bohai Bay Basin. a–f represents six different lithofacies: a Horizontal lamellar calcareous shale; b Lenticular laminated calcareous shale; c Laminated clay shale; d Massive clay mudstone; e Laminated siliceous shale; f Massive siliceous mudstone

The retained hydrocarbons amount in the Tertiary Shahejie shale in Bohai Bay Basin is controlled by pore structure (Fig. 9.18). The pore volume with pore diameter larger than 10 nm is about 2–12 times that of less than 10 nm, with good connectivity and retained hydrocarbon, accounting for about 55% of the total amount. The pore volume with pore diameter less than 10 nm has a low proportion, poor connectivity, and a small amount of retained oil, accounting for about 45% of the total. The large pore ratio of calcite shale is higher than that of siliceous shale, and the siliceous shale is higher than that of clay shale. However, the clay minerals in inorganic minerals have a layered structure, and their oil and gas absorption are greater than that of quartz and carbonate minerals (Ross and Bustin 2007; Li et al. 2016). The oil saturation in small pore volume has a poor correlation with the content of quartz, carbonate minerals, and clay minerals. Still, a positive correlation with the abundance of organic matter (Fig. 9.19), the adsorption capacity of organic matter to hydrocarbons is much greater than that of inorganic minerals (Jarvie 2012; Han et al. 2015; Shao et al. 2018).

9.4 Variation and Controlling Factors of Retained Oil in Shale

301

Fig. 9.16 Comparison of pore size distribution curves between extracted and unextracted shale samples in the Tertiary Sha-3 member of Bohai Bay Basin (sample numbers, sources and characteristics are shown in Table 9.1)

9.4.3 The Retained Hydrocarbon Controlled by Surrounding Rock Conditions The amount of retained hydrocarbon in shale is controlled by the sealing property of the surrounding rock. The behavior of hydrocarbon molecules at the interface between organic-rich shale and organic-poor surrounding rock is influenced by buoyancy, hydrocarbon-generating expansion force, capillary force, and formation pressure. The former two can be used as the driving force for hydrocarbon expulsion from shale. The formation pressure prevents hydrocarbon from entering the surrounding rock, and the capillary force is related to the properties of the surrounding rock. The pore throat radius and sealing property of surrounding rock are the key factors affecting the amount of hydrocarbon retained in shale: When the expansion force of hydrocarbon generation from organic matter and other hydrocarbon expulsion forces are greater than the capillary resistance of surrounding rock, the remaining hydrocarbons are driven into surrounding rock and the amount of remaining oil in shale decreases; When the hydrocarbon expulsion force is less than the capillary resistance

302

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.17 Comparison of N2 adsorption–desorption curves between extracted and unextracted shale samples from the Tertiary Sha-3 member in Dongpu Sag, Bohai Bay Basin (sample numbers, sources and characteristics are shown in Table 9.1)

of surrounding rock, the remaining hydrocarbon in shale stays in the source rock, which leads to the increase of shale oil content (Jarvie 2012). The test results of hydrocarbon retention in continental shale are related to surrounding rock. The shales of the Sha-3 member in Dongpu Sag, Bohai Bay Basin are mostly thin-bedded and adjacent to salt rock, siltstone, argillaceous siltstone, or silty mudstone in space. This complex superimposed relationship can affect the hydrocarbon expulsion process from shales. Statistics on the oil content of 2057 shale samples from 156 wells in salt-bearing and salt-free zones showed that the average pyrolysis hydrocarbon S1 amount was 0.37–0.45 mg/g in the salt-bearing zone and was 0.02–0.10 mg/g in the salt-free zone (Fig. 9.20a). Figure 9.20b, c respectively show the comparison of the characteristics of chloroform asphalt “A” and hydrocarbon components in the salt-bearing and salt-free mud shale. It is found that the content of saturated hydrocarbon in salt-bearing shale is higher than that in non-salt-bearing shale. In comparison, the content of non-hydrocarbon and asphaltene components is higher in non-salt-bearing shale. These results indicate that the retained hydrocarbon amount in shale in the salt-bearing zone is much higher than that

303

Proportion of pore volume (%)

9.4 Variation and Controlling Factors of Retained Oil in Shale

Sample number Ineffective pores ( 2.0%, and almost all liquid oil in shale disappears. Shale oil is gradually transformed into shale gas until no gas is discharged, indicating the formation of the active source-rock depth limit (Pang et al. 2020). The study also shows that at the same depth, Ro value of shale is higher in the salt-bearing zone (Fig. 9.23a1) than in the salt-free zone (Fig. 9.23a2), which is conducive to organic matter transformation and shale oil generation and retention. The adsorption of source rock controls the variation of retained hydrocarbon in shale with burial depth. The increase of burial depth results in the densification of shale and affects its hydrocarbon retention ability. N2 adsorption–desorption experiments show that the pore volume and average pore size of shale decrease with the increase of burial depth, which leads to the decline in hydrocarbon retention capacity and the reduction of actual hydrocarbon retention (Fig. 9.24a). For the extracted samples, the pore volume of the 5193.7 m buried sample is 58.50% of that of the 1777.71 m buried sample, and the average pore size is only 31.04% of the latter. The specific surface area was positively correlated with the depth above 4200 m and decreased with the increase of depth below 4200 m, indicating that the densification of shale in the early stage of increasing burial depth was mainly caused by the large pores turning into small pores under the action of compaction. The small pores gradually disappeared under the overburden pressure in the late stage. Compaction with the increase of burial depth is the main reason for enhancing the densification of shale and reducing the amount of retained hydrocarbon (Selley 1978; Magara 1980). On the other hand, under the appropriate degree of thermal evolution, the structure of organic matter changes, and many organic pores are formed, which provide storage space for retained hydrocarbons (Sun and Luo 2016). The internal pores of organic

308

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.24 Variation of shale pore structure with depth and its controlling effect on retained hydrocarbon content of source rocks in the Tertiary Sha-3 member of Dongpu Sag, Bohai Bay Basin. a Shale pore structure changes with depth: a1 Average pore size and depth, a2 Pore volume and depth, a3 Specific surface area and depth; b Organic pore development characteristics of shale: b1 Primary organic pore (sample 22); b2 Primary organic pore (sample 3); b3 and b4 Secondary organic pores (sample 12)

matter in this study are very rare (Fig. 9.24b). The organic pores observed by SEM are mainly of primary origin, which is found in lamellar shale, and the single pore diameter is usually larger than 10 µm. Organic matter pores related to thermal evolution are rare in the research area, only found in sample 12, and the burial depth of 4905.01 m has wholly entered the gas generation stage. Organic pores in source rocks of the Sha-3 member in Bohai Bay Basin have little effect on the amount of retained hydrocarbons.

9.5 Mobility of Shale Oil and Its Genetic Mechanism Shale oil’s mobility determines its recovery. The exploration and development practice shows that high porosity and permeability, high gas-oil ratio, and high formation pressure are conducive to the efficient recovery of shale oil (Nojabaei et al. 2013; Teklu et al. 2014; Akkutlu et al. 2017; Alharthy et al. 2018; Li et al. 2019; Du et al. 2020). Shale oil recovery can also be enhanced through fracturing and other interventions. The average global recovery factor of marine shale oil is between 4.3 and 5.7%, about 5.0% (EIA 2012); Continental shale oil has not been commercially exploited on a large scale, and there is a lack of data on recovery factor. This paper mainly conducts research through physical simulation experiments to discuss the oil mobility in continental shale and its major controlling factors.

9.5 Mobility of Shale Oil and Its Genetic Mechanism

309

9.5.1 The Principle of Physical Experiment on Shale Oil Mobility Principle of the simulation experiment. This study focuses on simulating the variation characteristics of movable oil ratio in rock media with different porosity, permeability, kerogen content, clay mineral content, and crude oil properties. All the cores used in the physical simulation experiments were artificially prepared by the Percolation Physics Laboratory of China University of Petroleum at Beijing (Fig. 9.25a). The artificial cores are made of quartz sand and epoxy resin. When preparing the cores, the relative ratio of the content of these two raw materials should be determined first, generally 12:1, and evenly placed into the mold (Fig. 9.25b). Then different variables are considered, including different porosity and permeability, different types and contents of clay minerals, crude oils with different viscosity, and different kerogen contents. After that, all the materials are mixed and evenly distributed in the mold, and the mold is put into the three-axis press, which slowly rises from zero pressure to the design value, and keeps the pressure for 5 h, and the pressure is slowly lowered to zero to stop the operation of the press. Finally, 48 h after core solidification, the mold is removed, cubic core modules with a side length of about 7 cm are taken out, and 2–3 artificial cores with a diameter of 2.50 ± 0.03 cm and a length of 5.00 ± 0.04 cm are taken out of the modules (Fig. 9.25c). A total of 38 artificial cores were prepared in this study. According to the four main controlling factors in the experimental scheme, these artificial cores were divided into four groups. In group 1, the variable factors were porosity and permeability, and six artificial cores (A1–A6) were prepared under different pressure conditions (10, 20, 30, 40, 50, and 60 MPa). In the second group, the variable factors are the types of clay minerals (illite, kaolinite, chlorite, and montmorillonite) and their contents. Under the premise of the pressure being 20 MPa and the ratio of quartz sand to the epoxy resin being unchanged, the single type of clay minerals with the content ratios of 3%, 6%, 9%, 12%, and 15% were added uniformly respectively. The artificial cores with illite as a variable were numbered B1–B5, and there were five cores in total; the artificial cores with kaolinite as a variable were numbered C1–C5, and there were five cores in total; the artificial cores with chlorite as variable are D1–D5, a total of 5 cores; the artificial cores with montmorillonite as a variable were E1–E3, a total of 3 cores. In the third group, the variable factor is the crude oil viscosity, and the parameters set in the preparation of this type of core are the same and consistent with A3 (F1–F8). The variable factor was kerogen content in the fourth group, which was prepared based on shale samples from the Sha-3 member in the Gaoliu area, Nanpu Sag. Under the premise that the pressure is 20 MPa and the ratio of quartz sand and epoxy resin is unchanged, kerogen (G1–G6) with the content ratios of 0, 3, 6, 9, 12, and 15% is added evenly. The basic physical properties of all cores were measured by gas measurement before the experiment. Simulation experiment process. The physical simulation experiment of nuclear magnetic displacement was completed in Suzhou Taiyu Testing Co., LTD. The testing process is shown in Fig. 9.26. The detection instrument was MESOMR23-60H-I

310

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.25 Physical simulation experiment equipment for artificial core preparation and obtained artificial core samples. a Artificial core compactor; b Artificial core mold; c Artificial core photographs A–E series (c1) and F–G series (c2)

Nuclear Magnetic Resonance (NMR) imaging analyzer with a resonance frequency of 23 MHz, a magnetic intensity of 0.5 T, and a magnetic temperature of 32 ± 0.01 °C. The test temperature was 24.5 °C, and humidity was 45.9%. The test was completed in seven steps: The first step is to conduct preliminary treatment for the core. The core cutter is used to cut the experimental core to about 60 mm. After grinding the end, the core length, diameter, and other basic parameters are measured. The second step is to test the core porosity and permeability data. The core is dried for 24 h at 105 °C and put into the core porosity and permeability tester to test the core porosity and permeability. In the third step, the sample was saturated with manganese chloride solution and vacuumed with manganese chloride solution (mass concentration 50%) for eight hours using a vacuum saturation device. In the fourth step, the sample was saturated with crude oil and injected into the crude oil at a flow rate of 0.1 mL/min. The saturated oil cores were placed in white oil and left standing. F1–F8 series artificial cores were saturated with 5#, 6#, 7#, 8#, 9#, 10#, 12#, and 15# crude oil, respectively. The fifth step is to debug NMR parameters. Using NMR analysis application software, the center frequency, pulse width, TW time, and other equipment parameters are tested using standard samples and water film standard samples. The nuclear magnetic resonance (NMR) test was carried out on the rock sample at the sixth step. After the core was placed into the gripper, T2 spectrum cumulative NMR sampling test was carried out to test the T2 spectrum of the core after saturated oil. At the seventh step, the core recovery factor was calculated. Manganese chloride solution (50% mass concentration) was injected at

9.5 Mobility of Shale Oil and Its Genetic Mechanism

311

Fig. 9.26 Nuclear magnetic resonance displacement system and its flow chart for shale oil dynamic study

the flow rate of 0.1 mL/min, and 2 MPa followed the confining pressure. After water flooding to 98% water, nuclear magnetic resonance test was performed, and the core recovery factor was calculated. The experimental results were quantitatively characterized. Figure 9.27 shows the comparison of NMR curves and signals of 24 oil-bearing artificial cores in five groups before and after the displacement experiment. The NMR curve of the retained oil in the artificial cores before displacement represents the pore size distribution of the shale sample in the oil-saturated state, which is represented by a solid line. The NMR curve after oil displacement represents the pore size distribution of immovable residual oil, represented by dotted lines. The ratio of the difference between them (Qbeginning − Qresidual ) and the area enclosed by the abscissa and the original oilbearing area is the ratio of movable oil (Rmovable ). The higher the relaxation time T2 value is, the larger the pore size is; the higher the NMR signal amount is, the larger the pore volume is, and the higher the oil content is. The T2 spectrum curve of the core generally has the characteristics of doublet type, and the relaxation time range of the main peak and the secondary peak is 50–500 ms and 1–20 ms, respectively, indicating that these artificial cores mainly develop two types of pore size. The crude oil is mainly charged in a relatively large pore size range, and the content is very low in a small pore size range. After displacement, the content of crude oil in the larger pore size decreases obviously. In comparison, the content of crude oil in the smaller pore size does not change significantly, indicating that the smaller of pores, the less of retained oil. The relationship between the movable and immovable oil ratios in shale samples and curve signals and the correlation between them is expressed by Eqs. 9.1–9.3. Rmovable =

Q begin − Q remain Q begin

(9.1)

312

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.27 Moving oil signal variation characteristics and test results of five groups of 24 oil-bearing artificial cores in NMR flooding simulation experiment. The solid line area represents the original retained hydrocarbon amount before the displacement experiment, and the dotted line area represents the residual hydrocarbon amount after the displacement experiment: a test results of artificial core (A1–A6); b artificial core test results (B1–B5); c artificial core test results (C1–C5); d artificial core test results (D1–D5); e artificial core test results (E1–E3)

Rimmovable =

Q remain Q begin

Rmovable + Rimmovable = 1

(9.2) (9.3)

9.5.2 Porosity and Permeability Controlling on the Movable Oil Ratio In the simulation experiment of, Group A–G, the movable oil ratio of core samples (A1–A6) in Group A changed the most, from 75.63 to 1.21% (Fig. 9.28). The corresponding porosity decreased from 27.49 to 1.54%, and the permeability decreased from 1432.77 × 10–3 to 0.0022 × 10–3 µm2 . The movable oil ratio is positively correlated with core porosity and permeability, and the correlation coefficients are R2 = 0.971 and R2 = 0.950, respectively as in Fig. 9.28. The experimental results clearly show that the better the porosity and permeability of shale is, the higher the percentage of movable oil in the retained oil is, and the more favorable it is to development and utilization.

9.5 Mobility of Shale Oil and Its Genetic Mechanism

313

Fig. 9.28 Variation of movable oil ratio with core permeability in NMR flooding simulation experiment (Group A cores)

9.5.3 The Type and Content of Clay Minerals Control the Percentage of Movable Oil With the increase of clay mineral content, the ratio of movable oil in shale decreases, and different clay minerals have different effects on the ratio (Fig. 9.29). The movable oil ratio of core samples containing illite in Group B has the slightest variation, mainly distributed between 60.65 and 67.60%, with an average of 65.34%; The percentage of movable oil in core samples containing kaolinite in Group C ranges from 66.74 to 78.46%, with an average of 72.02%. The correlation between movable oil ratio and clay mineral content is weak, R2 = 0.16 for Group B and R2 = 0.022 for Group C, respectively, indicating that illite and kaolinite content have weak adsorbability to movable oil (Fig. 9.29b, c). The movable oil ratios containing chlorite in Group D ranged from 48.70 to 74.79%, with an average of 66.51%. The percentage of movable oil containing montmorillonite in Group E ranged from 47.92 to 62.14%, with an average of 53.54%. The correlation between movable oil ratio and clay mineral content is R2 = 0.752 for Group D and R2 = 0.883 for Group E, respectively. The percentage of movable oil decreases with the increase of clay mineral content, which indicates that montmorillonite and chlorite have an inhibitory effect on the mobility of crude oil (Fig. 9.29d, e). The specific surface area of the pores in clay minerals are large, but the pore size is small, and the oil and gas mainly exist in an adsorption state, which is not conducive to the flow of oil and gas. The T2 spectrum before and after displacement shows that the higher the content of clay minerals is, the lower the ratio of movable oil is. Different clay minerals have different effects on hydrocarbon adsorption capacity (Passey et al. 2010; Ji et al. 2012; Guo et al. 2014; Zheng et al. 2018), mainly related to the different crystal structures and specific surface area of clay minerals. Montmorillonite has a typical structure of 2:1 type water-aluminum layer and silicon-oxygen layer, with the internal and external specific surface area of

314

9 Evaluation of Unconventional Shale Oil and Gas Resource

Fig. 9.29 Variation characteristics of movable oil ratio with clay mineral content and type in NMR displacement physical simulation experiment. Cores of Group B and C contain illite and kaolinite, and cores of Group D and E contain chlorite and montmorillonite, respectively

the two layers, the total specific surface area is the largest, the adsorption capacity of hydrocarbons is also the strongest (Ji et al. 2012; Guo et al. 2014). The influence of four clay minerals on the movability of crude oil is montmorillonite ≥ chlorite > kaolinite > illite.

9.5.4 Oil Viscosity Controlling on Shale Movable Oil Ratio Figure 9.30a shows the simulated experimental results of displacement of crude oil with different viscosity in core samples of Group F. The ratio of movable oil in Group F ranged from 47.93 to 52.27%, with an average of 50.56%; The NMR curves of saturated oil and residual oil show a decreasing trend with the increase of crude oil viscosity, indicating that the ratio of movable oil decreases (Fig. 9.30b1). There are obvious differences in crude oil properties between continental shale oil in China and marine shale oil in North America: The viscosity of north American marine shale oil is relatively light, while that of continental shale oil in China is high in wax content and viscosity, which is an important reason for the high production of shale oil in Jiyang Depression of Bohai Bay Basin in the early stage and the sharp drop in the later stage (Wang et al. 2013). The details are shown in Fig. 9.30b2, indicating that shale oil viscosity can inhibit shale oil mobility and thus affect shale oil production. The experimental results only qualitatively reflect the relationship between the viscosity and the movability of crude oil, in actual geological conditions, the viscosity of crude oil varies in a wide range, and the relationship between the viscosity and the movability of crude oil is more complicated due to the influence of temperature, pressure, components, and other conditions.

9.5 Mobility of Shale Oil and Its Genetic Mechanism

315

Movable oil ratio (%)

Viscosity (mPa·s)

B2 Retained oil

Oil production/day (t/d)

F1-F8 Signal amount

B1

Residual oil

Viscosity (mPa·s) T2/ms

A

B

Fig. 9.30 Variation characteristics of movable oil ratio in rock samples with different crude oil viscosity under physical simulation experimental conditions. a Movable oil signal changes of core F Group in NMR displacement simulation experiment (core F1–F8); b Movable oil ratio changes with crude oil viscosity: b1 NMR flooding simulation results (F1–F8 core), b2 Relationship between crude oil viscosity and shale oil daily production in the Jiyang Depression, Bohai Bay Basin (Ning et al. 2017)

9.5.5 Kerogen Content Controlling on the Percentage of Movable Oil Clay minerals and organic matter have a strong adsorption effect on oil and gas because of their large specific surface area (Guo et al. 2014). At present, most studies are focused on the comprehensive impact of the two factors on crude oil retention, but the quantitative research of every single factor is weak. Figure 9.31a is the T2 NMR spectrum of retained oil obtained from core (Group G) samples with different kerogen contents in this study, reflecting the distribution characteristics of the mobility ratio of crude oil, varying between 42.80 and 65.38%, with an average of 52.31%. In addition, with the increase of kerogen content, the movable oil ratio of core changes regularly before and after displacement (Fig. 9.31b1). The higher the kerogen content, the lower the movable oil ratio, the correlation coefficient R2 = 0.758 (Fig. 9.31b1). The experimental results of pyrolysis of shale oil samples from four wells in the Jiyang Depression also show similar characteristics. The S1-1 + S1-2 or released hydrocarbons before 350 °C can be used to characterize the free hydrocarbons or movable oil in shale; The index of S2-1 between 350 and 450 °C can be used to characterize the hydrocarbon in adsorption state or immovable oil in shale. The ratio of movable oil to immovable oil decreases with the increase of TOC content, indicating that shale oil mainly exists in the pore space of kerogen by adsorption, which leads to a decrease in the proportion of movable oil (Li et al. 2017).

316

9 Evaluation of Unconventional Shale Oil and Gas Resource Movable oil ratio (%)

Retained oil

Residual oil

B2

Kerogen content (%)

S1-1+S1-2/S2-1 (%)

G1-G6 Signal amount

B1

T2/ms

A

TOC (%)

B

Fig. 9.31 Variation characteristics of movable oil ratio in shale with kerogen content in NMR displacement simulation experiment. a Variation characteristics of movable oil signal of Group Cores (G1–G6); b Movable oil ratio varies with kerogen content: b1 Results of Group G simulation experiment (G1–G6), b2 Correlation statistics of tertiary organic carbon content and movable oil ratio in Bohai Bay Basin (Li et al. 2017), S1-1 + S1-2 /S2-1 is the ratio of free hydrocarbon to adsorbed hydrocarbon in thermolysis hydrocarbon analysis method. FY1 is well Fanye 1; LY1 is Liye 1 well; L69 is Luo 69 well; NY1 is Niuye1 well

9.6 Prediction and Evaluation of Shale Oil Resources The fundamental problem of shale oil resource evaluation is to make clear the total amount of shale oil and its mobility in geological conditions (Wang et al. 2013; Zou et al. 2013b). However, the mobility of shale oil is currently not accounted. Taking shales in the Sha-3 member in the Gaoliu area, Nanpu Sag, Bohai Bay Basin as an example, the total hydrocarbons amount and movable potential resources of shale were evaluated by volume method and Monte Carlo simulation using the key parameters obtained from the above study.

9.6.1 Principle of Evaluation for Potential Recoverable Resources of Shale Oil The exploration and evaluation of continental shale oil resources in China are still in the initial stage (Zhang et al. 2012; Liu et al. 2014). The volume method is a more suitable method (Song et al. 2013; Wang et al. 2013, 2015b; Xue et al. 2015; Liu et al. 2016; Lu 2017). Key geological parameters to be obtained mainly include shale distribution area, thickness, density, oil content, movable oil ratio, and recovery factor (Liu et al. 2014; Xue et al. 2015; Li et al. 2016; Lu 2017). The relationship between these six key parameters and the potential recoverable shale oil resources is expressed in Eq. 9.4:

9.6 Prediction and Evaluation of Shale Oil Resources

Q = S × H × D × Kr × Km × E

317

(9.4)

In Eq. 9.4, Q—Potential recoverable resources of shale oil, tons; S—Shale oil distribution area, km2 ; H—average thickness of shale oil-bearing formations, m; D—Density of shale oil-bearing formations, t/m3 ; Kr—average oil content within shale, percentage by weight of rock (%); Km—movable oil ratio, percentage of the total oil amount in shale (%); E—Shale oil resource recovery factor (%).

9.6.2 Key Parameters of Recoverable Oil and Gas Resources Evaluation Geological characteristics of shale oil distribution. Parameter 1 is the shale distribution area (S), which refers to the horizontal distribution range of the source rocks containing shale oil resources, usually determined based on seismic data and drilling results. The organic parent material abundance (TOC), organic parent material type (KTI), and thermal evolution degree (Ro) of effective source rocks should meet certain standards. The shales of the Sha-3 member in Nanpu Sag of Bohai Bay Basin are developed in the Gaoliu area with large thickness, high TOC content, good organic matter type, and moderate maturity. It is a set of high-quality hydrocarbon source rocks and is conducive to the formation and distribution of shale oil resources (Fig. 9.32). Parameter 2 is the thickness of shale oil distribution (H). H refers to the longitudinal distribution range of the source rock containing shale oil resources and is usually determined based on seismic data and drilling results. Shales with monolayer thickness below a critical condition (< 1 m) need to be excluded, and the effective monolayer thickness is accumulated to make a plane equivalent map. The thickness of shales in the Sha-3 member in the Gaoliu area mainly ranges from 300 to 700 m, with an average of 500 m (Fig. 9.32a). The TOC content in the source rocks mainly ranges from 1.5 to 4.0%, with an average of about 2.5% (Fig. 9.32b). Organic matter types are mainly type I–II (Fig. 9.32c), and maturity is between 0.8 and 1.0% in the stage of large oil generation (Fig. 9.32d). Parameter 3 is shale density (D), which refers to the specific gravity of shale oil source rock per unit volume, usually based on logging data or core sampling tests. The density of shale in the Sha-3 member in the Gaoliu area increases from shallow to deep. At a depth of 500 m, the average density of shale is less than 2.40 g/cm3 ; About 2.40 g/cm3 in 500–3000 m; At 3000–4000 m, it is 2.44 g/cm3 ; After 4000 m, the average density of shale is greater than 2.56 g/cm3 , and then variation range is small (Hou 2014). Unconventional oil and gas reservoirs that meet current commercial development conditions and are expected to achieve high production are called sweet spots and are subdivided into sweet layers or sweet zones (Zou et al. 2012). Figure 9.32e divides the shale oil sweet horizon into the best favorable sweet horizon (I), better favorable sweet horizon (II), non-sweet horizon (III), and the non-resource horizon (IV).

318

9 Evaluation of Unconventional Shale Oil and Gas Resource Strata Submember

Oil Group

Thick ness

Lithology/Resistance

Sweet spots grade

Sha3 3 submember

II

A

B

IV

III

C

D

Sha3 5 submember

Sha3 4 submember

E I

III

Fig. 9.32 Geological and geochemical characteristics of dark shale of Tertiary Sha-3 member in the Gaoliu area, Nanpu Sag, Bohai Bay Basin. a Dark shale thickness (H, M); b Organic parent material abundance (TOC, %); c Organic parent material type (KTI); d Degree of thermal evolution of organic parent material (Ro, %); e Shale sweet layer classification: the best favorable sweet layers (I), better favorable sweet layers (II), non-sweet layers (III) and non-resource layers (IV)

Shale oil content (Kro) or pore oil saturation (Sro). The shale oil content refers to the oil amount per unit weight of shale, a comprehensive characterization of movable oil and immovable oil, and a key parameter to calculate shale oil resources by volume method. The commonly used oil content parameter is the corrected pyrolytic hydrocarbon S1 or chloroform bitumen “A” (Xue et al. 2015; Jiang et al. 2016). The Soxhlet extraction method was used to extract hydrocarbons from shale pores, and then TOC and rock pyrolysis tests were carried out, respectively, to characterize oil content quantitatively. There is a correlation between organic geochemical parameters of shale before and after extraction, such as TOC, Tmax, S1 , and S2 . Overall, the geochemical parameters after extraction are positively correlated, and the values of TOC, Tmax, S1 , and S2 are also higher after extraction. The pore saturation rate of oil in the shale of Sha-3 member in the Gaoliu area of Nanpu Sag varies greatly. The oil content obtained by the pyrolysis method and NMR method is different: calcareous shale has the highest oil content, and the average values of the two ways are 8.4% and 34.4%, respectively; the average oil content of clay shale is 6.8% and 21.04%, respectively; siliceous shale has the lowest oil content, averaging 1.9% and 10.03%. The results of measured oil content in different shales by different methods are summarized in Table 9.2. Shale oil mobility and its variation characteristics. Mobility (Km) of shale oil refers to the percentage of retained hydrocarbon in shale that can be transported outward under certain pressure driving conditions. Based on the physical simulation results of the movable oil ratio of shale in the Sha-3 member in the Gaoliu area of Nanpu Sag, a quantitative correlation model for movable oil ratio was established (Eq. 9.5). The distribution characteristics of related parameters are listed in Table 9.3: The porosity of shale ranges from 2.9 to 12.3%, with an average of 6.5%; the content of montmorillonite in clay minerals ranges from 3.4 to 21.4%, with an average of

9.6 Prediction and Evaluation of Shale Oil Resources

319

Table 9.2 Comparison of oil contents based on pyrolysis and NMR methods for four groups of shales Lithofacies type

Pyrolysis oil content (%)

NMR method oil content (%)

Interval value

Interval value

Average value

Average value

Siliceous shale

0.7–46

1.9

9.46–10.77

10.03

Calcareous shale

8.4

8.4

17.05–52.28

34.4

Clay shale

1.5–15.9

6.8

12.88–33.28

21.04

Mixed shale

0.3–64.1

20.4

10.43–57.72

36.14

10.7%; the organic carbon content ranged from 0.5 to 3.1%, with an average of 1.3%; the ratio of movable oil of shale in the study area is between 47.3 and 69.5%, with an average of 60.5%. At the same time, the movable oil ratio of 262 unconventional hydrocarbons reservoirs in 12 petroliferous basins obtained by different research methods was statistically analyzed (Fig. 9.33). It is found that the mobility ratio of tight oil is between 16.1 and 63.9% with an average of 36.5%, and that of shale oil is between 3.1 and 60.37% with an average of 27.6%. The movable oil ratio of shale obtained in this paper is normal. Ytheor y = 0.48X 1 − 1.45X 2 − 0.23X 3 + 73.13

(9.5)

Table 9.3 Associated parameters of Tertiary Sha-3 member shales in the Gaoliu area of Nanpu Sag Sample

Yactual (%)

Porosity X1 (%)

Montmorillonite content X2 (%)

Organic matter content X3 (%)

Ytheory (%)

Error (%)

G19-10-12

57.14

6.35

13.32

0.54

56.74

G19-10-16

64.00

10.48

14.30

0.61

57.29

− 6.71

L68X1-6

75.00

4.96

11.45

0.59

58.77

− 16.23

L68X1-7

57.14

4.66

14.04

1.00

54.78

− 2.36

L68X1-17

85.71

7.66

5.62

0.57

68.53

− 17.18

L68X1-4

65.00

7.02

4.32

0.97

70.01

5.01

G19-10-10

50.00

5.36

11.97

0.62

58.20

8.20

G83-10-5

62.20

12.32

7.35

1.99

67.93

5.73

G83-10-7

80.00

4.16

3.35

0.70

70.11

− 9.89

G83-10-6

58.70

4.92

7.32

1.12

64.62

5.92

G19-10-9

52.38

4.54

14.72

0.73

53.80

1.42

G80-12-10

45.81

3.31

21.41

2.73

43.05

− 2.76

G80-12-1

65.06

11.62

10.79

3.12

62.34

− 2.72

G19-10-21

55.54

2.88

9.27

2.23

60.56

5.02

− 0.40

320

9 Evaluation of Unconventional Shale Oil and Gas Resource Tight oil/gas

Frequency

Shale oil/gas

Average:47.51%

Average:37.46%

Movable fluid saturation/% Fig. 9.33 Statistical analysis results of movable hydrocarbon ratio of global unconventional tight oil and shale oil (Li 2019)

In Eq. 9.5, Y theory —Movable oil ratio of shale, %; X 1 —Porosity, %; X 2 —Montmorillonite content, %; X 3 —Organic matter content, %. Shale oil recovery factor and variation characteristics. The Shale oil recovery factor (E) is the percentage of the total oil produced with current technology. It is a key parameter for evaluating potential recoverable oil and gas resources. As there is no continental shale reservoir that has been commercially exploited in China, this parameter is obtained in the laboratory or inferred from the geological conditions of the current shale reservoir. This paper collects shale oil recovery in different petroliferous basins (Table 9.4) published in literatures. According to the statistical analysis, the shale oil recovery rate under the current technical conditions is between 3.0 and 10.0%, with an average of 7.2%.

9.6.3 Prediction and Evaluation of Recoverable Shale Oil Resources This study selected the Gaoliu area in Nanpu Sag, Bohai Bay Basin, China, to evaluate shale oil potential recoverable resources and predict sweet spots. Determine the critical conditions for shale oil resource discrimination. The distribution range of shale oil is predicted, and then the distribution characteristics of shale oil sweet spot are determined and evaluated. Shale oil sweet spots refer to the shale oil distribution areas where high productivity can be obtained based on existing data and technology. They are characterized by large thickness and continuous and widespread distribution, high abundance of organic parent material and

9.6 Prediction and Evaluation of Shale Oil Resources

321

Table 9.4 Associated parameters for the evaluation of shale oil in Tertiary Sha-3 member in the Gaoliu area Type

Movable oil/ gas ratio (%)

Sample umber (unit)

Research area and horizon (area names)

Data source (references)

Range of changes (%)

Tight oil

8.61–57.5 (mean 30.7)

12

/

Lei (2017)

50.47

/

Penglaizhen group, west Sichuan

Sima et al. (2017)

53.22–73.3 (mean 63.9)

8

Yanchang group, Ordos Basin Gao et al. (2018)

Minimum value: 15 Average value: 30 Maximum value: 65

34.5–83.2

/

Yanchang group, Ordos Basin Wang et al. (2017)

9.7–29.83 (mean 16.1)

6

Yanchang group, Ordos Basin Bai et al. (2018)

29.44–68.92 (mean 46.7)

21

Lu’er section, jimusar depression, Junggar Basin

Li et al. (2018a)

2.16–46.55 (mean 19.6)

9

3rd section of Shahejie formation, Bohai Bay Basin

Chen (2015)

20.78–45.67 (mean 34.2)

4

Yanchang group, Ordos Basin Gao et al. (2018)

16.27–65.67 (mean 44.9)

24

Yanchang group, Ordos Basin Wu and Zhao (2017)

10.73–81.86 (mean 48.35)

264

Yanchang group, Ordos Basin Gao and Li (2015)

2.16–55.94 (mean 27.48)

15

Yanchang group, Ordos Basin Li et al. (2018b)

10.99–61.99 (mean 34.86)

26

Yanchang group, Ordos Basin Li et al. (2019)

5.38–32.67 (mean 19.5)

12

He8, Sudong area, Ordos Basin

Tight gas

2.18–62.57 (mean 30.43)

Shale oil

Ming et al. (2015)

He8, Sudong area, Ordos Basin

7.73–83.62 (mean 41)

8

He8 and Shan1, Suxi area, Ordos Basin

Liu et al. (2016)

25.33–97.57 (mean 60.37)

30

Shahejie formation, Dongying Li et al. depression, Bohai Bay Basin (2018c)

13.54–89.11 (mean 29.36)

17

Barnett Shale

Han et al. (2015)

4.2–16.63 (mean 9.4)

50

Saxony Basin

Zink et al. (2016)

17.30–69.28 (mean 48.15)

30

Lucaogou formation, Junggar Basin

Guo et al. (2014)

7.12–91.29 (mean 29.31)

29

Qianjiang formation, Qianjiang Basin

Chen et al. (2018b)

Minimum value: 20 Average value: 40 Maximum value: 70 Minimum value: 10 Average value: 25 Maximum value: 60

(continued)

322

9 Evaluation of Unconventional Shale Oil and Gas Resource

Table 9.4 (continued) Type

Shale gas

Movable oil/ gas ratio (%)

Sample umber (unit)

Research area and horizon (area names)

Data source (references)

> 10.0

/

Posidonia shale

> 30.0

/

Vaca Muerta shale

Ziegs et al. (2017)

3.06–16.25

/

Jiyang depression, Bohai Bay Basin

Sang et al. (2017)

24.3–24.7

2

4th section of shahejie formation, Dongying depression, Bohai Bay Basin

Li (2014)

8–28

/

3rd section of shahejie formation, Bohai Bay Basin

Zhang et al. (2014)

9–30

/

4th section of shahejie formation, Bohai Bay Basin

23.19–30.84 (mean 27.2)

48

Longmaxi formation, Sichuan Zhou et al. Basin (2016)

23.6–41.4 (mean 31)

4

Shahejie formation, Dongpu Sag, Bohai Bay Basin

Wang et al. (2015a)

Range of changes (%)

Minimum value: 15 Average value: 30 Maximum value: 65

mainly containing type I Kerogen, moderate thermal evolution degree and high gasoil ratio in shale oil, strong sealing of surrounding rock and high formation pressure, well-developed shale lamina and high content of brittle minerals. The discriminant index and identifying standards are only of reference significance and change with the improvement of technical level. Predicting the favorable distribution area of sweet spots. The most favorable target strata in the Tertiary Sha-3 member of the study area are firstly selected according to the sealing property of the surrounding rocks. According to the actual geological conditions of the study area, five key parameters of shale distribution area (S), shale thickness (H), organic parent material abundance (TOC), organic parent material type (KTI), and current hydrocarbon generation stage (Ro) and their discriminant criteria were secondly determined: H > 100 m, TOC > 2.0%, KTI > 75, Ro = 0.8–1.35%. Finally, the target horizons that meet the requirements of the above indicators are delineated and quantitatively evaluated by overlapping these effective parameters. Based on the above methods, the sweet spots of shale oil in the Sha-3 member are predicted, as shown in Fig. 9.34a. It covers an area of 8.2 km2 , with an average thickness of 500 m, TOC ≈ 2.0%, KTI ≈ 75, and Ro = 1.0%. According to Formula 9.4, the amount of shale oil resources in the study area is 1.48 × 108 t, accounting for about 50% of the total amount of shale oil in the area. Evaluation of shale recoverable oil resources. The volume method evaluates the amount of shale movable oil resources in the Sha-3 member in the Gaoliu area of Nanpu Sag. The values of six key parameters in Eq. 9.4 are as follows: shale

9.7 Summary

323

Fig. 9.34 Prediction and evaluation results of shale oil distribution in the Tertiary Sha-3 member in the Gaoliu area, Nanpu Sag, Bohai Bay Basin. a Prediction results and classification of plane distribution characteristics of movable oil sweet zone; b Monte Carlo simulation results of shale oil resources: potential movable shale oil amount (b1) and recoverable shale oil resources (b2)

distribution area (S) and thickness (H) shown in Fig. 9.32a; Shale density (D) varied from 2.23 to 2.65 g/cm3 , with an average of 2.45 g/cm3 (Ma and Xie 2018); The oil content (Kr) of shales of four lithofacies ranged from 1.9 to 20.4%, with an average of 2.5%; Movable oil ratio (Km) ranged from 47.3 to 69.5%, with an average of 60.5%. The total amount of movable oil and potential recoverable resources of shale in the study area are evaluated by Monte Carlo simulation technology, as shown in Fig. 9.34b. The results show that the movable oil amount corresponds to 1.32 × 108 t and 1.62 × 108 t when the cumulative probability is 10% and 90%, respectively. The movable oil amount is 1.48 × 108 t corresponds to a cumulative probability of 50%. The mode and average values are 1.50 × 108 and 1.50 × 108 t. The recoverable shale oil resources are 0.07 × 108 t and 0.13 × 108 t, respectively, with the cumulative probability of 10% and 90%, the corresponding results are 0.10 × 108 t with the cumulative probability of 50%. The mode value is 0.095 × 108 t, and the average value is 0.10 × 108 t. The recoverable oil resources in the sweet spot area account for 50% of the total shale oil resources, and their distribution prediction results provide a geological basis for exploration well planning and deployment.

9.7 Summary The shale retained oil occurs in the pores of organic matter and inorganic minerals in the source rock in various forms and is controlled by various factors. Although the amount of shale retained oil is huge, only the movable part can constitute potential resources. A large research results show that the large-scale exploitation and utilization of marine shale oil in North America is related to its high ratio of recoverable oil.

324

9 Evaluation of Unconventional Shale Oil and Gas Resource

In contrast, terrestrial shale oil of huge potential in China has not been exploited and utilized on large scale, mainly due to the low percentage of movable oil. It is of great theoretical significance and practical value to understand the main controlling factors of continental shale oil and develop evaluation technology for its movability. In this paper, we take the terrestrial shale oil of Tertiary Sha-3 member in Bohai Bay Basin, China, as the research object. Geochemical analysis, mineralogical analysis, imaging observation, and pore structure analysis determined that the movable oil enrichment is mainly controlled by six factors: lithofacies type, pore space, clay content, original hydrocarbon content, surrounding rock condition, and burial depth of target layer. It is found that the mineral composition, bedding structure, and lithofacies characteristics of terrestrial shale are significantly different from those of marine shale. The variation characteristics of continental shale oil are mainly controlled by four geological factors, including sedimentary facies, pore structure, surrounding rock condition, and burial depth. The results of the Nuclear Magnetic Resonance (NMR) displacement experiment of oil movability from artificial cores show that the ratio of movable oil increases with porosity and permeability increasing, clay mineral content decreasing, oil viscosity decreasing, and kerogen content decreasing. The shale movable oil ratio and recovery factor were obtained according to the actual geological conditions. The distribution of recoverable oil resources in the Gaoliu area of Nanpu Sag was simulated by applying the volume method model and the Monte Carlo technique, providing a scientific basis for further exploration decisions.

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Chapter 10

Evaluation of Reformed and Destroyed Oil and Gas Reservoirs

New Understanding: (1) Oil and gas reservoirs destroyed by tectonic movements are common in petroliferous basins. Oil and gas destruction due to tectonic activities are mainly controlled by four factors, including activity intensity, times, and sequence of tectonic movements and sealing ability of caprocks. High intensity and frequency tectonic movements result in destruction of large oil and gas amount. Strong plasticity and thick cap rock can preserve large volumes of oil and gas. The superposition of multistage tectonic movements influences the formation and distribution of original oil and gas reservoirs. (2) The model for estimating the oil and gas volumes destroyed through multistage tectonic movements has been established based on logical analysis, by calibrating measured geological parameters and determining original accumulated oil and gas amount (Q0 ), oil and gas destruction ratios (Kl ), times (n), sequence (i) and sealing capability in each tectonic event. Thus, the destroyed oil and gas amounts due to tectonic events and the remaining oil and gas resource potentials can be evaluated. Relative volume of oil and gas destroyed can be predicted assuming the original oil and gas accumulation amount to be 1 unit, and the 1 and 0 represent 100% preserved and 100% destroyed, respectively. (3) In the Tazhong area of Tarim basin, the WPS has experienced four stages of oil and gas accumulations and three stages of adjustments and reformations. Around 68%, 59%, 28% and 0% of hydrocarbons have been destroyed in the four stages of tectonic events of the 510 Ma, 298 Ma, 227 Ma and 38 Ma, respectively. Remaining oil and gas resource reserves are about 1.9 billion tons after multistage accumulations, reformations, and destructions. (4) More than 60% of oil and gas reservoirs formed in the earlier stages have been destroyed by tectonic events in the Tarim Basin, about 95% of the large oil and gas reservoirs and 93% of commercial wells with daily production of over 100 tons are distributed in areas with higher remaining resource potential, whereas 70% of the 156 failed wells are distributed outside these areas. Success probability of well drilling increases by more than 19% when considering destroyed oil and gas caused by tectonic events.

© Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_10

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10.1 Introduction and Issue The oil and gas reservoirs are the most important sources of fossil energy and the oil and gas traps formed in specific geological formations are critical for the preservation of petroleum resources (Magoon and Dow 1994; Marini and Frapiccini 2014; Sharma and Shane 2016; Zieba and Grøver 2016). Tectonic movements undermine the integrity of trap conditions, leading to oil and gas damage in various ways, including upward migration or entry into new traps forming new oil and gas reservoirs, surface leakage and destruction due to biodegradability, escape into the atmosphere, or formation of bitumen and heavy oil (Brooks et al. 2006; Connan 1984; Head et al. 2003; Shah et al. 2010). Several large reserves of heavy oil and bitumen have been identified in the West Basin of Alberta in Canada, Venezuela Basin, Morondava Basin of Madagascar, and Junggar Basin in China (James 2000; USGS 2007; Garnet 2010). According to the 7th International Conference report on heavy oil and bitumen, around 1.11 trillion tons of crude oil and tar sand reserves have been discovered so far (He et al. 2010). Superimposed basins are largely correlated to oil and gas reservoirs, and in China, many studies have focused on the formation conditions, evolutionary history, geological characteristics, and complex petroliferous properties of these basins in western China (Jin 2006; Li et al. 2010). Due to multi-stage tectonic movements, the oil and gas reservoirs formed earlier in the superimposed basin experienced a series of adjustments and reformations, resulting in complicated oil and gas reservoirs with distinct features (Jin 2006; Pang et al. 2012b). Classic concepts on petroleum geology and explorations face new challenges in situations where oil and gas reservoirs formed in early stages undergo destruction (Magoon and Dow 1994; Pang 2014a). Due to the paucity of effective methods and techniques for predicting their formation and distribution has resulted in high oil and gas exploration risks and low effectiveness. Quantitative evaluation of oil and gas reservoirs reformed due to tectonic movements has important practical significance in terms of formulating guidelines for oil and gas exploration (Jin 2006, 2007; Pang et al. 2012b; Pang 2014a). Quantitative evaluation not only can predict completely damaged reservoir areas and reduce drilling risks (Pang et al. 2012b), but also can help to identify reservoir distributions that have been preserved, thereby opening up new exploration areas and increasing success rate of exploration wells (Jia 2007). Evaluating the objective potential resources through the oil and gas amount destroyed by tectonic movements can further help in understanding oil and gas reservoirs distribution, and provide guidance and long-term oil and gas exploration strategy (Jin 2006; Pang 2014a). A breakthrough in this problem is essential not only to improve geological models on the formation and distribution of oil and gas reservoirs, but more importantly, to promote oil and gas resources exploration of complicated superimposed basins (Pang et al. 2012b). In this chapter, we take the Tarim Basin in China as an example for a systematic quantitative evaluation of oil and gas reservoirs destruction, the controlling factors, quantitative relationship between tectonic movements and destroyed hydrocarbons

10.2 Geological Setting and Evaluation Method

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volume and the remaining resources. Our study offers integral constraints to provide geological basis for choosing favorable targets and for lowering the risks.

10.2 Geological Setting and Evaluation Method The Tarim Basin, covering an area of 560,000 km2 is the largest complex superimposed basin in northwestern China. The Precambrian basement of the Tarim Basin belongs to the Tarim Craton, which together with the North China Craton and the South China Craton defines the fundamental Precambrian tectonic framework of China basement of China as shown in Fig. 10.1a (Zhao and Guo 2012; Zhai and Santosh 2011; Zhao and Zhai 2013; Yang et al. 2016). The basement rocks are dominantly composed of Neoarchean and Paleoproterozoic units (Lu et al. 2002; Lu and Yuan 2003; Zhang et al. 2013), which are mainly exposed along the margin of the craton, including the Quruq-tagh, Aksu, Tieklik-West Kunlun and the Altyn Tagh-Dunhuang areas as shown in Fig. 10.1b (Lu et al. 2008). These include the Archean–Paleoproterozoic TTG (tonalite–trondhjemite–granodiorite) suite formed at 2.83–2.46 Ga (Long et al. 2010; Xin et al. 2013), Archean supracrustal rocks of 2.60–2.55 Ga (Xin et al. 2013), Paleoproterozoic paragneisses and minor meta– volcanics of ~ 2.2 Ga (Zhang et al. 2012; Ma et al. 2013), and low-grade Mesoproterozoic–early Neoproterozoic volcano–sedimentary sequences with minor carbonates and various intrusive rocks (Zhang et al. 2013). The late Neoproterozoic to Cambrian unmetamorphosed strata which unconformably overlie the basement in both northern and southern parts are considered to have been deposited after ~ 760 Ma (Zhang et al. 2016). These are composed of multiple glacial diamictites from the bottom to top, with intervals of volcanic rocks and layers of mudstones, sandstones, limestones, and cap carbonates with stromatolite, recording multiple glaciations (Xu et al. 2005; Zhang et al. 2013, 2016; He et al. 2014). Voluminous Neoproterozoic intrusive rocks formed at ~ 0.82–0.75 Ga are distributed along the margins of the TB (Ye et al. 2013; Zhang et al. 2012; Long et al. 2011; Zhang et al. 2014a, b; Xu et al. 2013). Basaltic eruption occurred at 0.78 and 0.76 Ga are intercalated with the Neoproterozoic sedimentary rocks (Xu et al. 2013). Mafic dyke swarms and mafic–ultramafic complexes were emplaced during ~ 0.82–0.80 Ga (Deng et al. 2008; Zhang et al. 2011). Several granitoid intrusion with ages in the range of ~ 0.82–0.80 Ga have also been identified (Long et al. 2011; Xu et al. 2013). Another suite of mafic dyke swarms at 0.78–0.76 Ga exposed in Quruqtagh and Aksu area in the northern part of the Tarim Block intrude into the 0.82 Ga granite and older Precambrian basement (Zhan et al. 2007; Zhang et al. 2014a, b) and unconformably overlain by ca. 755 Ma volcaniclastic successions (Xu et al. 2005). The central domain of the Tarim Basin is broadly occupied by > 10 km thick sedimentary units ranging in age from Cambrian to Quaternary (Wang et al. 2014a). Among these, the oil and gas reservoirs are located within Cambrian and Ordovician carbonate, Silurian and Carboniferous marine sandstone, and continental-sourced sandstone of Triassic, Jurassic, Cretaceous and Tertiary age (Zhu et al. 2015a, b).

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Fig. 10.1 Geological setting and data. a General tectonic framework of China illustrating the Precambrian cratons (after Zhao et al. 2004). b Simplified geological map of the Tarim Craton and adjacent terrains, showing the distribution of Precambrian rocks around the Tarim Craton and the central cover in the Tarim Basin (modified after Ge et al., 2012)

Oil and gas resources that have been discovered from these strata are estimated as 12.337 billion tons (Tarim oil company, PetroChina 2002). Tar sands are widely distributed in the Silurian strata, and it was estimated that over 8.6 billion tons of original resource had been destroyed by tectonic events (Zhang et al. 2004; Jiang et al. 2008). Additionally, widely exposed oil–gas seepages are observed on the surface of the Kuqa Depression. By the end of 2010, 296 wells were drilled in the Tarim Basin, the deepest being more than 8000 m with an average depth of 5900 m. A total of 138 wells have been identified for commercial oil and gas flows, whereas the other 156 wells are not commercially yielding (Pang et al. 2012b). Similar to other superimposed basins developed in Western China such as the Junggar and Qaidam Basins (Fig. 10.2), the Tarim Basin has a complicated superimposed history involving several discrete basins developed during different stages but at the same location (Jin and Wang 2004). Studies show that Western China’s superimposed basins were compressed by tectonic forces from the north and south during the recent 50 m. y. leading to rapid uplift of the Tibetan Plateau (Zhou et al. 2006). Widespread distribution of hydrocarbon seeps, bitumen, and heavy oil in the Tarim Basin, Junggar Basin and Qaidam Basin reflect reservoir adjustments, alterations and destruction due to tectonic movements (Fig. 10.3). Figure 10.3a shows surface exposures of seeps in the Kuqa Depression resulting in ongoing local oil and gas seepage. Figure 10.3b shows the locations of a series of destroyed hydrocarbons on the surface like oil sands. The location of heavy oil in Junggar Basin is shown in

10.3 Relationship Between Tectonic Events and Oil/Gas Destruction

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Fig. 10.2 Effects of Tibetan plateau uplift on superimposed basins in Western China. a Tectonic setting of petroliferous basins in China; b relationship between Tibetan Plateau uplift time and uplift rate (after Zhou et al. 2006); c relationship between Tibetan Plateau uplift time and uplift elevation (after Zhou et al. 2006)

Fig. 10.3c, where large amounts of normal oil and gas are also accumulated below the ground, providing evidence of a directly damaged reservoir. Figure 10.3d shows the distribution of Silurian tar sands and dry bitumen as identified through a large number of exploration wells in the Tarim Basin, indicating multiple oil and gas reservoirs adjustments due to tectonic movements. These inferences are consistent with the results from several recent studies (Wu et al. 2002; Zhang et al. 2007, 2011; Lu et al. 2007; Pang et al. 2012b; Wang et al. 2014b; Guo et al. 2016; Huang et al. 2016a; Zhu et al. 2016).

10.3 Relationship Between Tectonic Events and Oil/Gas Destruction 10.3.1 Reformed Oil and Gas Reservoirs Due to Multi-stage Tectonic Events Tectonic movements in superimposed basins result in oil and gas reservoirs formation as well as destruction. Tectonic events have positive effects on the formation and distribution of oil and gas reservoirs in the subsidence stage with deposition of sedimentary strata and increasing burial depth, which leads to increased amounts of oil and gas being generated and expelled from source rocks. This would act

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Fig. 10.3 Characteristics of oil and gas reservoirs transformed by tectonic movements in Western China’s superimposed basin. a Distribution of oil and gas seepage on surface in the Kuqa Depression; b distribution of oil and gas seepage on surface in the Qaidam Basin; c distribution of tar sand on the surface in Junggar Basin; d distribution of tar sand of Silurian in the Tarim Basin

as a favorable scenario for oil and gas accumulation. Thus, the early oil and gas accumulation can be well protected due to thickening of overlying strata. On the other hand, the overlying strata undergo denudation in the tectonic uplift stage, under conditions of faulting and folding, and early formed oil and gas reservoirs may undergo adjustment, reconstruction and even destruction (Mark et al. 1993; Awang et al. 1999; Prost 2004; Yang et al. 2005; Li et al. 2010). The current distribution of oil and gas reservoirs in the Tarim Basin is resulted from multiple oil and gas accumulation, reformation and destruction due to multiple tectonic movements. From the northeast profile of the Tarim Basin (Fig. 10.4), it can be seen that early-formed oil and gas reservoirs in the Ordovician experienced at least three major tectonic events. The first phase was at the end of the Silurian, when thick strata of over 2500 m was distributed in the Tazhong and northern Tarim Uplifts. In the second stage, at the end of Permian, over 2000 m thick strata was distributed in the northern basin. In the third phase at end of the Cretaceous, over 1000 m thick strata was distributed in the south. Tectonic events adjust and destroy oil and gas reservoirs in various ways (Fig. 10.5) as follows. (i) Location migration of reservoir layers due to tectonic events and trap position changes that cause earlier gathered oil and gas to migrate and accumulate into a new trap. Figure 10.5a shows a Hudson reservoir in the Tarim Basin migrating again from northwest to southeast, with huge amounts of oil and gas on the move, that

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Fig. 10.4 A section (A–B) showing the distribution characteristics of oil and gas reservoirs in the Tarim Basin after multi-stage accumulations and adjustments

have not yet fully accumulated in the new trap (Xu et al. 2008; Luo et al. 2015). (ii) Reservoir scale reformation due to strong tectonic events, where part of the reservoir’s trap conditions were damaged causing partial oil and gas loss. Figure 10.5b shows the Tazhong 4 reservoirs have been changed from large reservoirs of 350 million tons to 120 million tons after multiphase tectonic events (Han and Li 2000; Zhao 2001; Liu 2003). (iii) Oil and gas reservoir damage where earlier formed reservoirs completely transformed to tar sands or solid bitumen due to effusion caused by tectonic events or component damage. Figure 10.5c shows distribution features of the Silurian dry asphalt in the Tazhong area of the Tarim Basin (Zhang et al. 2004; Xiang et al. 2010; Pang 2014a). (iv) Mixture of oil and gas from multiple sources and multistage oil and gas accumulations where oil and gas from different source rocks gathered in one trap due to tectonic events after expulsion. Studies indicate that the mixtures of oil and gas from multi-source and multistage oil and gas accumulations are basic characteristics of oil and gas accumulation in the Tarim Basin. Figure 10.5d shows the basic characteristics of mixture oil and gas between Cambrian crude oil with heavier carbon isotope and Ordovician crude oil with lighter carbon isotope. Studies show that mixed ratio of the two types of crude oil lies between 0 and 100%. Contribution of Cambrian crude oil increases with decreasing distance from the fault, and also with an increase in burial depth (Pang et al. 2016). The other factors are (v) microbial degradation; and (vi) high temperature cracking of crude oil due to reservoir burial depth becoming shallower and deeper controlled by tectonic events. Shallower burial depth helps microbes to transform oil and gas reservoirs leading to crude oil density polarization. One results in the formation of very large proportion of asphalt, whereas the other forms a very light proportion of methane gas. Figure 10.5e shows oil and gas reservoirs in Tazhong transformed under microbial action (Li et al. 2008, 2009, 2015). When burial depth increases, larger proportion of crude oil cracks into lighter gas-condensate reservoirs, or even into dry gas reservoirs with primarily containing methane, due to the high temperature (Han et al. 2009; Zhu et al. 2013).

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Fig. 10.5 Various mechanisms through which multiple tectonic events alter and destroy oil and gas reservoirs in the Tarim Basin. a Location migration; b scale reformation; c hydrocarbon reservoirs destruction; d multiple oil and gas sources mixture; e biodegradation of oil and gas

10.3 Relationship Between Tectonic Events and Oil/Gas Destruction

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10.3.2 Key Geological Factors Controlling Oil and Gas Destruction The volume of oil and gas destroyed is controlled by various geological factors, the most important being the intensity of the tectonic movements, stages, order, and plasticity and sealing ability of the cap rock. Destroyed oil and gas amount is directly proportional to tectonic event intensity. The most common forms of tectonic events include folding, faulting, fracturing and denudation (Fig. 10.6a) (Pang et al. 2002). Large-scale tectonic events produce strong folding, faulting and denudation of the strata, which cause more damage to the oil and gas reservoir. Smaller scale tectonic events cause the strata to produce folding with smaller amplitude, smaller slip fault and smaller thickness of denuded layer, which result in smaller reservoir damage. Recent studies have established a relationship between the forms of tectonic events in the Tarim Basin: faulting is stronger in areas of large denudation, and fault displacement increases as denudation thickness of overlying strata increases (Fig. 10.6b). Folding is stronger in larger denuded areas, and fault dip angle increases as denudation thickness of overlying strata increases (Fig. 10.6c). These features show that statistical analysis of the three parameters above can be used to express strength of tectonic events in the Tarim Basin. Figure 10.6d shows relationship among exploratory well production and denudation thickness of overlying strata belonging to Cambrian, Ordovician, Silurian, and Carboniferous, and reveals that in areas with large denudation thickness (> 250 m) and small denudation thickness (< 50 m), the production of target layer is low. Areas with smaller denudation thickness have weaker tectonic events, where the formations are in a deep and stable state, which is not conducive to oil and gas accumulation. Areas with larger denudation thickness have stronger tectonic events, and the formation are in an uplifted and denuded state, which is not conducive to oil and gas preservation after accumulation. A greater number of tectonic events results in larger oil and gas reservoir damage. The Tarim Basin witnessed multiple tectonic events during its evolution process, causing damage to oil and gas reservoirs formed in the early stages. Strong tectonic events, as well as many small movements can collectively lead to complete destruction of oil and gas reservoirs. Figure 10.7 shows the Tazhong 4 reservoirs, which suffered multistage tectonic events, with data from the reservoirs’ paleo oil–water boundary and their changing characteristics (Liu 2003), illustrating the control of multistage tectonic events on the degree of oil and gas reservoirs damage. Figure 10.7a shows the geological characteristics of oil and gas reservoirs formed during Late Permian, with reserves of 350 million tons. Figure 10.7b shows geological characteristics of oil and gas reservoirs after the first damage during Late Triassic, with reserves of about 250 million tons. Figure 10.7c shows geological characteristics of oil and gas reservoirs after second damage during Cretaceous, with reserves of 180 million tons. Figure 10.7d shows the current geological characteristics of the oil and gas reservoirs after nth damages, with reserves of about 120 million tons. Large oil–gas reservoirs are changed into small and medium oil–gas reservoirs after multistage tectonic movements, with the destroyed oil and gas amount estimated to

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Fig. 10.6 Forms and intensity of tectonic events and oil and gas reservoirs damage in the Tarim Basin (modified after Pang et al. 2012b). a Relationship between tectonic events and hydrocarbon accumulation; b relationship between fault throw and denuded zone thickness; c relationship between fold intensity and denuded zone thickness; d relationship between hydrocarbon productivity and denuded zone thickness

be more than 65% of their original amount in the Tazhong 4 reservoirs (Han and Li 2000; Liu 2003; Pang et al. 2012a). Stronger tectonic events would lead to larger damage to oil and gas reservoirs. When tectonic events with same intensity occur in different periods, they caused oil and gas reservoirs damage in different degrees. Early tectonic movements caused damage only to earlier formed oil and gas reservoirs, whereas the late movements will adjusted, reformed and damaged all of the oil and gas reservoirs formed in different stages (Mark et al. 1993; Prost 2004; Pang et al. 2012b; Pang 2014a). Figure 10.8 shows how multistage tectonic events affect the volume of oil and gas destroyed. Most of oil and gas reservoirs that accumulated early were destroyed by multiple tectonic events happened later, with only a few being preserved. None or very few oil and gas reservoirs that accumulated late are suffered from any damages caused by earlier tectonic events, and majority of the oil and gas reserve has been preserved. This indicates that late tectonic events adjust and damage all oil and gas that accumulated before the movements, and that the destroyed hydrocarbon amount could be far greater than that during the earliest period. Indeed, the extent of oil and gas destruction is affected by many factors under actual geological conditions, furthermore, the rate and intensity of destruction is also a function of the tectonic events, and the original scale of the oil and gas reserves (Q0 ), which are accumulated prior to the tectonic events (Pang et al. 2012b; Pang 2014a). The stronger the plasticity and sealing ability of overlying caprock during the process of tectonic events, the lesser the oil and gas reserves would be damaged. Damages caused by tectonic events are controlled by caprock sealing ability, which is

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Fig. 10.7 Paleo oil and gas boundary changing characteristics of Tazhong 4 reservoirs in the Tarim Basin during the process of reservoir reformation and damage in 4 different period (after Pang et al. 2012b). a Late Permian; b Late Triassic; c end of Cretaceous; d present day

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Fig. 10.8 Conceptual relationship model between sequence of tectonic events and destroyed oil and gas amount in the Tarim Basin

related to plasticity. If the plastic caprock deforms easily, covering cracks in reservoirs becomes easier and improves caprock sealing ability for oil and gas (Zhao et al. 2004; Pang et al. 2012b), some examples include the Cenozoic foreland basin in the Kuqa Depression of the Tarim Basin, due to the uplift of the Qinghai-Tibetan plateau and compression in the N–S direction of the Tianshan mountain, when Cretaceous sandstones witnessed intense folding and formation dip angle over 90° (Qi et al. 2013). Thrust fault developed in the study area, and fault anticline and semi-anticline also accumulated a large amount of natural gas. Studies show that the target salt layer over Cretaceous played a vital role in natural gas sealing and preservation; plastic deformation of salt layer during the tectonic events filled the gap between fracture spaces to ensure trap integrity and closure (Fu et al. 2015). Figure 10.9 shows an example from China’s largest source of West–East Gas Transmission, the Kela2 gas field located in the Kela2 anticline, which was blocked after plastic deformation of salt layer. In the past 5 years, a series of gas fields similar to Kela2 have been discovered, such as the Dabei and Keshen gas field, with cumulative reserves of more than 1000 billion cubic meters (Wang 2004), reflecting protection of oil and gas reservoirs through caprock sealing ability during tectonic events.

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Fig. 10.9 A section (C–D) showing the relationship between destroyed oil and gas amount due to tectonic events and sealing capacity of cap rock in the Kuqua depression of Tarim Basin

10.3.3 Superposition of Multistage Tectonic Events The Tarim Basin underwent multistage superimposed tectonic events. Based on analysis of seismic section in the Tarim Basin, at least 10 unconformities have been identified (Fig. 10.10a), including 6 large ones in the end of Ordovician, Middle Devonian, and at the end of Permian, Triassic, Jurassic, and Cretaceous (Lin 2006). Figure 10.10b shows erosion thickness caused by 6 major tectonic events, reflecting differences of tectonic intensity in different areas at different periods (Wang et al. 2004). In summary, Fig. 10.10 shows the following three points: (i) Each tectonic event involves integrated basin, indicating overall uplift of basin; (ii) Each tectonic event shows significant difference in tectonic strength in different areas, and denudation thickness is between 0 and 2500 m; and (iii) Different periods of tectonic events have different geological characteristics, the early stages during end of Ordovician and Middle Devonian mainly show the uplifts and denudation on southeast of the basin, indicating largest denudation thickness being more than 2500 m; the middle stage, at the end of the Permian and Triassic, shows overall uplift and denudation to the northeast of the basin, indicating largest denudation thickness being more than 2000 m; and the late stage at the end of Jurassic and Cretaceous show overall uplift and denudation in the southwest, indicating largest denudation being more than 1000 m (Wang et al. 2004). Preservation of oil and gas reservoirs in the Tarim Basin that developed in the early stage depends upon the superimposition of above process of multistage tectonic events. Studies show that repeatedly strong superimposition of tectonic movements cause damage to oil and gas reservoirs, whereas the superimposition of weak-weak tectonic movements is beneficial to the formation and preservation to tectonic movements

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Fig. 10.10 a Strata formation and their denudation periods distribution in the Tarim Basin in relation to multiple tectonic events (after Lin 2006); b denudation thickness distribution during tectonic events in the Tarim Basin

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347

reservoirs (Pang et al. 2012b). Three large tectonic cycles have been identified in the Tarim Basin (Tang et al. 2004), each associated with the formation and destruction of oil and gas reservoirs. In the early stages of the tectonic cycle, the basin tends to show integral subsidence and sedimentary of stratum, and this period was favorable for oil and gas generation, expulsion, migration, and accumulation. In the late tectonic cycle, the basin was often characterized by integral lifting, strata denudation, and this period was characterized by adjustments, alterations and destruction of oil and gas reservoirs. In order to objectively evaluate the influence of each tectonic event on the early oil and gas, we use the overburden strata denudation rate (Ks) to characterize tectonic event intensity (Eq. 10.1): Ks =

He H

(10.1)

Here, Ks—Tectonic event intensity; He—Eroded thickness of strata in tectonic cycle; H—Total thickness of strata in tectonic cycle. Figure 10.11a–c shows three tectonic event intensities in the early stages (2500– 495 Ma), middle stages (495–295 Ma), and late stages (295–24 Ma) of the three tectonic cycles, respectively, in the Tarim Basin. Figure 10.11d shows the tectonic intensity distribution characteristics after superimposition of the three tectonic cycles. The overall weak, relatively weak, strong and the strongest areas of tectonic intensity are also identified. From the diagram as shown in Fig. 10.11, it can be seen that the oil and gas reservoirs that have already been discovered in the Tarim Basin are distributed in areas where tectonic events are weak and relatively weak, whereas no oil and gas reservoirs have been discovered in the areas affected by the strong and strongest tectonic intensity. This indicates that areas with superimposition of strong-strong tectonic events damage oil and gas reservoirs, whereas areas with superimposition of weak-weak tectonic events preserve oil and gas reservoirs. Based on this classification, and the information from different regional tectonic superimposition in the petroliferous basin, the damage degree of tectonic events on oil and gas reservoirs and exploration risks for oil and gas resources can be predicted.

10.4 Evaluation of Destroyed and Remained Oil and Gas Resources 10.4.1 Conceptual Geological Evaluation Model The preservation of oil and gas reservoirs in complex superimposed basins is determined by the process of multistage tectonic movements superimposition. The key factors including intensities of movements, their sequence, period times of events, capabilities of caprock sealing in each tectonic event, controlling extents of oil and gas reservoir destructions. We show in Fig. 10.12 a conceptual geological model to

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Fig. 10.11 Superimposition of multiple tectonic movements and distribution characteristics of potential oil and gas reservoirs in Tarim Basin. a Tectonic movement intensities after the first cycle; b tectonic movement intensities after the second cycle; c tectonic movement intensities after the third cycle; d comprehensive tectonic movement intensities

illustrate relationship of these factors. Figure 10.12a shows three large tectonic events after the oil and gas accumulations in the early stage, timing of the events is indicated by the number of layers of unconformity. The eroded thickness in the corresponding unconformity records the intensity of each tectonic event (Fig. 10.12b). Figure 10.12c shows superimposition of multi-tectonic events and corresponding extent of oil and gas reservoirs destruction. The absolute oil and gas volume affected by each tectonic event can be calculated by determining the corresponding paleo oil–water contact of the oil and gas reservoirs. Intensity of each tectonic event is determined by calculating the eroded thickness in unconformities. The quantitative model for relationship between destruction rate of oil and gas caused by tectonic event and its intensity can be established by statistical analysis, which in turn provides calculation parameters for calculation of destroyed oil and gas amounts. Extent of oil and gas reservoir destruction in every well can be identified quantitatively by analyzing the superimposition of tectonic events. In the Tazhong area shown as example in Fig. 10.12b, the final oil/ gas-bearing properties depend on superimposition of three tectonic events. When all three events were strong, the superimposition of strong-strong results in oil and gas

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Fig. 10.12 Geological conceptual model of multi-stage tectonic events superimposition and evaluation of destroyed oil and gas reservoirs. A, B, C, D, E, F—different formation in research area; U1 —unconformity surface caused by first tectonic event; U2 —unconformity surface due to second tectonic event; U3 —unconformity surface by third tectonic event; K1 —destroyed oil and gas ratio compared with the total oil and gas accumulated before by the first tectonic event; K2 —destroyed oil and gas ratio due to second tectonic event; K3 —destroyed oil and gas ratio by third tectonic event; Qi0 —accumulated oil and gas amount before tectonic events; Qi1 —remained oil and gas amount after first tectonic event; Qi2 —remained oil and gas amount after second tectonic event; Qi3 —remained oil and gas amount after third tectonic event. a Geological section for distribution of oil and gas reservoirs; b intensity of tectonic event after oil and gas reservoir formed; c relationship between the destruction degree of oil and gas reservoirs and tectonic events superimposition in the basin (modified after Pang et al. 2012b)

reservoirs destruction, in which the oil/gas-bearing properties were worst. In contrast, when the three tectonic events were weak, the superposition of weak-weak results in the protection of oil and gas reservoirs, which had the best oil/gas-bearing properties. When tectonic events were alternatively strong and weak, the superimposition of strong–weak results in the transformation of oil and gas reservoirs to medium oil/ gas-bearing properties (Fig. 10.12c). If essential parameters such as the destruction rate of oil and gas amount caused by the tectonic events and the original oil and gas accumulation amount before each event are obtained, it is relatively easy to evaluate the volume or amount of destroyed oil and gas in each tectonic event, the total volume or amount of oil and gas destroyed by superimposition of several tectonic events, as well as the remained oil and gas volume or amount in these tectonic events.

10.4.2 Mathematical Model for Quantitative Evaluation The geological conceptual model for quantitative evaluation of oil and gas reservoirs destroyed by superposition of multistage tectonic events can be expressed by the mathematical formulae based on logical reasoning. The oil and gas resource reserve in the oil and gas reservoirs before the tectonic event can be designated as Q0 ; Kd1 , Kd2 , …Kdi …Kdn , respectively, refer to the intensities of the 1st, 2nd, …the ith, the

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nth…tectonic event. Their corresponding rates of destroying oil and gas are expressed by K1 , K2 , …Ki …, Kn . The sealing capability of caprock during each tectonic event is set as fc, expressed using fc1 , fc2 , …fci …, fcn . The Qli and Qi denote destroyed oil and gas amounts and remained oil and gas amount, respectively. The deduced model is as follows: Hydrocarbon destruction amount in the 1st tectonic event: Q l1 = Q 0 · (1 − K 1 )

(10.2)

Remaining hydrocarbon amount after 1st tectonic event: Q1 = Q0 − Qn

(10.3)

Hydrocarbon destruction amount in the 2nd tectonic event: Q l2 = Q 1 · (1 − K 2 )

(10.4)

Remaining hydrocarbon amount after 2nd tectonic event: Q 2 = Q 1 − Q l2

(10.5)

Hydrocarbon destruction amount in the ith tectonic event: Q h = Q i−1 · (1 − K i )

(10.6)

Remaining hydrocarbon amount after ith tectonic event: Q i = Q i−1 − Q li

(10.7)

Hydrocarbon destruction amount in the nth tectonic event: Q ln = Q n−1 · (1 − K n )

(10.8)

Remaining hydrocarbon amount after nth tectonic event: Q n = Q n−1 − Q ln

(10.9)

The remained hydrocarbons amount after each tectonic event, by assigning geological parameters, can be figured out by Eqs. 10.10–10.12, which are combination of above formulae. Remaining hydrocarbon amount after 1st tectonic event: Q 1 = Q 0 · (1 − K 1 ) · f c1 Remaining hydrocarbon amount after 2nd tectonic event:

(10.10)

10.4 Evaluation of Destroyed and Remained Oil and Gas Resources

Q 2 = Q 0 · (1 − K 1 ) · (1 − K 2 ) · f c2

351

(10.11)

Remaining hydrocarbon amount after nth tectonic event: Q n = Q 0 · (1 − K 1 ) · (1 − K 2 ) · · · · · (1 − K i ) · · · · · (1 − K n ) · f cn

(10.12)

10.4.3 Acquisition of Geological Parameters Acquisition of three types of geological parameters related to oil and gas accumulations and tectonic events is critical to the application of the quantitative model for evaluating oil and gas amount destroyed through tectonic events, including the original volume of oil and gas accumulation (Q0 ), tectonic destruction rate in each event (Ki ), and capability index of caprock sealing oil and gas reservoirs in each tectonic event (fci ), among which the third one is easy to acquire and is determined by both lithology and thickness in the evolution stage of caprock. The lithology of identified caprocks are mainly salt, mudstone, limestone, volcanic ash, etc. Sealing capability of them can be quantitatively described by multiplying their thickness and plasticity index. However, it is difficult to depict the original accumulated oil and gas amount (Q0 ) and the tectonic destruction rate for accumulated oil and gas (Ki ). Original accumulated hydrocarbons amount (Q0 ). Multistage oil and gas accumulations occurred in superimposed basins (Pang et al. 2015). Hydrocarbons provided by source rocks were not the same in each period of time. Based on variation of hydrocarbon generation potential with increasing burial depth, the hydrocarbon generation and expulsion rate from organic matter per unit weight in source rocks during their evolution were investigated (Fig. 10.13). Following this, combined with distribution area and thickness of source rocks, the total organic carbon content (TOC), kerogen type index (KTI) and degree of thermal evolution (Ro), and the hydrocarbon amount (Qe) expelled from source rocks in the whole petroleum system can be calculated by Eq. 10.13 (Pang et al. 2005). Qe =



qe (z) · h · A · ρ(z) · T OC

(10.13)

Here, Qe —Hydrocarbon expulsion amount from source rocks, t; qe (z)—Hydrocarbon expulsion intensity, t/km2 ; h—Thickness of source rock strata, m; A—Area of source rock, m2 ; ρ(z)—Density of source rock, g/cm3 ; TOC—Total organic carbon content, weight of source rock, %. Figure 10.13 shows that hydrocarbon generation potential of major Cambrian and Ordovician source rocks in the Tarim Basin varies within 88–380 mg, growing with increasing depth until it reaches 4600 m, and then decreases dramatically. According to the critical condition determined by hydrocarbon generation potential, the potential per unit weight of organic matter ((S1 + S2 )/TOC) decreases dramatically to a

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point in the sedimentary section; source rock expelled hydrocarbon abundantly at 1800 Ma. Additionally, decreasing rate of hydrocarbon generation potential reveals that hydrocarbon expulsion ratio varies between 0 and 500 mg/g, and increases with increasing depth. Also, characteristics of expulsion rate indicate that hydrogen expulsion peaked at 1000 Ma. Expulsion efficiency, e.g. the ratio of expelled hydrocarbon amount to total generation potential, is between 0 and 60%, which increases with depth. These parameters form the basis for calculating efficient hydrocarbons that source rocks provide for oil and gas accumulations in reservoir layers. Significant hydrocarbons amount (Qe ) expelled from source rock was lost through diffusion and dissolution in water and washed away (Pang et al. 1993). Some of these oil and gas was retained in the surrounding rocks due to absorption and capillary sealing effect during migration (Dickey 1975; Barker 1980; Durand 1988; Chen and Tian 1989; Pang et al. 1993, 2004; Pang 1995). In this paper, effective hydrocarbons for accumulation (Qep ) is defined as the remained hydrocarbons amount, which equal to that the expelled oil and gas amount (Qe ) minus the dissolved oil and gas amount in water (Qew ), diffused oil and gas amount (Qed ) and retained oil and gas amount (Qls ). It is calculated as follows: Q ep = Q 0 = Q e − Q ew − Q ed − Q ls

(10.14)

Fig. 10.13 Variation of hydrocarbon generation potential with increasing burial depth of Cambrian and Ordovician source rocks and plane distribution of hydrocarbons generation and expulsion intensities of these source rocks in the Tarim Basin of China. Variation of hydrocarbon generation potential and expulsion feature (a) and hydrocarbon expulsion intensity during Ordovician and Silurian period (b), Cretaceous and Quaternary period (c) and Carboniferous to Permian period (d), respectively

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Fig. 10.14 Calculation of effective oil and gas amount available for reservoirs formation from source rocks in the WPS of a superimposed basin. a Simulation of effective oil and gas amount expelled from source rocks; b physical simulation of oil and gas amount lost during their migration (after Yan et al. 2012); c mathematical simulation of oil and gas amount lost during migration (after Yan et al. 2012)

The hydrocarbon amount expelled from source rocks is identified to be related to the total generated amount and the residual amount of source rocks (Fig. 10.14a). Dissolved oil and gas amount is controlled by salinity of water in source rock, temperature, pressure, solubility of hydrocarbons in water and cumulative water discharged (Pang et al. 1993; Pang 1995). Diffusion oil and gas amount is affected by their concentration difference inside and outside the source rock (Pang et al. 1993; Pang 1995). Remained oil and gas amount is controlled by various geological factors as shown in Fig. 10.14b. The lost oil and gas amount increases as the migration distance increases; the residual oil and gas amount is less in reservoirs and passages with high porosity and permeability, whereas it is larger in tight reservoirs and passages; the migration path and other ways through which hydrocarbon loss occurs. A study by Yan et al. (2012) shows that calculation of lost oil and gas amount differs under various migration conditions, including directly migrating upward after expulsion, below the sealing rock in the source rock area and in the pathway system outside the source rock as shown in Fig. 10.14c. Oil and gas amount lost on their migration way can be modeled by simulation experiments, combined with actual geological conditions. In this paper, relevant results were applied (Pang 2014b). Hydrocarbon destruction rate caused by tectonic events (Ki ). Hydrocarbon destruction rate caused by tectonic events denotes the proportion of hydrocarbon amount destroyed by each tectonic event to total original accumulated hydrocarbon amount. This parameter can be obtained by following two methods. The first is inversion method, which refers to obtaining hydrocarbon destruction rate through

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geological analysis of oil and gas reservoirs that have been discovered. Figure 10.15 shows the result of hydrocarbon destruction rate with variance in tectonic event intensity based on an analysis of the oil and gas reservoirs in the Tazhong area in the Tarim Basin (Pang et al. 2012b). The conceptual model and calculation method of hydrocarbon destruction rate due to tectonic events is shown in Fig. 10.15a, where the oil–water contact surface in Carboniferous reservoir layer is easy to identify as shown in Fig. 10.15b, and Fig. 10.15c illustrates the relationship between the hydrocarbon destruction rate and tectonic event intensity. It is essential to work out the intensity of tectonic event and the extent of destroyed hydrocarbon amount during each event. Pang et al. (2012b) computed the destroyed hydrocarbon amount (Qd ), original accumulated hydrocarbon amount (Q0 ), and corresponding hydrocarbon destruction rate due to tectonic events (Ks = Qd /Q0 ) based on the variations in 15 paleo oil/ gas–water contact surface of oil and gas reservoirs in the Tazhong area. Tectonic intensity (Kd = He /Hc ) was determined by thickness of each overlying caprock (Hc ) and current eroded strata (He ) due to tectonic events. Following this, based on statistical analysis, the quantitative model for hydrocarbon destruction rate and intensity of tectonic activity was established as shown in Eq. 10.15, and is used to calculate different hydrocarbon destruction rates in the research area. Ks = f



He Hc

 (10.15)

Here, K s —Hydrocarbon destruction rate due to tectonic events, %; H e —Total thickness of overlying caprock strata reconstructed by tectonic events, m; H c —Eroded thickness of overlying strata, m. The above equation is applicable for calculating all hydrocarbon destruction rates due to tectonic events in our study area. The eroded thickness of overlying strata caused by common tectonic events varies in different wells, therefore, in order to display hydrocarbon destruction rate in a scientific way, its weighted average value from different wells was obtained based on grid normalization. The second is a forward modeling method to obtain hydrocarbon destruction rate, which is calculated by analyzing preservation conditions of oil and gas reservoirs. Figure 10.16 shows three common ways to characterize the preservation conditions in oil and gas reservoirs. The first was folding, which changed the caprock sealing capability and destroyed oil and gas reservoirs due to abundant fractures in caprock (Fig. 10.16a). The following three cases are identified: (i) Due to weak tectonic movements, there were no obvious folds in the formation and no obvious fractures in the caprock, oil and gas reservoirs were well preserved in traps, so the oil and gas destruction rate was 0%. (ii) Strong deformation occurred in the formations due to severe tectonic movements, the formation was tilted over by 90° and with obvious fractures, and the hydrocarbon destruction rate was 100%. (iii) Hydrocarbon destruction rate was between 0 and 100% for situation of tectonic movements is between (i) and (iii). The second was faulting, which destroyed integrity of overlying caprock, dislocated the caprock and caused fractures, all these factors destroyed the oil and gas reservoirs (Fig. 10.16b). There are three cases for faulting in oil and gas reservoirs.

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Fig. 10.15 Quantitative relationship between the hydrocarbon destruction ratio due to tectonic events and tectonic intensity in the Tazhong area. a Conceptual model and calculation method of hydrocarbon destruction ratio; b distribution of oil/gas–water contact surface of oil and gas reservoirs in Carboniferous; c relationship between hydrocarbon destruction rate and tectonic intensity (after Pang et al. 2012a)

Fig. 10.16 Quantitative conceptual model between hydrocarbon destruction rates and tectonic intensity. a The hydrocarbon destruction rate and folding intensity of strata; b the hydrocarbon destruction rate and fault displacement; c the hydrocarbon destruction rate and eroded thickness of overlying strata

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In the first case, oil and gas reservoirs have been well preserved because tectonic movement was so weak that it was unable to dislocate the caprock, therefore, the hydrocarbon destruction rate was 0%. In the second case, tectonic movement was strong to so strong extent that caprock has been dislocated completely, with thickness of caprock being thinner than the fault displacement, the hydrocarbon destruction rate in this case was 100%. In the last case, tectonic movement was medium, the caprock was dislocated by the fault, but the displacement distance of fault was not larger than the thickness of caprock, therefore, the hydrocarbon destruction rate was between 0 and 100%. The third way of destroying hydrocarbon reservoirs was erosion, where the formation overlying oil and gas reservoirs was partly eroded, weakening the sealing capability of cap rock (Fig. 10.16c). The extent of hydrocarbon destruction caused by erosion can also be divided into three situations based on intensity of tectonic movement. When tectonic movement was weak, the thickness of eroded formation was small, the overlying cap rock was complete, thereby preserving the oil and gas reservoirs, and thus hydrocarbon destruction rate was 0%; whereas, hydrocarbon destruction rate was 100% under the circumstance that the overlying formation (including caprock) was completely eroded and resulting in complete loss of Caprock’s capability. When the tectonic movement was of medium degree, the overlying strata would be partly eroded and the destruction rate was between 0 and 100%. Results obtained through forward modeling method are idealized, thus, it is necessary to calibrate the results based on practical data, or test them in practical applications when using this method for analysis.

10.5 Discussion and Conclusion 10.5.1 Evaluation of Absolutely Destroyed Hydrocarbons Amount The absolutely destroyed hydrocarbons amount is defined as the real oil and gas amount destroyed in tectonic events, this study is applied in the Tazhong Uplift of Tarim basin. The Tazhong Uplift is one of the second-order tectonic units in the Tarim Basin, covering an area of about 22,000 km2 with reserves of 1.041 billion tons, and most of the oil and gas have accumulated in the Paleozoic strata, including Cambrian and Ordovician carbonate rocks, Silurian and Carboniferous sandstones (Pang et al. 2012a). Figure 10.17a illustrates the distribution characteristics of oil and gas reservoirs discovered in the Tazhong Uplift, Figure 10.17b and c shows the accumulated oil and gas amounts during four periods of oil and gas accumulation processes and simulation calculation results of three hydrocarbon destruction events. Three conclusions arise from this analysis. First, the Tazhong Uplift is a tectonic uplift rich in oil and gas reservoirs with multiple target layers and oil and gas reservoir types. Oil and

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357

gas can accumulate in different positions, such as high structural positions, slopes and fault zones. There are 4 reservoir layers of Cambrian, Ordovician, Silurian and Carboniferous. Oil and gas reservoirs were discovered in different types, such as the mainly reef-bank body with high porosity, caves below unconformity surface and fracture reservoirs around fault. Oil and gas in them mainly came from the mixture of two sets of oil and gas source rocks, Cambrian-Lower Ordovician and Middle-Upper Ordovician in different phases and periods (Huang et al. 2016b). Secondly, four oil and gas accumulations occur in Tazhong area, and most of oil and gas were accumulated in the first and third stages with equivalent amount of oil and gas as 1.096 and 1.005 billion tons, respectively, and less in the second and the fourth stages with the oil and gas equivalent of 0.411 and 0.672 billion tons, respectively (Zhou et al. 2003). Third, based on four stages of oil and gas accumulations, three tectonic movements and reservoirs adjustments occurring after the first, second and third accumulation stages, we computed the absolute destroyed oil and gas amounts based on taking into consideration the parameters of original accumulated hydrocarbon amount for each oil and gas accumulation stage (Zhou et al. 2003) and hydrocarbon destruction rate for each tectonic event (Pang et al. 2012a). The final results show that roughly 68% of oil and gas amount in the first accumulation stage was damaged, 59% damaged in the second stage, and 28% in the third stage. Fortunately, almost all the oil and gas accumulated in the fourth stage were preserved. Comprehensive research shows that the oil and gas amount damaged in three tectonic events in the Tahzong area account for about 40%, and 60% of which was preserved. The model for oil and gas accumulation and destruction is illustrated in Fig. 10.18, where the evolution of oil and gas generation, expulsion, migration and accumulation conditions, and detailed analysis of geological and geochemical characteristics of oil and gas reservoirs have been reconstructed and integrated.

10.5.2 Evaluation of Relatively Destroyed Hydrocarbons Amount The relatively destroyed hydrocarbons amount is defined as the ratio of destroyed oil and gas amount in tectonic events to total accumulated oil and gas amount before tectonic events, this study is applied in the platform of the Tarim basin. Two reasons were considered to choose this method when evaluating relatively destroyed hydrocarbon amount and remained hydrocarbon amount in the platform of the Tarim Basin. One is that the typical hydrocarbon destruction rates for the whole basin are hard to obtain, because the proved oil and gas reservoirs are mainly distributed in several uplift regions, such as the Tabei Uplift and Tazhong Uplift (Zhang et al. 2014a, b; Pang et al. 2016), the manpower and financial resources to get detailed analysis of geological and geochemical characteristics, when oil and gas reservoirs were proved in different regions and layers, is unaffordable in the current circumstances (Pang et al. 2012c). On the other hand, original accumulated hydrocarbon amount is very

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Fig. 10.17 Evaluation of destroyed oil and gas amount after multistage tectonic movements in the Tazhong area of the Tarim Basin. a Distribution of oil and gas reservoirs proved in different layers in Tazhong Uplift; b accumulated and destroyed oil and gas amounts in different stages; c cumulative oil and gas amounts by accumulation and destruction

difficult to get in different regions and layers, especially in the basin’s deep depression areas, where geological and geochemical data are limited, and oil and gas accumulation dynamics in deep depression area are different from those of uplift area. Additionally, it is not necessary to conduct studies on absolute hydrocarbon destruction amount due to tectonic events in the whole basin, because when the original accumulated hydrocarbon amount is not clear, evaluation result of absolutely destroyed hydrocarbon amount cannot confirm the remained oil and gas resource and actual exploration risk. For example, if the absolutely destroyed hydrocarbon amount in

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359

Fig. 10.18 The unified model for oil and gas accumulation and destruction in the Tazhong Uplift of Tarim Basin. C—Carboniferous; S—Silurian; O3s —Sangtamu Formation of Ordovician; O3l — Lianglitage Formation of Ordovician; O1y —Yingshan Formation of Ordovician; O1p —Penglaiba Formation of Ordovician

a study area is large, the exploration risk is still unknown as the original accumulated hydrocarbon amount cannot be calculated. The basic principle for studying relatively destroyed hydrocarbon amount and remained hydrocarbon amount is as follows. First, on the basis of oil and gas accumulation conditions combined with time and space, relative original hydrocarbon amount or hydrocarbon accumulation probability of target layers is predicted (Qr ) as shown in Fig. 10.19a. This is then

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multiplied by hydrocarbon destruction rates due to tectonic events (Kr ), the product of the two is the relative destroyed hydrocarbon amount (Qrd ). Relatively remained hydrocarbon amount (Qrk ) can be calculated by relative original hydrocarbon amount (accumulation probability) minus relative destroyed hydrocarbon amount (Qrd ). The calculation formula can be expressed as follows: Qr k = Qr − Qr d

(10.16)

Q r k = Q r · (1 − K r )

(10.17)

Here, Qrk —Relative remained oil and gas resource potential of one target layer after tectonic movements, %; Qr —Relative original hydrocarbon amount, expressed in accumulation probability of oil and gas in one target layer during a certain accumulation stage, %; K r —Hydrocarbon destruction ratio due to tectonic event, %. Hydrocarbon destruction ratio is directly associated with and completely based on the intensity of tectonic movement. This is consistent with the research results that the unconventional oil and gas reservoirs which formed under non-buoyancydriven are widely continuous distribution, and their formation and distribution are not controlled by structures and traps (Song et al. 2015). If the petroliferous basin has a large area, it is more scientific and reasonable to determine the hydrocarbon destruction ratio values based on statistical analysis of tectonic movement intensities according to more data from their coordinate points. On the basis of the above methods and technical background, several critical parameters were obtained for the four sets of target layers in the platform of the Tarim Basin, i.e. Cambrian, Ordovician, Silurian and Carboniferous System, including relative original hydrocarbon accumulation amount (hydrocarbon accumulation probability), hydrocarbon destruction rate due to tectonic events, relative destroyed hydrocarbon amount and relative remained resource potential. Figure 10.19a and b illustrates the prediction of relative hydrocarbon accumulation probability before tectonic event, and relative remained hydrocarbon amount after tectonic events, in Carboniferous reservoir layers of Tarim basin. From analysis of predicted results, three points can be concluded as follows. Firstly, the accumulated oil and gas resources in Carboniferous focus on three favorable areas, which reflect comprehensive results of original oil and gas accumulations in three different stages of at 298, 227, 38 Ma as shown in Fig. 10.19a. It is the space and time combination of favorable hydrocarbon source areas, favorable reservoir areas, favorable caprock areas and lower potential areas. We also compared the higher accumulation probability with discovered oil and gas reservoirs, it can be seen from Fig. 10.19a that there are three favorable oil and gas accumulation areas, including continuous area of Tabei and Tazhong area (region A), eastern part of the Tabei Uplift (region B), the Bachu Uplift and its northern slope (region C). Hydrocarbon exploration of Carboniferous reservoir layers started in 1989 and 93 wells have been drilled by 2010, with 34 wells being identified as commercial production wells,

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Fig. 10.19 a Relative original hydrocarbon accumulation amount (probability of hydrocarbon accumulation) of Carboniferous reservoirs before tectonic movements in the Tarim Basin and b relative remained potential hydrocarbon resource of Carboniferous reservoirs after tectonic movements in the Tarim Basin

and 59 wells as failed. Successful prospective wells are mainly distributed in region A with relatively high original oil and gas accumulation probability (Fig. 10.19a) and relatively high remained oil and gas potential resources (Fig. 10.19b), and the failed wells are mainly distributed in regions B and C with relatively low original oil and gas accumulation probability (Fig. 10.19a) and relatively low remained oil and gas potential resources (Fig. 10.19b). Secondly, during the geological history, the accumulation of hydrocarbon in the southern Tarim Basin was damaged by tectonic movements. The Carboniferous oil

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and gas reservoirs have suffered alterations, reformations and destruction due to three tectonic cycles in about 254, 220, 24 Ma. The original accumulated hydrocarbon resources (Fig. 10.19a) in the Bachu Uplift, its northern slope and the southern Tazhong Uplift have been almost destroyed. There are 9 failed wells in the above areas, namely, MC1, MX2, TZ64, TZ18, TZ52, H4, Q2, K1, GD1, all of which were drilled in the original high accumulated hydrocarbon areas before tectonic events (Fig. 10.19a) and low remained hydrocarbon areas after tectonic events (Fig. 10.19b). Studies show that Carboniferous oil and gas reservoirs are formed during 298 Ma and destroyed during 220 Ma by tectonic events, and 15% of the 59 failed wells were result by destruction of oil and gas reservoirs in tectonic events. These failed wells are mainly distributed in the south-west region of the Tarim Basin, thereby making it obvious that exploration should be concentrated in the north-west region, that is, the Tabei Uplift and its eastern parts, and the Tazhong Uplift and its northern parts. There is about 12.337 billion tons of oil and gas resources in the Tarim Basin based on China’s third round of oil and gas resources evaluation (Tarim oil company, PetroChina 2002). At present, a lot of dry asphalt has been discovered in the Silurian sandstone layers, where its original reserves are about 8.6 billion tons. They were believed to be formed due to tectonic reformation at the end of Devonian Period (Lu et al. 2007; Huang et al. 2016a). Based on hydrocarbon destruction rate at the end of Permian and Cretaceous in the Tazhong area, the destroyed oil and gas amount was calculated to be more than 15.17 billion tons. Taking the three important tectonic cycles into account, the calculated total destroyed amount exceeds 23.77 billion tons, accounting for 19.2% of total current hydrocarbon resources in the Tarim Basin, indicating that 65.8% of original oil and gas resources have been destroyed. Thirdly, the most favorable exploration areas of Paleozoic strata in the Tarim Basin are distributed in the Tabei Uplift and the Tazhong Uplift. Figure 10.20 illustrates the comprehensive results of original hydrocarbon accumulation in multiple layers at multistage, and hydrocarbon amount destroyed due to multiple tectonic events in the Paleozoic strata in the Tarim Basin. Studies have shown that the largest remained potential resource areas are located in the Tabei and Tazhong Uplifts, and parts of the Bachu Uplift. The discovered oil and gas reservoirs, high oil and gas production wells, and failed wells were considered as the test and examination for theoretical prediction of remained hydrocarbon potential resource in target reservoir layers, and the results indicate that the coincidence rate is more than 90%. 86% of the discovered commercial oil and gas reservoirs are distributed in the predicted favorable accumulation areas with oil and gas accumulation probability larger than 50%, 95% of which are in areas with high remained oil and gas potential resource after multistage of tectonic events. Among 294 exploration wells, those with daily production of over 100 tons (oil equivalent) are distributed in the predicted favorable accumulation areas with oil and gas accumulation probability larger than 50%, over 93% are distributed in areas with high remained oil and gas potential resource; over 70% of the 156 failed wells are distributed in areas with oil and gas accumulation probability less than 25%, and 19% are distributed in the areas where have experienced large-scale hydrocarbon accumulation but followed by large tectonic destruction. It is realized

10.6 Summary

363

Fig. 10.20 Comprehensive prediction and evaluation for remained oil and gas potential resource of Paleozoic strata after multiple adjustments, alterations and destructions on oil and gas reservoirs in the Tarim Basin

that consideration of tectonic movements destruction on oil and gas reservoirs can reduce their exploration risks by more than 19%.

10.6 Summary Tectonic movements of basins exert significant control on the transformation of oil and gas into bitumen, heavy oil, dry gas and oil and gas seeps. Investigations on the changes of oil and gas reservoirs through tectonic activities, and quantitative evaluation of remained oil and gas resources have important significance for understanding the distribution and exploration of current oil and gas reservoirs. The Tarim Basin in China has a complex tectonic history, resulting in the migration and accumulation of oil and gas, transformation of oil and gas reservoir types, phase variation and damage of hydrocarbons, as well as the low success rate of exploration wells. At least six major tectonic movements are identified that influenced the distribution, reformation and destruction of oil and gas reservoirs in this basin. The destruction of oil and gas reservoirs by tectonic events is mainly controlled the intensity, frequency, order of tectonic events, and cap sealing ability. Thus, intense tectonic activities can lead to greater destruction. A strong plastic cap rock would ensure higher preservation of oil and gas. The superimposition of strong-strong tectonic events destroys oil and gas reservoirs, the superimposition of strong–weak transforms types of reservoirs, and the superimposition of weak-weak protects the reservoirs. In this study, based on geological analysis and logical deductions, we establish a quantitative relationship

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among the destroyed hydrocarbon amount and the original accumulated hydrocarbon amount, hydrocarbon destruction rate, tectonic events such as movement number, intensity, order, and cap seal capacity (fc). By calibrating the model with measured geological parameters, destroyed oil and gas amount was evaluated by applying this model. The final results indicate that about 68%, 59%, 28% and 0% of accumulated oil and gas earlier before tectonic events was destroyed after tectonic events happed at about 510 Ma, 298 Ma, 227 Ma and 38 Ma, respectively, about 1.9 billion tons oil and gas are remained as potential resources. Over 60% of the original hydrocarbon amount has been destroyed in the Tarim Basin, more than 95% of oil and gas reservoirs and over 93% of high production exploration wells are located in predicted favorable areas with high remained potential oil and gas resource, whereas 70% of failed wells are located outside these areas. A careful evaluation of the damaged oil and gas reservoirs due to tectonic events can considerably enhance the success rate of hydrocarbon exploration. The core content of this chapter has been published in Marine and Petroleum Geology (Pang et al. 2012a, 2018).

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Zhan S, Chen Y, Xu B, et al. 2007. Late Neoproterozoic paleomagnetic results from the Sugetbrak Formation of the Aksu area, Tarim basin (NW China) and their implications to paleogeographic reconstructions and the snowball Earth hypothesis. Precambrian Research, 154: 143–158. Zhang C L, Ye X T, Zou H B, et al. 2016. Neoproterozoic sedimentary basin evolution in southwestern Tarim, NW China: New evidence from field observations, detrital zircon U-Pb ages and Hf isotope compositions. Precambrian Research, 280: 31–45. Zhang C L, Zou H B, Li H K, et al. 2012. Multiple phases of Neoproterozoic igneous activity in Quruqtagh of the northeastern Tarim Block, NW China: Interaction between plate subduction and mantle plume? Precambrian Research, 222–223: 488–502. Zhang C L, Zou H B, Li H K, et al. 2013. Tectonic framework and evolution of the Tarim Block in NW China. Gondwana Research, 23: 1306–1315. Zhang G Y, Zhao W Z, Wang H J, et al. 2007. Multicycle tectonic evolution and composite petroleum systems in the Tarim Basin. Oil & Gas Geology, 28(5): 653–663. Zhang J, Pang X Q, Liu L F, et al. 2004. Bitumen sandstone distribution characteristics and geological significance of Silurian System, Tarim Basin. Chinese Science: Earth Science, 34: 169–176. Zhang L, Wang Q Y, Chen N S, et al. 2014a. Geochemistry and detrital zircon U-Pb and Hf isotopes of the paragneiss suite from the Quanji massif, SE Tarim Craton: Implications for Paleoproterozoic tectonics in NW China. Journal of Asian Earth Sciences, 95: 33–50 Zhang S C, Huang H P, Su J, et al. 2014b. Geochemistry of alkylbenzenes in the Paleozoic oils from the Tarim Basin, NW China. Organic Geochemistry, 77: 126–139 Zhang S C, Zhang B M, Li B L. et al. 2011. History of hydrocarbon accumulations spanning important tectonic phases in marine sedimentary basins of China: Taking the Tarim Basin as an example. Petroleum Exploration and Development, 38(1): 1–14. Zhao G C, Guo J H. 2012. Precambrian geology of China: Preface. Precambrian Research, 222–223: 1–12. Zhao G C, Zhai, M G. 2013. Litho tectonic elements of Precambrian basement in the North China Craton: review and tectonic implications. Gondwana Research, 23: 1207–1240. Zhao J Z, Li Q M, Wang Q H, et al. 2004. On the formation and distribution of mid-large oil and gas fields in the Tarim Basin. Journal of Northwest University (Natural Science Edition), 34(2): 212–217 (in Chinese with English abstract). Zhao J Z. 2001. Timing marine petroleum accumulation in the Tarim Basin by oil/gas-water contact retrospecting. Petroleum Exploration and Development, 28(4): 53–56. Zhou H Y, Pang X Q, Jiang Z X, et al. 2003. Quantitative evaluation of petroleum accumulation systems around Manjiaer Sag in Tarim Basin. Xinjiang Petroleum Geology, 24(5): 382–385 (in Chinese with English abstract). Zhou J X, Xu F Y, Wang T C, et al. 2006. Cenozoic deformation history of the Qaidam Basin, NW China: Results from cross-section restoration and implications for Qinghai—Tibet Plateau tectonics. Earth and Planetary Science Letters, 234(1–2): 195–210. Zhu G Y, Chen F R, Chen Z Y, et al. 2016. Discovery and basic characteristics of high-quality source rocks found in the Yuertusi Formation of the Cambrian in Tarim Basin, China. Journal of Natural Gas Geoscience, 1(1): 21–33. Zhu G Y, Wang H T, Weng N, et al. 2015b. Geochemistry, origin and accumulation of continental condensate in the ultra-deep-buried Cretaceous sandstone reservoir, Kuqa Depression, Tarim Basin, China. Marine and Petroleum Geology, 65: 103–113 Zhu G Y, Zhang S C, Su J, et al. 2013. Alteration and multi-stage accumulation of oil and gas in the Ordovician of the Tabei Uplift, Tarim Basin, NW China: Implications for genetic origin of the diverse hydrocarbons. Marine and Petroleum Geology, 46: 234–250. Zhu G Y, Zou C N, Yang H J., et al. 2015a. Hydrocarbon accumulation mechanisms and industrial exploration depth of large-area fracture-cavity carbonates in the Tarim Basin, western China. Journal of Petroleum Science and Engineering, 133: 889–907 Zieba K J, Grøver A. 2016. Isostatic response to glacial erosion, deposition and ice loading. Impact on hydrocarbon traps of the southwestern Barents Sea. Marine and Petroleum Geology, 78: 168–183.

Chapter 11

Evaluation of the Global Oil and Gas Resources

New Understanding: (1) Global total generated hydrocarbon amounts and their distributions as different types of resources are jointly controlled by source rock characteristics, hydrocarbon dynamic fields, and essential parameters such as preservation efficiency, ratio of movable hydrocarbons and recoverable factors. (2) The unified genetic model and mass balance equations among the hydrocarbon generation, different occurrences and major controlling factors have been established to realize the evaluation of hydrocarbon amounts in different forms as by lost and preserved as 3-type and 3-level resources. (3) The global generated hydrocarbons is 141.84 × 1012 t, 82% been lost or destroyed, 7.7% is unmovable in reservoirs, and only 18% accumulated as resources: the current, successive and prospective are 1.4%, 7.6% and 9.0%, respectively; of them 8.8% for conventionals, 48.7% for the tights and 42.5% the shales. (4) The global potential current, successive and prospective resources could sustain human society for another 200, 1500 and 3000 years, respectively, if produced in annual production rate as in 2019. Humanity should focus its efforts on extracting them safely and greenery, rather than worrying about their exhaustion.

11.1 Introduction and Issue With the increasing consumption of hydrocarbons and energy shortage across the globe, it is critical for petroleum companies and governments to know the amount of hydrocarbon resources remaining on Earth that we can depend on. Human knowledge about the source, formation and distribution of hydrocarbons has advanced a lot in the past over one hundred years, which makes the evaluation of global hydrocarbon resources possible. Early research in the nineteenth century believed that hydrocarbons were accumulated in traps driven by buoyance (White 1885; Levorsen 1956; Longwell 2002). Since then, following more than a century of studies, geologists came to realize that hydrocarbons were originated from plants and animal remains © Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_11

369

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11 Evaluation of the Global Oil and Gas Resources

(Brooks 1935; Robinson 1966) which were mainly distributed in sedimentary basins with a large number of organic materials preserved for at least a billion years (Tissot and Welte 1978; Ghori et al. 2009; Sun and Wang 2016). Inorganic origin also has an important influence on the formation and distribution of petroleum (Kenney et al. 2002; Lobanov et al. 2013; Huang et al. 2017; Brovarone et al. 2020), but no commercial hydrocarbon reservoirs found so far are of inorganic origin (Glasby 2006; Höök et al. 2010; Selley and Sonnenberg 2014). The amount of global ultimate hydrocarbon resources is controlled by the total amount of generated hydrocarbons from the original organic matter, the conditions of the hydrocarbon migration, accumulation, preservation and exploration in all sedimentary basins in the world. Hydrocarbons are unrenewable and will be gradually exhausted with the continuous exploration. Figure 11.1 illustrates the variation of global annually proved reserves and produced hydrocarbons. However, the estimate numbers released each year by the USGS, IEA and other organizations since the beginning of the new century did not reflect the actual amount of ultimate hydrocarbon resource, but are realistic resources and keep growing with the advance of science and techniques and discovery of new type of hydrocarbon reservoirs. For example, the USGS estimated in 2000 the global residual hydrocarbon resources was 1400 × 108 t oil equivalent (USGS 2003). The value did not decrease but increased to 4330 × 108 t in the 2015 USGS report, although 1975.1 × 108 t had been extracted between 2000 and 2015 (BP 2016). Similarly, China’s estimate of total in-place hydrocarbons resources in China also increased gradually with more explorations and improved techniques, from 280 × 108 t in 1975 to 1126 × 108 t in 2000 and then to 2257 × 108 t in 2015 (Table 11.1). What are the total ultimate petroleum resources on the earth? What is the composition? With the growingly important role of hydrocarbons in our society and the fear of shortage and exhaustion, these questions inevitably confront us (Kennedy and Norman 2005). Since the end of the nineteenth century when the theories of buoyancy-driven hydrocarbon migration (Cordell 1977) and trap-controlling hydrocarbon accumulation (Levorsen 1956) were proposed, conventional hydrocarbon exploration have been developed rapidly, and the Pool Scale Sequence Method (Lee and Wang 1985) of hydrocarbons reservoirs was established to evaluate the global conventional hydrocarbon resources, but oil and gas resources formed in non-trap structures are not taken into account. Since the theory of petroleum organic genesis (Edwards 1997) was established, geologists quantitatively evaluated petroleum resources by calculating the total generated hydrocarbons amount (Pang et al. 1993a) in sedimentary basins and analyzing the efficiency of hydrocarbon migration and accumulation, but also the oil and gas resources formed by non-buoyance-driven were not taken into account. The discovery and study of unconventional hydrocarbons reservoirs (Schmoker and Oscarson 1995) at the end of the twentieth century facilitated the quantitative evaluation of unconventional tight hydrocarbons resources, which was done by studying the in-place accumulated hydrocarbons in sedimentary basins and analyzing key parameters such as the ratio of movable hydrocarbons (Gao and Li 2015) in reservoir layers, but the potential oil and gas resources in future were not taken into account. The ability of recovering natural gas hydrate (NGH) has also been concerned by a lot of countries and research agencies (Kerr 2004), the

11.1 Introduction and Issue

371

Fig. 11.1 Variation of oil/gas annual production and proved reserves in the world. a Oil production world summary. b The variation of world annual proven reserves, the proven reserves in the new century have increased substantially due to the increased knowledge of unconventional oil and gas

NGH potential resource has been estimated by studying the total gas hydrate amount in Gas Hydrate Stable Zone with high pressure and low temperature, however, it is very difficult to obtaining practical recovery factors at present time (Xinhua net 2020). These research advances enable the IEA, USGS, BP and other agencies to assess the global conventional and unconventional hydrocarbons resources under the current technological conditions and publish their results annually (Ehrenfeld 2005). However, it is still impossible to evaluate the global ultimate hydrocarbon resources since the correlations and differences between conventional and unconventional resources have not been clarified. As greenhouse gases are emitted and human living conditions become worse and worse, geochemists and environmental scientists are eager to know how much oil and gas the earth has produced during

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Table 11.1 Past evaluations of oil/gas resources in China by different researchers and institutions (Meyerhoff 1979; Guan et al. 1981; Zhang 1997; Dai 1999; MLR 2016) Units/scholars

Time

Oil and gas resource evaluation results

1. Japan External Trade Organization

1975

Total continental resource is 135 × 108 t, recoverable resource is 45 × 108 t (oil and gas)

2. D D Wu

1976

Total resource is 300–500 × 108 t, recoverable resource is 100–200 × 108 t (oil and gas)

3. Q S Wei

1976

Total continental resource is 228 × 108 t, recoverable resource is 76 × 108 t (oil and gas)

4. A A Meyerhoff

1979

Total resource is 280 × 108 t, recoverable resource is 93 × 108 t (oil and gas)

5. T B An, H F Zhang

1980

Total resource is 500–700 × 108 t (oil)

6. S C Guan

1981

Total resource is 280 × 108 t (oil)

7. China Energy Society

1984

Total resource is 470–640 × 108 t (oil)

8. China Ministry of Geology and Mineral Resources

1987

Total resource is 614.7 × 108 t (oil) and 26.8 × 1012 m3 (gas)

9. China Ministry of Petroleum Resources

1987

Total resource is 787.5 × 108 t (oil) and 33.3 × 1012 m3 (gas)

10. Masters et al

1987

Recoverable resource is 100 × 108 t (oil) and 6.63 × 1012 m3 (gas)

11. OGJ Journal

1987

Recoverable resource is 25.1 × 108 t (oil) and 0.87 × 1012 m3 (gas)

12. J X Chen

1991

Total resource is 773.08 × 108 t (oil) and 25.92 × 1012 m3 (gas)

13. Planning Office of Shishan Institute, China Ministry of Geology and mineral resources

1991

Total resource is 814.7 × 108 t (oil)

14. China National Petroleum Corporation

1994

Total resource is 940 × 108 t (oil) and 38.14 × 1012 m3 (gas)

15. K Zhang

1997

Total resource is 834.5 × 108 t (oil) and 52.5 × 1012 m3 (gas)

16. J X Dai

1999

Total resource is 38.03 × 1012 m3 (gas)

17. X Q Pang, Z J Jin et al

2000

Total resource is 834.5 × 108 t (conventional oil) and 52.5 × 1012 m3 (conventional gas) (including 26 basins)

18. China Ministry of Land and Resources

2005

Total resource is 1086 × 108 t (oil) and 56 × 1012 m3 (gas)

19. China Ministry of Land and Resources

2016

Total resource is 1257 × 108 t (oil) and 90.3 × 1012 m3 (gas)

11.2 Identification and Distribution of Oil and Gas Resource Types

373

its evolution, where it has gone and what its impact on the human environment has been. This study focuses on three essential but unsolved challenges: (1) the genetic correlations and differences between conventional and unconventional resources; (2) the major factors controlling the formation and distribution of different types of hydrocarbon resources during the evolution of sedimentary basins; (3) the mass balance equations involving the total generated hydrocarbons amount from source rocks, the lost and dispersed hydrocarbons amounts during migration and accumulation, and the preserved hydrocarbons amounts available as potential resources. In this study, all hydrocarbon resources are divided into three categories by their geological characteristics in our evaluation, including the conventional hydrocarbon resource, the tight hydrocarbon resource, and the shale hydrocarbon resource. The conventional resources include the normal oil and gas in conventional trap, the heavy oil and asphalt in reformed trap (Meyer and Attanasi 2003) and the natural gas hydrates in special trap with high pressure and low temperature (Milkov et al. 2003). The shale resources include those in shales and coalbeds (Dong et al. 2015), whereas oil shale (Knaus et al. 2010) is excluded because it is not oil in geological conditions. To make the discussion easier, we assume that the hydrocarbon resource type does not reform or change to another type after it is formed. Also in this study, all hydrocarbon resources are classified into three levels by the recovery factor, including the realistic level (I), the expected level (II) and the ultimate level (III), corresponding to the recovery factor of the current value, a factor of up to 50% and a ultimate factor of up to 100%, respectively. The primary purpose of this study is to understanding the amount of oil and gas produced in the Earth’s evolution and where it went, finally evaluate the amount of global hydrocarbon resources base on the three types and the three recovery levels.

11.2 Identification and Distribution of Oil and Gas Resource Types 11.2.1 Identification of Oil and Gas Resource Types The hydrocarbon resource types are identified based on the drilling results of reservoirs and their distribution characteristics in petroliferous basins as shown in Fig. 11.2. The total generated, remained and expelled hydrocarbons are illustrated in Fig. 11.2a. The conventional resources (red region in Fig. 11.2b) are distributed in reservoirs with high porosity and permeability (F > 10 ± 2%, K > 1 md) above the buoyance-driven hydrocarbon accumulation depth (BHAD) (Pang et al. 2012). The unconventional tight resources (yellow region in Fig. 11.2b) are widely distributed in reservoirs with low porosity and permeability (F = 10 ± 2% to 2 ± 1%, K = 1.0–0.01 md) (Zou et al. 2013) between the BHAD and the active source-rock depth limit (ASDL) (Pang et al. 2020). The unconventional shale resources (pink region

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11 Evaluation of the Global Oil and Gas Resources

Fig. 11.2 Conceptual model for the formation and distribution of the three types of hydrocarbon resources controlled by dynamic boundaries in petroliferous basins. a Variation of the hydrocarbon generation potential index ((S1 + S2 )/TOC) of source rocks with increasing depth; Qrs1 —residual hydrocarbons (HCs); Qrs2 —potential HCs; Qe —accumulative HCs expelled from source rocks; HGT—hydrocarbon generation threshold; HET—hydrocarbon expulsion threshold; ASDL—active source-rock depth limit. b Distribution of the three types of hydrocarbons resources: BHAD— buoyance-driven hydrocarbon accumulation depth, red—conventional resources, yellow—tight resources, pink—shale resources. c Vertical distribution of original hydrocarbons amount: pink— shale resource (Qrs ), red—conventional resource (Qec ), yellow—tight resource (Qeu )

in Fig. 11.2b) are widely distributed within the source rocks of low porosity (F < 20%) and ultra-low permeability (K < 0.01 md), and can be further subdivided into coalbed hydrocarbon resource and shale oil/gas resource according to the lithology of the source rocks. Figure 11.2c illustrates the vertical distribution of hydrocarbon amounts available for the formation of conventional oil and gas resource (red), shale oil and gas resource (pink) and tight oil and gas resource (yellow).

11.2.2 Dynamic Boundaries for Oil and Gas Resources Distribution in the Underground Hydrocarbon dynamic boundaries are critical conditions dividing the formation and distribution of different hydrocarbons resources, and are also called hydrocarbons thresholds. The controlling of hydrocarbon generation threshold (HGT), hydrocarbon expulsion threshold (HET), buoyancy-driven hydrocarbon accumulation depth (BHAD), hydrocarbon accumulation depth limit (HADL) and active source-rock depth limit (ASDL) on hydrocarbons resources are shown in Figs. 11.2 and 11.3, and can be identified by drilling results, reservoirs formation conditions and distribution characteristics. HGT refers to the critical condition for hydrocarbons to generate from source rocks massively as shown in Fig. 11.3a1, which is generally identified by the maturity of source rocks with an average vitrinite reflectance of Ro ≈ 0.5% (Tissot and Welte 1984), theoretically sets the minimum depth of shale oil/gas resources.

11.2 Identification and Distribution of Oil and Gas Resource Types

375

Fig. 11.3 Variation of hydrocarbon dynamic boundaries of source rocks and sandstone reservoirs with increasing vitrinite reflectance and burial depth in the six petroliferous basins in China. a Variation of residual hydrocarbons amounts and their relations to the HGT, HRP and ASDL (a1), and variation of expelled hydrocarbons amounts and their relations to HET, HEP and ASDT (a2). b Variation of sandstone porosity with increasing depth and their relations to BHAD and HADL (b1), and variation of the maximum sandstone porosity with increasing maturity of Ro and their relations to HADLs and the dry layer thickness ratio (b2)

HET is the critical condition for hydrocarbons to be expelled from source rocks in separate phases as shown in Fig. 11.3a2, indicated by the maximum value of hydrocarbon residual peak (Qrm) and is generally identified by the maturity of source rock with Ro = 0.7 ± 0.15% (Pang et al. 2005), setting the minimum depth of conventional resources formation. ASDL is the critical condition of source rock transformation from active state to be exhausted state with increasing burial depth as shown in Fig. 11.3a2, identified majorly by the source rock maturity with Ro = 3.5 ± 0.5%, it theoretically controls the maximum formation depth of all hydrocarbon resources. BHAD is the critical condition for the transition of the dominating hydrocarbon migration force from the buoyancy force to non-buoyancy forces, and it corresponds to the boundary between the conventional resources and unconventional resources as shown in Fig. 11.3b1, generally identified by the porosity of 10 ± 2%, permeability of 0.01 md and pore throat radius of 1 µm in sandstone reservoirs, it sets the maximum depth for the formation of all conventional hydrocarbon resources. HADL is the maximum depth for a hydrocarbon accumulation, and corresponds to the drilling results displaying a dry layer ratio reaching 100%, as showed in Fig. 11.3b2, it is generally identified by the sandstone porosity of 3.0 ± 1% and pore throat radius of 20 ± 10 nm, theoretically controls the maximum depth for the formation of unconventional tight hydrocarbons resources.

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11 Evaluation of the Global Oil and Gas Resources

11.2.3 The Unified Model for the Distribution of Different Oil and Gas Resources The hydrocarbons dynamic field refers to an area with similar oil/gas sources, migration driving forces, accumulation styles and resource types confined by a dynamic boundary. The unified genetic model is established to address the differences and correlations among the formation and distribution of three types of hydrocarbon resources in petroliferous basins in the world (Fig. 11.4). The conventional resource is formed and distributed in the free-hydrocarbon dynamic field (F-HDF) above the BHAD, with oil/gas resource quantity determined by hydrocarbon amount expelled from source rocks located between HET and BHAD. Unconventional tight resources are formed in the confined-hydrocarbon dynamic field (C-HDF), with oil/gas resource quantity determined by hydrocarbon amount expelled from the source rocks located between BHAD and ASDL. Unconventional shale resources are formed in the bound-hydrocarbon dynamic field (B-HDF) within source rocks, where the oil/gas resources are controlled by hydrocarbon amount remaining within the source rocks between HGT and ASDL. The maximum depths of these three types of resources gradually decrease with increasing heat flow in petroliferous basins. The identification of hydrocarbon thresholds, division of hydrocarbons dynamic fields, and jointly controlling on three type resources have been discussed in a previous paper (Pang et al. 2021).

11.3 Evaluation Methods of Oil and Gas Resources 11.3.1 Estimation of the 3-Type and 3-Level Resources Based on Mass Balance Estimating hydrocarbon resources by mass balance is considered the most logical and accurate method (Bishop et al. 1983), however, it has not been successfully applied to solve relative problems since the relationships between the amounts of different hydrocarbons were not established. Furthermore, there were no necessary analytical instruments in the past to obtain some important parameters for the calculation of hydrocarbons resources, such as the radius of micro-nanometer pore throat in the reservoir layers, the ratio of immovable hydrocarbons to total hydrocarbons in tight reservoir layers. The establishment of the unified model, the rapid development of modern computer technology and the advance of analytical instruments allowed us to apply mass balance to evaluate the global ultimate hydrocarbon amount in different forms. The calculations are based on Eqs. 11.1–11.5 with relevant 5 essential geological parameters pre-obtained. Q i j = Q generated · K i · Ri · Mi · E i j (i = C, U, S; j = R, E, P)

(11.1)

11.3 Evaluation Methods of Oil and Gas Resources

377

Fig. 11.4 The unified genetic model of hydrocarbon dynamic boundaries and fields jointly controlling on the three types of hydrocarbon resources in petroliferous basins. The positions of the dynamic boundaries have been corrected for the eroded strata effect. Blue—F-HDF with conventional resource; yellow—C-HDF with tight resource; pink—B-HDF with shale resource. BHAD—buoyance-driven hydrocarbon accumulation depth; HADL—hydrocarbon accumulation depth limit; ASDL—active source-rock depth limit

Q total = Q c + Q u + Q s

(11.2)

Q realistic = Q i × E current

(11.3)

Q expected = Q i × E 50%

(11.4)

Q ultimate = Q i × E 100%

(11.5)

In the above equations, Qij is the total recoverable resources of the 3-types (i) and 3 levels (j), where i = C, T, S, referring to Conventional, unconventional Tight and Shale resources, respectively, and j = R, E, U, referring to Realistic, Expected and Ultimate resource, respectively; Qgenerated is the amount of total hydrocarbons originated from organic matters in source rocks and is related to the thickness (H, m), area (S, km2 ), total organic content (TOC, %), kerogen type index (KTI) and thermal for forming maturity (Ro, %); Ki is the amount ratio of initial hydrocarbons available ∑ type i resource to the total generated hydrocarbons (Ki < 1 and Ki = 100%); Ri

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11 Evaluation of the Global Oil and Gas Resources

is the preservation efficiency of generated hydrocarbons in migration, accumulation and reformation (Ri ≤ 100%), larger Ri indicates more preserved hydrocarbons; Mi is the amount ratio of movable hydrocarbons to total hydrocarbons in reservoir layers, reflecting the state of hydrocarbon occurrence (1 ≥ Mi ≥ 0), larger Mi indicates more movable hydrocarbons preserved in reservoir layers; Eij is the level j recovery factor of the type i resource (0 ≤ Eij < 100%), greater Eij means higher proportion of hydrocarbon resource able to be produced from reservoirs, which will increase and tend to approach but never reach 100% with improving technology.

11.3.2 Acquisition and Validation of Five Essential Parameters Total generated hydrocarbons amount (Qgenerated ). There are two steps in the calculation of Qgenerated : the first step is to calculate the total generated hydrocarbons amount in 6 representative basins and the original ratios of 3-type hydrocarbons by actual geological data; the second step is to derive the global total generated hydrocarbons amount (Qgenerated ) by Eq. 11.1, the global realistic conventional resource amount (Qij ) is obtained from previous study and other 4 relative parameters are confirmed by studying drilling results of hydrocarbon reservoirs in 6 representative basins in the first step. The amounts of total remaining and total expelled hydrocarbons in the 6 basins are calculated by Eqs. 11.6 and 11.7, and the total generated hydrocarbon amounts are calculated by Eq. 11.8 or Eq. 11.8. Figure 11.5 illustrates a case study in the Songliao Basin of China, where the Upper Cretaceous Qingshankou Formation acts as the major source rocks. The variations of the source rock thickness, organic carbon content and thermal maturity are displayed in Fig. 11.5a, and the hydrocarbons generation intensity, remaining intensity and expulsion intensity are shown in Fig. 11.5b. By summarizing results of each source rock unit, the total generated, remaining and expelled hydrocarbons amounts from all source rocks in the six basins in China were calculated. Then, the total generated hydrocarbon amounts in all basins in China and over the world were derived from Eq. 11.1, and expressed in Eqs. 11.6–11.10 as below:   Sk · Hk · Dk · T OCk · Rr K T Ik , Rok , T OCk , Φk (k = 1, 2, . . . , N ) (11.6)   ∑ Sk · Hk · Dk · T OCk · Re K T Ik , Rok , T OCk , Φk (k = 1, 2, . . . , N ) Qe = (11.7) Qr =

∑

Q generated = Q generated =

∑

∑

Qr k +

∑

Q ek (k = 1, 2, . . . , N )

(11.8)

  Sk · Hk · Dk · T OCk · R p K T Ik , Rok (k = 1, 2, . . . , N ) (11.9)

11.3 Evaluation Methods of Oil and Gas Resources

379

Fig. 11.5 The areal distribution of source rock characteristics and related hydrocarbons amounts from the K2 Q1 of the Upper Cretaceous Qingshankou Formation, Songliao Basin, China. a1 source rock thickness (H, m); a2 total organic carbon content (%); a3 thermal maturity (Ro, %); b1 hydrocarbons generation intensity (104 t/km2 ); b2 hydrocarbons retention intensity (104 t/km2 ); b3 hydrocarbons expulsion intensity (104 t/km2 ). Darker color indicates larger index values

Q generated =

Qc K c ·Rc ·Mc ·E cp

(11.10)

In the above equations, Qgenerated is in the unit of ton; S is area (km2 ); H is thickness (m); D is density (t/m3 ); TOC is total organic content (%); KTI is kerogen type index (0–100); Ro is vitrinite reflectance (%); F is porosity (%); k is the number of source rock beds; Rp is hydrocarbons generation rate (kg/Tc) (Pepper and Corvi 1995); Qr is the amount of total hydrocarbons remaining in source rocks (t); Rr is hydrocarbon residual rate (kg/Tc), calculated by the “S1 ” or “A” index (Pang et al. 1993b); Qe is total expelled hydrocarbon amount (t); Re is hydrocarbons expulsion rate (kg/ Tc); Kc , Rc , Mc , Ecp are the same parameters as used in Eq. 11.1, and their values are obtained by studying the results in six representative basins, revised by results of other basins in China and in the world reported in literature. Qc is conventional resources, and the global conventional resources are obtained from others (IEA 2016; EIA 2020).

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11 Evaluation of the Global Oil and Gas Resources

Initial ratio (Ki) of different type of hydrocarbon amount to total generated. The ratio (Ki ) of the initial hydrocarbon amount available for type i resource formation to the total generated hydrocarbon amount was obtained from the study of hydrocarbons generation, retention, and expulsion of effective source rocks in the six basins as shown in Fig. 11.5. Figure 11.6 illustrates a case study of the three initial ratios (Kc, Ku and Ks) of the Qingshankou Formation source rocks of the Songliao Basin, and the results are 18.9% for Kc, 47.4% for Ku and 33.7% for Ks, respectively. Figure 11.7 shows the results from all major source rocks in the six basins, from which two observations can be made. First, the HETs of all studied source rocks are almost the same regardless of their kerogen types, corresponding to Ro = 0.7 ± 0.1%, and the BHADs are the same for all sandstone reservoirs with Ro = 1.2 ± 0.1% and the ASDLs are the same for all source rocks with Ro = 3.5 ± 0.5%. Second, Ki varies in a range of ± 10%: Kc varies from 8.7 to 11.8% with an average of 10.3%, Ku varies from 35.0 to 54.3% with an average of 44%, and Ks varies from 35.5 to 54.1% with an average of 46%. The variations of Ki among different source rocks or in small basins are significant, but very similar in big basins. Statistically, we can reasonably postulate that the Ki should be the same for all the basins of China and those over the world. Ratio of movable hydrocarbon amount to the total in reservoirs (Mi). The amount ratio of movable hydrocarbons to total hydrocarbons in the reservoirs is determined by statistical analysis of results published in literature (Mansfield and Issa 1994). High pressure water flood experiments (water displacing oil) were also conducted to obtain data on Mi at different pore-throat conditions. A lot of hydrocarbons within small pore-throats in tight reservoirs and shale source rocks are unmovable, occurring as dead oil or dead gas. Hydrocarbons which are movable in reservoirs constitute the potential resources (Li et al. 2020; Chen et al. 2019). Proportion of movable hydrocarbons in shale and tight reservoirs depends on the distribution of pore throat radius in the reservoir layers. It is difficult for reservoir layers with pore throat radius less than less than 30 nm to form hydrocarbon resources (Zou et al. 2015a). Hydrocarbons in free phase have the highest value of Mi (Jarvie 2012), reach 100%; the Mi value is also related to the physical state of hydrocarbons in reservoir layers, with a higher gas-to-oil ratio leading to a higher Mi value (Theloy 2013). The Mi values for shale and tight reservoirs can also be obtained from the oil–water flooding NMR experiment (Gao and Li 2015) or the oil saturation index analysis (Jarvie 2012). All the data collected from literatures are summarized in Table 11.2. Hydrocarbon preservation efficiency (Ri ). Hydrocarbon preservation efficiency (Ri ) in the migration, accumulation and reformation was calculated by Eq. 11.11, using the data of hydrocarbon generation amount (Qp ) and accumulated amount (Qa ) in the mature petroleum systems of the six representative basins, larger Ri indicates less lost and disperse of hydrocarbons and more accumulation in petroleum system. The statistical results of Ri from 6 representative basins, revised by the results from other basins, were then applied to all the basins in China and over the world. Figure 11.8 illustrates Ri distributions in 6 representative petroliferous basins in China.

11.3 Evaluation Methods of Oil and Gas Resources

381

Fig. 11.6 A case study of hydrocarbon generation, expulsion, and vertical distribution and their control on resource types in the profile of the Qingshankou Formation of Songliao basin, China. a A geological cross section showing the distribution of major source rocks and their related reservoirs. b Variation of hydrocarbon generation, remaining and expulsion characteristics with increasing thermal maturity: b1—hydrocarbon generation potential index and its relations to HET, ASDL and hydrocarbon expulsion amount (Qe ); b2—hydrocarbon expulsion rate and its relations to the porosity variation and BHAD of the reservoir layer; b3—remaining and expelled hydrocarbons available for forming the three types of resources

Ri =

Q ai Q pi

(i = 1, 2, . . . , N )

(11.11)

Hydrocarbon recovery factor in production (Eij ). The current recovery factors (Eij , j = R) for 3-types of realistic resources in production are obtained from statistical analysis of results published in literature (Table 11.3). The Eij value increases with technological advancement (BP 2018), for example, the average recovery factor for conventional oil reservoirs in the Daqing Oilfield of the Songliao Basin increased from 5% in 1972 to 40% in 2016. The current hydrocarbon extraction technology has been applied to many complex geological fields, including deep water, deep

382

11 Evaluation of the Global Oil and Gas Resources

Fig. 11.7 Vertical distribution of initial hydrocarbon amounts generated and expelled by major source rocks in the 6 representative basins in China. a Tarim Basin, hydrocarbons from Cambrian, Ordovician, Triassic and Jurassic; b Junggar Basin, from the Permian and Jurassic shales; c Ordos Basin, from the Carboniferous, Permian and Triassic; d Sichuan Basin, from Cambrian, Silurian, Permian, Triassic and Jurassic; e Bohai Bay Basin, from Paleogene Shahejie and Dongying formations; f Songliao Basin, from Upper Cretaceous Qingshankou and Nenjiang formations. Pink— hydrocarbons available for the formation of conventional resources; green—for shale resources; yellow—for tight resources. BHAD—buoyance-driven hydrocarbon accumulation depth

strata, desert and plateau, therefore, their current values of ECR in Table 11.3 are thus applied to evaluate the global realistic conventional resource. It is not appropriate to apply the current recovery factors of Eij from unconventional resources to the whole unconventional resources in China and around the world, because they not representatives globally and most of the discovered commercial unconventional reservoirs so far are confined to the areas with shallow burial depth, high hydrocarbon enrichment and better development conditions. Therefore, it is necessary to calibrate the current EUR and ESR by comparing the difference and correlation between the discovered and undiscovered unconventional resources. The original values of EUR and ESR should be corrected by a coefficient of Kfactor before they are applied to evaluate the global unconventional recoverable resources in order to make the results more rational and representative. The average value of Kfactor in the six Chinese basins are 0.59 and 0.34 for shale oil and gas, 0.20 and 0.47 for tight oil and gas. Figure 11.9 illustrates a case study. Correction for recovery factors of the unconventional resources is needed. It is not correct to directly apply the current recovery factors of the currently explored reservoirs to all unconventional oil/gas resources mainly because the factors are not representative. Most of the proved commercial unconventional reserves on the world were confined to very limit areas with shallower burial depth, high hydrocarbon

11.3 Evaluation Methods of Oil and Gas Resources

383

Table 11.2 Statistical results on the amount ratio of the movable oil/gas to total oil/gas in the unconventional oil and gas in the world Type

Movable oil/ gas ratio (%)

Sample number (unit)

Research area and horizon (area names)

Data source (references)

Range of changes (%)

Tight oil

8.61–57.5 (mean 30.7)

12

/

Lei (2017)

50.47

/

Penglaizhen group, west Sichuan

Sima et al. (2017)

53.22–73.3 (mean 63.9)

8

Yanchang group, Ordos Basin

Gao et al. (2018)

Minimum value: 15 Average value: 30 Maximum value: 65

34.5–83.2

/

Yanchang group, Ordos Basin

Wang et al. (2017)

9.7–29.83 (mean 16.1)

6

Yanchang group, Ordos Basin

Bai et al. (2018)

29.44–68.92 (mean 46.7)

21

Lu’er section, jimusar depression, Junggar Basin

Li et al. (2018a)

2.16–46.55 (mean 19.6)

9

3rd section of shahejie formation, Bohai Bay Basin

Chen (2015)

20.78–45.67 (mean 34.2)

4

Yanchang group, Ordos Basin

Gao et al. (2018)

16.27–65.67 (mean 44.9)

24

Yanchang group, Ordos Basin

Wu and Zhao (2017)

10.73–81.86 (mean 48.35)

264

Yanchang group, Ordos Basin

Gao and Li (2015)

2.16–55.94 (mean 27.48)

15

Yanchang group, Ordos Basin

Li et al. (2018b, c)

10.99–61.99 (mean 34.86)

26

Yanchang group, Ordos Basin

Li et al. (2019)

5.38–32.67 (mean 19.5)

12

He8, Sudong area, Ordos Basin

Ming et al. (2015)

Tight gas

2.18–62.57 (mean 30.43)

Shale oil

He8, Sudong area, Ordos Basin

7.73–83.62 (mean 41)

8

He8 and Shan1, Suxi area, Ordos Basin

Liu et al. (2016)

25.33–97.57 (mean 60.37)

30

Shahejie formation, Dongying Li et al. depression, Bohai Bay Basin (2018b, c)

13.54–89.11 (mean 29.36)

17

Barnett Shale

Han et al. (2015)

4.2–16.63 (mean 9.4)

50

Saxony Basin

Zink et al. (2016)

17.30–69.28 (mean 48.15)

30

Lucaogou formation, Junggar Basin

Cao et al. (2017)

7.12–91.29 (mean 29.31)

29

Qianjiang formation, Qianjiang Basin

Chen et al. (2018)

Minimum value: 20 Average value: 40 Maximum value: 70 Minimum value: 10 Average value: 25 Maximum value: 60

(continued)

384

11 Evaluation of the Global Oil and Gas Resources

Table 11.2 (continued) Type

Shale gas

Movable oil/ gas ratio (%)

Sample number (unit)

Research area and horizon (area names)

Data source (references)

> 10.0

/

Posidonia shale

> 30.0

/

Vaca Muerta shale

Ziegs et al. (2017)

3.06–16.25

/

Jiyang Depression, Bohai Bay Sang et al. Basin (2017)

24.3–24.7

2

4th section of shahejie formation, Dongying Depression, Bohai Bay Basin

Li (2014)

8–28

/

3rd section of shahejie formation, Bohai Bay Basin

Zhang et al. (2014)

9–30

/

4th section of shahejie formation, Bohai Bay Basin

23.19–30.84 (mean 27.2)

48

Longmaxi formation, Sichuan Basin

Zhou et al. (2016)

23.6–41.4 (mean 31)

4

Shahejie formation, Dongpu Sag, Bohai Bay Basin

Wang et al. (2015a, b)

Range of changes (%)

Minimum value: 15 Average value: 30 Maximum value: 65

enrichment and good development conditions, which makes the recovery factor of these reservoirs less representative when used to evaluate the current economically and technically recoverable resources for the whole global unconventional oil/gas. Therefore, it is necessary to calibrate EUR and ESR by comprehensive study the difference and correlation of proven and unproven unconventional oil/gas reserves. The original value of EUR and ESR been corrected by a coefficient of Ecalibrate before they are applied to evaluate the global unconventional recoverable resources in order to make the results more reasonable and representative. The correction includes two factors, the burial depth correction factor (Kdepth ) and hydrocarbon enrichment correction factor (Kenrich ). Their relationships are expressed in Eqs. 11.12–11.15 and illustrated by Fig. 11.9. EU R = EU∗ R × E calibrate

(11.12)

E calibrate = K depth × K enrich

(11.13)

∗ K depth = E depth × ∗ K enrich = E enrich ×

 

∗ Q Deconomic Q tatal ∗ QCeconomic Q tatal

 (11.14)  (11.15)

11.3 Evaluation Methods of Oil and Gas Resources

385

Fig. 11.8 Statistical analysis results of three essential parameters for evaluating hydrocarbon resources from the 6 representative petroliferous basins in China, combined with previous research results of these parameters in other resource evaluations in China. a Initial hydrocarbon ratios for three type resources (Ki); b preservation efficiency of conventional resources (Rc); c current recovery factors for Type i resource (Ei): a—Tarim Basin; b—Junggar Basin; c—Ordos Basin; d—Sichuan Basin; e—Bohai Bay Basin; f—Songliao Basin

In the above equations, EUR is the calibrated current recovery factor for all potential unconventional resources, E∗UR is the current measured recovery factor for proven economical unconventional reservoirs. Ecalibrate is the universal correction coefficient for current recovery factor of unconventional oil/gas resources. Kdepth is the depth correction factor. Kenrich is the enrichment condition correction factor. E∗depth is the current recovery factor for proven economic reserves within certain shallow depth available for economically and technologically recovery, QD∗economic is the potential hydrocarbon resource buried in limit shallow depth; Qtotal is the total potential unconventional resources. E∗enrich is the current recovery factor for proven economic reserves within certain high abundance of TOC, QC∗economic is the potential unconventional resource with high abundance of TOC that meets the requirements of economic recovery. For the depth correction factor of shale oil/gas, the variations of the remaining hydrocarbon amount in source rocks with increasing depth in the six basin in China are used to determine Kdepth . The deeper the burial depth (expressed in maturity degree of source rocks, Ro%) is, the smaller the recovery factor is.

Tight oil

China

China

China

Canadian

Canadian

17.5

18.2–18.5

14.7

10

EIA (2012)

Chen and Kirk (2013)

Zheng et al. (2017)

Zheng et al. (2017)

Li et al. (2012)

Yao (2003) Minimum value: 5.0 Average value: 15.0 Maximum value: 20.0

Tight gas

12

8–15

44–55

48–51.8

48.2–50.6

World

40

9.6

50–95

Sun (2012)

50–70

60

58.8

63.00

Recoverable factor (%)

World

World

10.3–48.3/ 24.2

Conventional gas

Type

35–70/50

America

31

Minimum/ MLR (2015a) 10.0 Average/ Satter et al. 33.0 (1992) Maximum/ Wang and Xu 70.0 (2012)

MLR (2010)

Average factor (%)

70–80

China

24.7

References

15–44.8/26.3

China

27.72

Conventional oil

Area name

Recoverable factor (%)

Type

America

Canada

World

China

China

World

China

China

World

China

China

Area name

Recoverable factor (%)

USGS (2009)

C&C (2015)

Liu et al. (2004)

Li et al. (2012)

Liu et al. (2004)

Liu et al. (2015)

Zheng et al. (2017)

(continued)

Minimum/ 15.0 Average/37.0 Maximum/ 55.0

Minimum/ MLR (2015a) 50.0 Average/65.0 Zhang et al. Maximum/ (2010) 95.0

MLR (2010)

References

Table 11.3 Current oil/gas recovery factors in the production of conventional and unconventional resources in China and in the world

386 11 Evaluation of the Global Oil and Gas Resources

America, Zhang et al. Canada/West (2014) Siberian Basin

Bohai Bay Basin

China

3–10

7–7.8

8.8

Zhang et al. (2010)

Li (2012)

HIS (2014)

World

5.0 (4.3–5.7)

References

Shale oil

Area name

Recoverable factor (%)

Type

Table 11.3 (continued)

Minimum value: 3.0 Average value: 7.5 Maximum value: 10.0

Average factor (%) Shale gas

Type

World

24.8 (22.3–28.3)

North America

35

North America

13.2

North America

World

21.8 (18–25)

17.4

America

10–20

China’s Yangtze platform

China

10–20

China

15–17.4

Area name

18.6

Recoverable factor (%)

Hammes et al. (2011)

Chalmers et al. (2012)

John (2002)

EIA (2012)

HIS (2014)

Wang et al. (2015a, b)

Wang et al. (2016)

Zou et al. 2012

MLR (2016)

References

Minimum/ 10.0 Average/20.0 Maximum/ 35.0

Recoverable factor (%)

11.3 Evaluation Methods of Oil and Gas Resources 387

388

11 Evaluation of the Global Oil and Gas Resources

Fig. 11.9 Recovery factor correction for shale and tight hydrocarbons in the six representative basins in China. a Distribution characteristics of shale hydrocarbons with depth and the current recovery factor correction. a1: vertical distribution of residual HC in source rocks and the current recoverable resource interval, Kdepth is the ratio of the depth interval (ΔR) corresponding to current recoverable layers to the whole distribution depth range (R). a2: TOC distribution of shale source rocks in current recoverable layers, Kenrich is distribution frequency of TOC in recoverable layers. a3: comprehensive recovery correction factor of shale oil and gas, Kfactor = Kdepth × Kenrich . b Tight hydrocarbons distribution and current recovery correction. b1: vertical distribution of tight HC and the current recoverable resource interval, Kdepth refer to the ratio of depth interval (ΔR) corresponding to current recoverable layers to the whole distribution depth range (R). b2: porosity distribution frequency (P) in current recoverable tight hydrocarbon layer, Kenrich is distribution frequency of Porosity in recoverable layers. b3: comprehensive correction factor for tight hydrocarbon recovery factor, Kfactor = Kdepth × Kenrich

The factor value is calculated with Eq. 11.14 and Fig. 11.9a1. For the enrichment condition correction factor (Kenrich ), the larger the TOC of the source rock layers is, the higher the hydrocarbon enrichment is, and the higher the recovery factor is. Its value is calculated with Eq. 11.15 and Fig. 11.9a2 using the TOC distribution data of the six basin in China. Figure 11.9a3 illustrates the comprehensive corrected factors (Ecalibrate ) and its distribution for shale oil and shale gas based on the data from the six basins and Eq. 11.13. In the same way, the depth correction factor (Kdepth ) for tight oil/gas is also calculated with Eq. 11.14 and Fig. 11.9b1, the latter illustrating the variations of expelled hydrocarbon amounts with depth from source rocks. The larger the porosity of the reservoir layers is, the higher the hydrocarbon enrichment is, and the higher the recovery factor is. The value of Kenrich is calculated by Eq. 11.15 and Fig. 11.9b2 showing data of porosity distribution. Figure 11.9b3 illustrates comprehensive corrected factors for tight oil resources and for tight gas resources and the distributions of the factors based on the data from the six basins and Eq. 11.13. The statistical analysis results of current recovery factors for conventional oil/gas resource, unconventional tight oil/gas resource and unconventional shale oil/ gas resources in China and in the world are summarized in Table 11.3, including their possible maximum values, possible minimum values, maximum possible values and the average values. The corrected values for conventional oil (Eco ) vary from 10 to 70% with an average of 33%, and for gas (Ecg ) vary from 50 to 95%, with an average

11.3 Evaluation Methods of Oil and Gas Resources

389

of 65%. The values for tight oil (Euo ) vary from 5.0 to 20.0% with an average of 15%, and for gas (Eug ) vary from 15.0 to 55.0% with an average of 37%. The values for shale oil (Eso ) vary from 3.0 to 10.0% with an average of 7.5%, and for gas (Esg ) vary from 10 to 35% with an average of 20%.

11.3.3 Characterization of Essential Parameters The five essential parameters (Qgenerated , K, R, M, E) and their ranges of variation are validated and revised by using the mass balance calculation, research results of six Chinese basins and published data on other basins in China and the world. The evaluation values of hydrocarbon resources are determined by statistical analysis of these data. Figure 11.10 illustrates the statistical analysis results of four essential parameters (K, R, M, R).

Fig. 11.10 The four essential parameters for the evaluation of hydrocarbon resources and their variation range based on collected data from six Chinese basins and others. a Initial hydrocarbon ratios (Ki); b hydrocarbon preservation efficiency (Ri); c movable hydrocarbon ratios (Mi); d current hydrocarbon recovery factors (Ei); i = C, T, S, corresponding to the three types of resources, e.g., conventional, tight and shale

390

11 Evaluation of the Global Oil and Gas Resources

11.4 Evaluation Results of the Global Oil and Gas Resources 11.4.1 Characterization of Hydrocarbon Resources The hydrocarbons resources results vary with their types, recovery levels, and are expressed in the form of probability distribution, including the possible minimum value with cumulative probability of 10% (P10), the maximum possible value with P50, the possible maximum value with P90. Table 11.4 lists the evaluated results of hydrocarbon resources in six representative basins, all basins in China and over the world (Figs. 11.11 and 11.12).

11.4.2 The Global Ultimate Hydrocarbons Resources and Their Components The ultimate amount of global hydrocarbon resources is 25.83 × 1012 t, it is about 18 times of the world proven hydrocarbon reserve to date. The ultimate amount in China is 1.2 × 1012 t, which accounts for 4.65% of the global resources, and is 8.73 times of China’s proven hydrocarbons reserves. The ultimate amount in the 6 representative Chinese basins is 7654.0 × 108 t, accounts for 64% of the total ultimate resource amount in China. Figure 11.13a–c illustrates the detail evaluation results of hydrocarbon resources for 6 representative basins, all basins in China and over the world respectively. Figure 11.13c shows the difference of the 3-types and 3-levels of resources for all basins in the world. In the global realistic hydrocarbon resource, the proportions of conventional, tight and shale are 44.04%, 32.57% and 23.39%, respectively, and the combined share of the two unconventional resources is 55.96%. Among the global expected resource, the proportions of conventional, tight and shale resources are 8.74%, 48.65% and 42.61%, respectively, and the two types of unconventional resources exceed 91.26%. At the ultimate level, the proportion of conventional resource is the lowest at 8.75%, the tight resource proportion is the largest with 48.70% and the shale resource proportion is in the middle with 42.55%. The sum of the two unconventional types exceeds 91.25%. The variations of proportions for 3 type resources among the realistic, expected and ultimate levels are of similar trend for both Chinese 6 representative basins and all the basins.

World

China

Six basins

East

Central

West

Comprehensive utilization (%)

Resources

Comprehensive utilization (%)

Resources

Comprehensive utilization (%)

42

9555

39

432

39

295

53

Songliao Basin

Summary of resources

61

34

Sichuan Basin

Bohai Bay Basin

46

18

Ordos Basin

83

Junggar Basin

50

11,310

50

557

50

382

64

118

27

60

29

85

100

22,620

100

1115

100

765

127

235

54

120

60

169

Qmin

5

3025

6

158

5

103

33

5

21

11

10

23

6

7110

6

369

6

239

71

11

52

27

22

55

P50

6

13,073

7

670

7

427

116

20

100

49

40

103

P90

50

29,226

50

1372

50

964

358

127

81

101

189

108

P10

Expected

50

62,878

50

2952

50

2035

754

268

172

214

397

230

P50

Qa

Qmax

P10

Realistic

Expected

Realistic

Prospective

Tight hydrocarbons resources (×108 t)

Conventional hydrocarbons resources (×108 t)

Tarim Basin

Area (location/name)

423

286

346

628

375

50

105,016

50

4839

50

3246

1187

P90

Table 11.4 Evaluation results of hydrocarbon resources in representative basins, and in all basins of China and over the world

100

58,242

100

2746

100

1932

716

254

162

203

379

218

P10

534

342

429

794

460

100

125,824

100

5896

100

4067

1508

P50

Prospective 751

(continued)

100

210,033

100

9662

100

6493

2376

845

571

691

1258

P90

11.4 Evaluation Results of the Global Oil and Gas Resources 391

World

China

Six basins

East

Central

West

5

Comprehensive utilization (%)

Comprehensive utilization (%)

Resources

Comprehensive utilization (%)

4

2667

5

128

89

24

Songliao Basin

Summary of resources

4

31

Sichuan Basin

Bohai Bay Basin

10

7

Ordos Basin

14

Junggar Basin

Resources

P90

Prospective

5

5113

5

239

5

166

57

8

45

18

14

23

5

8962

5

412

5

284

111

15

63

32

27

36

50

30,010

50

1414

50

958

271

77

125

145

120

221

50

55,074

50

2491

50

1699

595

162

146

236

242

317

50

91,520

50

4129

50

2785

1078

290

173

370

425

449

100

60,281

100

2837

100

1917

543

153

250

289

239

442

P10 636

324

292

471

484

100

109,924

100

4994

100

3392

1186

P50

P90 898

100

182,979

100

8276

100

5568

2154

582

345

740

848

8

21,778

9

1040

9

700

181

80

131

91

54

161

P50

548

344

510

669

632

50

129,262

50

6000

50

4116

1412

P50

Expected

100

258,368

100

12,005

100

8225

2821

1094

687

1020

1338

1265

P50

Prospective

Realistic

P50

Expected P10

P10

P90

Realistic

P50

The sum of three types of hydrocarbons resources (×108 t)

Shale hydrocarbons resources (×108 t)

Tarim Basin

Area (location/name)

Table 11.4 (continued)

392 11 Evaluation of the Global Oil and Gas Resources

11.4 Evaluation Results of the Global Oil and Gas Resources

393

Fig. 11.11 Evaluation of oil/gas resources in the world by using the Monte Carlo Simulation method. a The amount of total generated hydrocarbon of oil (left) and gas (right). b Realistic resources of shale oil/gas (2 graphs on the left) and tight oil/gas (2 graphs on the right). c Expected resources of shale oil/gas (2 graphs on the left) and tight oil/gas (2 graphs on the right). d Prospective resources of shale oil/gas (2 graphs on the left) and tight oil/gas (2 graphs on the right)

11.4.3 Distribution of Potential Hydrocarbon Resources The potential hydrocarbon resources refer to the residual or remaining hydrocarbon resources undiscovered in the earth, which could be discovered and extracted in future. The relations among the total resource, proven reserve and potential resource are expressed in Eqs. 11.16–11.19. ΔQ tatal = ΔQ conventional + ΔQ tight + ΔQ shale

(11.16)

ΔQ curr ent = Q realistic − Q pr oven

(11.17)

ΔQ succeed = Q expected − Q realistic

(11.18)

ΔQ prospect = Q ultimate − Q expected

(11.19)

where, ΔQtotal , ΔQconventional , ΔQtight and ΔQshale refer to the total, conventional, tight and shale undiscovered potential resources, respectively; ΔQcurrent , ΔQsucceed and ΔQprospective refer to three level potential resources, named as current, successive and prospective potential resources; other symbols have the same meaning as in Eqs. 11.1–11.5. The global potential resources can be obtained by subtracting the global proven hydrocarbon reserves from the global total resources. The global realistic hydrocarbon resource is 21,778 × 108 t, the proven reserve is 4796 × 108

394

11 Evaluation of the Global Oil and Gas Resources

Fig. 11.12 Evaluation of oil/gas resources by using the Monte Carlo Simulation method for the 6 representative basins (a), all petroliferous basins of China (b) and in the world (c). a1: evaluation results of oil/gas generation amounts for 6 representative petroliferous basins, a2: realistic oil/gas resources for tight oil/gas and shale oil/gas, a3: expected resources for tight oil/gas and shale oil/ gas, a4: prospective resource for tight oil/gas and shale oil/gas; b1: evaluation results of oil/gas generation amounts for all basins in China, b2: realistic resources for tight oil/gas and shale oil/gas, b3: expected resources for tight oil/gas and shale oil/gas, b4: prospective resource for tight oil/gas and shale oil/gas. c1: evaluation results of oil/gas generation amounts for all basins in the world, c2: realistic resources for tight oil/gas and shale oil/gas, c3: expected resources for tight oil/gas and shale oil/gas, c4: prospective resource for tight oil/gas and shale oil/gas

t, and the current potential resource is therefore 16,982 × 108 t. The corresponding values of them in China are 1040 × 108 t, 267 × 108 t, and 773 × 108 t, respectively (Fig. 11.14). Table 11.5 lists the statistical results of proven reserves of different types of hydrocarbons resources in China and over the world. Potential resources exist mainly in unconventional reservoirs. The potential resource proportion is much higher in unconventional resources than in conventional resources. The ratios of potential resources in the realistic resources change from type to type. The ratio in conventional resources is the lowest at 50–52%, the highest in the shale ones at 96–99%, and the intermediate in the tight at 88–98%. The ratios of potential resources in the expected and ultimate resources show the same variation

11.4 Evaluation Results of the Global Oil and Gas Resources

395

Fig. 11.13 Evaluation results hydrocarbons resources in China and over the world. a Results for the six basins in China (1—Junggar, 2—Sichuan, 3—Ordos, 4—Songliao, 5—Tarim, 6—Bohai Bay); b results of all basins in China; c results of all basins in the world

characteristics. Potential resources are mainly controlled by non-buoyance dynamic zones and fine-grained sedimentary facies as shown in a stratigraphic cross section in Fig. 11.15. It can be seen that the unconventional (tight and shale) resources in the Songliao basin account for more than 81.1% of the total potential resource. Potential resources occur mainly in reservoirs with deep burial depth. Figure 11.16 shows the distribution of proven and potential hydrocarbons resources in petroliferous basins in China and over the world. Figure 11.16a illustrates the distribution of the proven hydrocarbons reserves in six Chinese basins. The proven reserves decrease rapidly with increasing depth, more than 80% of proven reserves and less than 50% of the total generated hydrocarbons are distributed down to a depth of 4500 m, implying the potential resource in the shallow area is much smaller than in the area with depth > 4500 m. Figure 11.16b shows the vertical distribution of the proven 52,926 hydrocarbons reservoirs in the world’s 1,186 basins. More than

396

11 Evaluation of the Global Oil and Gas Resources

Fig. 11.14 Distributions of proven and undiscovered potential hydrocarbons resources in China and in the world, in terms of the 3-levels (a) and the 3-types (b). Yellow—proven reserves or resources, dark yellow—undiscovered or potential resources

80% of the proven hydrocarbons reserves and less than 50% of generated hydrocarbons amount are distributed in area with burial depth less than 4500 m, implying our efforts shall be directed to deeper reservoir layers below 4500 m with less than 20% of the proven reservoirs but more than 50% of the total generated hydrocarbons. Potential resources mainly exist in future. Global potential hydrocarbons resources exist mainly in successive and prospective resources, and can only be effectively exploited after scientific and technological progress be made in future. Figure 11.17 shows the variation of potential resources over time. The total recoverable shale hydrocarbons resources will increase from 0.51 × 1012 t to 5.51 × 1012 t if the recovery factor increases from the current values of 7.5% for oil and 20% for gas to the expected 50%, and it will be 10.99 × 1012 t if the recovery factor reach100% (Fig. 11.17a); The recoverable unconventional tight hydrocarbons resources will be 0.71 × 1012 t, 6.29 × 1012 t, and then 12.58 × 1012 t if the recovery factor stays at the current value of 15% for oil and 37% for gas, increases to the expected 50%, and then to 100% (Fig. 11.17b). For conventional hydrocarbons resources, the realistic resources are 0.96 × 1012 t at the current recovery factors of 33% for oil and 65% for gas, and the expected resources are 1.13 × 1012 t at a recovery factor of 50%, and the ultimate resources are 2.26 × 1012 t at a recovery factor of 100% (Fig. 11.17c). Finally, the world’s total realistic, expected and ultimate resources with 3-types are 2.18 × 1012 t, 12.93 × 1012 t and 25.84 × 1012 t (Fig. 11.17d).

198

476

Heavy oil/asphalt (available resources)

Oil shale (available resources)

(5.4–9)/7.5

Gas

(10–15)/12.5

1.2

(18–40)/38

Oil

3.7

Gas

(120–137.4)/137.4

Gas

Oil

(360–381.02)/381.02

(Zou et al. 2012)

(Zou et al. 2013)

(MLR 2016; Zou et al. 2012; Ma 2018)

(Zou et al. 2013 2015b; MLR 2016)

Referencing China’s shale gas proven reserves as a percentage of recoverable resources

(Li et al. 2012; Zou et al. 2015b; Song 2016)

(Zou et al. 2015b)

5000

1079

(49–256)/152.5

27.5

6.4

89.2

81.4

(1870–2998)/2062

(Wang et al. 2016; Hammes (2272–3336)/2530 et al. 2011; Wang 2015; Yao 2017; MLR 2017)

Resource reserve (×108 t) (minimum–maximum, mean)

Oil

World

Resource reserve (×108 t) (minimum–maximum)/mean References

China

Coalbed methane (available resources)

Shale oil and gas (reserve)

Tight oil and gas (reserve)

Conventional oil and gas (reserve)

Type

Table 11.5 Proven reserves of conventional and unconventional oil/gas resources in China and in the world

(continued)

(Zou et al. 2012; Wang et al. 2016; Knaus et al. 2010)

(Zou et al. 2013; Meyer and Attanasi 2003)

(Zou et al. 2012; Wang et al. 2015a, b; Song 2016; Dong et al. 2015)

(EIA 2012)

Referencing the world’s shale gas proven reserves as a proportion of recoverable resources

Referencing China’s tight oil and gas proven reserves as a percentage of recoverable resources

(BP 2016, 2018; Tong et al. 2014; Dong et al. 2015)

(MNR 2017; BP 2016, 2018; Tong et al. 2014, 2018; World Energy Resources 2016)

References

11.4 Evaluation Results of the Global Oil and Gas Resources 397

(50–70)/60

1375.32

Hydrate (available resources)

Total

(Zou et al. 2012)

(Zou et al. 2013)

14,645

(2099–3000)/2550

1067

Resource reserve (×108 t) (minimum–maximum, mean)

60

World

Resource reserve (×108 t) (minimum–maximum)/mean References

China

Oil sand (available resources)

Type

Table 11.5 (continued)

(Zou et al. 2012; Wang et al. 2016; Milkov et al. 2003)

(Zou et al. 2013; Wang et al. 2016)

References

398 11 Evaluation of the Global Oil and Gas Resources

11.4 Evaluation Results of the Global Oil and Gas Resources

399

Fig. 11.15 N–S cross section with lithology showing the distribution of three hydrocarbons dynamic zones in the Upper Cretaceous Qingshankou Formation, Qijiagulong Depression, Songliao basin, China, modified from Jia (2017). A—Bound hydrocarbon dynamic zone (B-HDZ) for shale oil/gas resources (blue); B—confined hydrocarbon dynamic zone (C-HDZ) for the tight oil/gas resources (light yellow); C—free hydrocarbon dynamic zone (F-HDZ) for conventional oil/gas resource (yellow)

Fig. 11.16 Vertical distribution of generated hydrocarbons amount, proved reserves/reservoirs and estimated potential resources in six representative basins in China (a) and 1186 petroliferous basins in the world (b)

400

11 Evaluation of the Global Oil and Gas Resources

Fig. 11.17 Distribution and variation of the global hydrocarbon resources of 3-types for conventional, tight and shale oil/gas and 3-levels for realistic, expected and ultimate oil/gas over time

11.5 Mass Balance of Hydrocarbons in Different Forms 11.5.1 Quantitative Characterization of Evaluated Results The generated hydrocarbon amount (Qgenerated ) is equal to the total of the lost (Qlost ), unmovable (Qunmovable ) and the resource (Qresource ), which is further divided into the produced (Qproduced ), proven and available resource (Qavailable ) and unproven or potential resource (Qpotential ). These five hydrocarbon amounts are related using Eqs. 11.20–11.25, Ri and Mi have the same meaning as in Eq. 11.1. Q generated = Q lost + Q unmovable + Q resource

(11.20)

Q lost = Q generated × (1 − Ri )

(11.21)

Q unmovable = Q generated · Ri · (1 − Mi )

(11.22)

Q resource = Q potential + Q proven

(11.23)

Q potential = Q undiscovered

(11.24)

Q proven = Q produced + Q available

(11.25)

Figure 11.18 illustrates the mass balance results of the global hydrocarbon resource evaluation during their formation and evolution. Figure 11.18a illustrate the

11.5 Mass Balance of Hydrocarbons in Different Forms

401

Fig. 11.18 Mass balance results of the global generated hydrocarbons amount, the 3-types resources and other forms of them in the evolution. a Total global generated hydrocarbons amount and its composition. b Total global ultimate resource and its composition. c Total global realistic resource and its composition

total global generated hydrocarbon amount and its composition: the total amount is about 142 × 1012 t and account for 100%, of which 74.3% have been lost, dispersed or destroyed, 7.7% is unmovable in reservoir layers, the current, successive and prospective resources account for 1.4%, 7.6% and 9.0%, respectively. Figure 11.18b illustrate the global total ultimate resource and its composition: the ultimate amount is 25.8 × 1012 t and account for 18.0% of total generated amount; 3-types resources of conventional, tight and shale account for 8.8%, 48.7% and 42.5% of the global ultimate resource, respectively; unconventional (tight + shale) resources are 10.36 times of the global conventional resource. Figure 11.18c illustrate the total global realistic resource and its composition: the total amount is 2.18 × 1012 t and account for only 1.4% of total generated amount; of which 9.1% are proven and produced, 12.9% are proven and available as current resource, and 78.0% are undiscovered or as potential resource, which is 3.5 times of the proven reserves.

11.5.2 Reliability of Evaluated Results Comparison of the results with previous results about global resources. The evaluation results in this study (Table 11.6) are compared with the comprehensive results (Table 11.6) obtained by the previous research and organizations. The comparison is listed in Table 11.6. The results of the extra-heavy oil and bitumen (EHOB) and liquefied natural gas (NGL) in Table 11.4 are incorporated into the entry of conventional oil in Table 11.5. The previous research results were based on reports from various institutions (IEA 2016, 2020). The basic data are from the IEA database, USGS, OGJ, BP, BGR, US DOE/EIA/ARI. The comprehensive results are

402

11 Evaluation of the Global Oil and Gas Resources

broadly representative in the industry, but only reflect the realistic resources under the current recovery factor conditions. On the contrary, this study investigates three types of oil/gas resources at three recovery levels, including the realistic resource with current recovery factor, expected resource with a recovery factor of 50%, and ultimate resource with recovery factor of 100%. The overall characteristics are as follows. Our estimated global realistic oil/gas resources (26,575 × 108 toe) are 29% higher than that in the previous comprehensive results (20,679 × 108 toe). Our realistic conventional oil / gas resources (9555 × 108 toe) is basically the same as that in the comprehensive results (10,650 × 108 toe), which is about 10% lower. However, our global realistic unconventional oil/gas (tight + shale) resource amount (12,223 × 108 toe) is 121% higher than that in the previous comprehensive result (5527 × 108 toe). There are five main reasons for the above differences. First, the starting point of our research is based on the previous assessment results of global conventional oil/gas resources. On this basis, the realistic global conventional oil/gas resources should be similar with the previous comprehensive results. Table 11.6 Comparison of our evaluation results with previous ones Remain conventional (×108 t)

Remain unconventional (×108 t)

Comprehensive results (×108 t)

Oil/gas

Tight HCs

Shale HCs

Subtotal HCs

Remaining

Proven

Total

OECD

2514

424.2

2356.1

2780.3

5294.3

566.5

5860.8

Americas

2087.1

251.9

1984.3

2236.2

4323.3

463.3

4786.6

Europe

288.7

Area

61.8

155.5

217.3

506

57.7

563.7

Asia Oceania 138.2

101.8

226.4

328.2

466.4

45.5

511.9

Non-OECD

8135.7

958.8

1797.8

2756.6

10,892.3

3925.4

14,817.7

Europe/ Eurasia

2576.5

230.1

377.3

607.4

3183.9

933.7

4117.6

Asia

592.8

206.4

535.5

741.9

1334.7

222.8

1557.5

Middle East

2550.2

129.6

80.9

210.5

2760.7

1895.5

4656.2

Africa

1062.5

173.7

390

563.7

1626.2

347.4

1973.6

Latin America

1356.4

227.8

404.1

631.9

1988.3

524.7

2513

Previous results

10,649.6

1383

4143.8

5526.8

16,186.6

4491.9

20,678.5

Our evaluation results

9555

7110

5113

13,323

21,778

4797

26,575

Ratio of ours/ previous

0.90

5.14

1.23

2.21

1.35

1.07

1.285

11.5 Mass Balance of Hydrocarbons in Different Forms

403

The most probable reason why our results are lower (10%) is that this study incorporates the extra heavy oil, asphalt and liquefied natural gas into the realistic conventional oil/gas resources, while they are all categorized as unconventional resources in the previous results. Second, the previous results in Table 11.6 were obtained in 2013 or 2014, while our evaluation results are based on the current recovery factor conditions of 2019. Considering the rapid development of unconventional oil and gas resources in the past five years in the United States, China and the world, it is fully understandable that our evaluation results are higher than the previous comprehensive results. In the resource evaluation report of 2014 (EIA 2012), EIA explicitly states that the United States is rich in tight oil and gas resources, with the recoverable amount ranging from 30 billion barrels to 120 billion barrels, but finally chose 80 billion barrels. EIA’s latest data (EIA 2018) also show that USA daily production of natural gas from shale and tight oil and gas (650 × 108 ft3 , accounting for 70% of USA total dry gas production) and crude oil production (7 million barrels per day, accounting for 60% of USA total oil production) in 2018 is 4–5 times higher than 10 years ago. In 2015, EIA’s evaluation results of unconventional oil and gas resources in the USA increased by 60% compared with that in 2014, so it is reasonable that our global resource evaluation results in 2019 will have a significant increase compared with that in 2014. In addition, China’s unconventional oil and gas exploration has been developing rapidly in recent years, with the proved reserves of shale gas increasing by 1.3 × 1012 m3 from 2015 to 2019, which is about 3 times of the reserve increase in the previous 15 years (MLR 2015a; MNR 2019; MLR 2015b; MNR 2019). Third, the previous comprehensive results in Table 11.6 only deal with the resources of some countries and regions in the world, so they do not represent the global resources. In 2014, EIA only evaluated the recoverable resources of unconventional tight oil and shale oil in 42 countries (IEA 2016; Flowers 2019), because these countries have organized unconventional oil and gas explorations or carried out similar geological surveys or studies. Although their reports cover the major petroleum basins in the world, they are not representative of the world, and therefore the numbers in the comprehensive results are smaller than the actual global total unconventional oil and gas resources. Fourth, this study evaluates the global oil and gas resources based on the principle of Mass balance, which includes both the oil and gas resources of the currently recognized and discovered resource types and also the currently unrecognized but potentially discoverable resource types in future, including the unconventional oil and gas resources such as heavy oil, tar sands, natural gas hydrates, etc. Therefore, our evaluated global oil and gas resources are larger than the previous comprehensive results. Fifth, there are conceptual differences between the previous comprehensive results in Table 11.6 and the current evaluation. The current estimate of shale oil and gas resources is 5113 × 108 toe, which is close to the previous comprehensive results of 4144 × 108 toe, with a difference of less than 20%. However, the current result of tight oil and gas (7110 × 108 toe) is 4–5 times larger than the comprehensive result of predecessors (1383 × 108 toe). The most likely reason for this phenomenon is

404

11 Evaluation of the Global Oil and Gas Resources

that the production of shale oil/gas in oil field companies actually includes a lot of tight oil/gas in reservoir layers within the source rocks or around these source rocks. Governmental subsidies in some countries for shale oil/gas production incentivized oil companies to count tight oil/gas as shale oil/gas. However, our study strictly distinguishes shale oil/gas from tight oil/gas by the definition, and their evaluation results are not mixed. Considering the above five factors, we believe that the global realistic oil/gas resource quantity evaluated in this paper is objective and reflects the current human cognition of oil and gas. Therefore, it is credible to infer the global total oil and gas resources from the correlations between the realistic and potential resources and between conventional and unconventional resources. Application conditions of the results. The evaluation of global oil and gas amount in different forms in this paper is carried out under certain conditions, so the following problems should be paid attention to when applying these results. Firstly, the global total generated hydrocarbon amount in this paper only represents a minimum value as there are three other categories of hydrocarbons not included in our results, e.g., the hydrocarbons generated by the non-effective source rocks with TOC < 0.5% and Ro < 0.5%, the hydrocarbons formed by the dry bitumen during a continuous deep burial, and the hydrocarbons formed by the possible abiogenic production existing in subsurface. Oil shale was also excluded from our estimated results (Metz 1974). Secondly, the estimated resources in this paper have been compared with the results published by USGS, IEA and others (Table 11.6). The numbers in our results are much larger than other organizations because they include 3-levels of resources as the realistic, successive and prospective, whereas the previous published results only include the realistic resources. Our realistic resource amount and ultimate resource amount are 1.29 times and 12.73 times of the numbers reported by USGS and other agencies respectively, indicating a much broader prospect of future exploration. Our conventional realistic resource amount is inline with the previous reports, but unconventional realistic resource is larger for three reasons: (1) the previous results were obtained before 2014, and do not reflect the current level of understanding; (2) the previous results covered only major countries and regions, not the globe; and (3) the previous results included only the hydrocarbons resources we have understood. Thirdly, the hydrocarbons resources are likely to sustain much longer time than we thought. The annual hydrocarbon production in China was 3.2 × 108 t in 2017, and the number for the world in the same year was 84 × 108 t (BP 2017), respectively. If oil and gas production stays as the current recovery factor, it will take 242 years for China and 202 years for the world to deplete the hydrocarbon resources. If the recovery factor is at the level of 50%, the time will be 1792 years for China and 1482 years for the world. The time would be 3688 years for China and 3019 years for the world if we can boost the recovery factor close to 100%. At present, the hydrocarbons resources are mostly used as fuels or producing electricity, with commitments to reduce carbon dioxide emissions and the gradual formation of a low-carbon economic life from many countries, we will use hydrocarbons more for other purposes such

11.6 Summary

405

as producing chemical raw materials, then the value of hydrocarbons will be further enhanced in such circumstances and the sustainable times will be longer in the future. Fourthly, the potential hydrocarbons resources are seemly to be more than enough for our generation and the generations after us, however they are unrenewable resources. The biggest challenge we face today is how to develop new technologies to exploit and utilize these resources safely, harmlessly, efficiently, rather than worrying about their shortage or creating international tensions for short-term political or commercial interests. What took the earth a billion years to form could be burned as fuel within 3000 years by human, just a short moment in the geological history. It is our responsibility to cherish the hydrocarbon resources and wisely use them to protect our living environment and accelerate the development of renewable energy source to save more of the hydrocarbons for future use as more precious and meaningful resources.

11.6 Summary The global hydrocarbon amounts in the earth system are very important not only to human economic prosperity, but also to our living environment. Geologists, geochemists and environmental scientists have been constantly exploring new methods to understand how much hydrocarbons have been generated and how they are existing on the earth. As these issues involve a very wide range of subjects such as the correlation and distribution between conventional and unconventional oil and gas reservoirs and resources, they have not been solved so far. Although the BP, USGS and IEA release annually the global hydrocarbon resource assessment results since the beginning of the new century, they only involve the recoverable resources under the current technological conditions. This paper investigated the generation, migration and accumulation of conventional and unconventional oil and gas resources in six representative petroliferous basins in China, discovered three hydrocarbon dynamic boundaries and three dynamic fields, established a unified genetic model to clarify the mechanism of how these boundaries and fields jointly control the formation and distribution of different reservoirs and resources. Application results of the genetic model to the world show that the global generated hydrocarbon amount is about 142 × 1012 t, 74.3% lost or destroyed, 7.7% accumulated but unmovable in reservoir layers, and only 18% accumulated and preserved as resources. The global 3 level resources of the current, successive and prospective could sustain human society for another 200, 1500 and 3000 years, respectively, if they are produced in annual production of 2019. Instead of worrying about resource exhaustion, humanity should focus its efforts on developing advanced technologies that can safely and greenery extract those resources.

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11 Evaluation of the Global Oil and Gas Resources

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Chapter 12

Evaluation of the Global Potential Resource of the Natural Gas Hydrate

New Understanding: (1) Natural gas hydrate (NGH) and conventional oil and gas reservoirs have many similarities in terms of creation, migration, and accumulation. While NGH is only distributed in the Gas Hydrate Stable Zone (GHSZ), a region of high pressure and low temperature, it is nevertheless a part of the larger global petroleum system. The form, quality and quantity of existing conventional petroleum resources are taken as a benchmark when estimating the economic worth of NGH. Using mass balance equations and Monte Carlo simulation methods, the in situ and technically recoverable resources of the global NGH are estimated to be 84.36 × 1012 m3 and 25.55 × 1012 m3 , or about 12.6% and 5.4% of the total global conventional natural gas resources, respectively. (2) The results from the mass balance approach and Monte Carlo simulation technology are more trustworthy and robust than the estimates of 22.09 × 1012 m3 from the volumetric approach and of 41.46 × 1012 m3 from statistical trend analysis of 29 prior estimates, with an uncertainty range that has converged to a level that is comparable to conventional oil/gas resource assessment. The method for evaluating gas hydrate reservoir resources put out in this paper offers a fresh approach for doing so in different petroliferous basins and provinces. (3) In terms of commercial production, environmental concerns, and geological disasters, natural gas hydrate faces a number of difficulties. Additionally, according to the equivalent annual consumption of natural gas in 2017, the recoverable resources of global gas hydrate technology only make up 1.87% of the total recoverable gas resources of conventional reservoir technology. This means that they can only support the world’s oil and gas demand for 3.4 years. The NGH resources could not take over as the primary source of energy in the future due to its underutilized and unsustainable resource, geohazard and environmental concerns associated with resource development, and lack of a competitive advantage over quickly expanding new and renewable resources.

© Science Press 2023 X. Pang, Quantitative Evaluation of the Whole Petroleum System, https://doi.org/10.1007/978-981-99-0325-2_12

413

414

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

12.1 Introduction and Issue The natural gas hydrate (NGH) was viewed as a solution to a future energy shortage because Trofimuk et al. (1973) estimated the global in-situ NGH resource is 3.02– 3.09 × 1018 m3 (gas equivalent) and that it could be used for 400,000 years at current levels of yearly consumption if fully exploited (Wood and Jung 2008; Arthur 2011; Wadham et al. 2012; Senger et al. 2016). Many attempted to verify the resource potential, while others studied the feasibility of technical recovery. Interest in research on NGH increased markedly over the past two decades (Fig. 12.1). NGH has been the subject of research projects in the United States (Booth et al. 1996), Japan (Konno et al. 2017), Canada (Dallimore et al. 2005), India (Sain and Gupta 2012), Korea (Ning et al. 2012) and China (Yang et al. 2015) since 1996. A number of offshore production tests were conducted after the Millik-5L-38 well production test of permafrost gas hydrate in northern Canada in 2002 in an effort to develop new production methods for the resource. In 2017, China completed a 60-day production test in Shenhu Area of South China Sea. NGH has been recognized as a novel source of energy in the country ever since. (Ministry of Natural Resources of the People’s Republic of China 2017). In 2020, a second round of test in Shenhu Area for 30 days, produced a total of 861.4 × 103 m3 from a horizontal well (Xinhua Net 2020). Can global gas hydrates eventually take the place of oil and gas as the world’s primary energy source? The matter is still being researched. There have been at least 29 previous assessments of the worldwide NGH resource that have been done (Table 12.1). First of all, there is a lack of agreement regarding the nature, method of occurrence, and precise definition of the resource, as evidenced by the fact that resource estimates can vary by up to five orders of magnitude. Second, as knowledge advances, methodologies are better, and evaluation data accumulates over time,

Fig. 12.1 The worldwide amount of NGH publications. The data of Chinese publications is from China National Knowledge Infrastructure (CNKI), the searching key word is Natural Gas Hydrate and Methane Hydrate. Science Direct provided the information for English articles, and the search terms used were “natural gas hydrate” and “methane hydrate”

12.1 Introduction and Issue

415

resource estimations eventually decline. This echoes a resource estimate declining curve with increasing exploration drilling in Shenghu Area of the South China Sea, evidencing the learning history of hydrate resource exploration. The lessons learned and statistics from, for example the Shenhu hydrate exploration expedition, help better understand the NGH resource formation and distribution. Thirdly, most estimates are in-place gas without distinguishing resources from natural occurrence of low concentration hydrate (Boswell and Collett 2011). Although Boswell and Collett (2006) introduced technically recoverable resource (TRR) in their Alaska assessment, but the global TRR estimates are elusive and largely based on speculation if any (Chong et al. 2016). Although different scholars use different research methods and techniques to realize the global NGH resource evaluation, at least four essential factors need to be considered by them, the current research progresses have created conditions for determining these four key parameters, but there are still major problems with them. The first is the stratigraphic areas conducive to the formation and distribution of NGH, the genesis mechanism of NGH (Sloan 2003; Falenty et al. 2014) and the main controlling factors (Wood et al. 2002; Phrampus and Hornbach 2012) confine the formation and distribution of NGH in the Gas Hydrate Stable Zone (GHSZ) which has high pressure and low temperature in the marine (Solov’Ev 2012), the poles (Collett et al. 2011; Huang et al. 2017) and the plateau ice sheet (HIS 2020), laying a theoretical foundation for NGH resource prediction (Dickens et al. 1997). The second is the in-place gas content of NGH recoverable resource and its ratio to total gas amount available for the formation of NGH resource in GHSZ. Highly enriched NGH are primarily found in sandstone and conglomerate reservoirs with high porosity and high permeability, similar to the distribution of conventional oil and gas resources in the reservoir layers (Table 12.2; Katsube et al. 2005; Wang et al. 2010; Gong et al. 2013). It is feasible to calculate the amount of in-place NGH gas by statistically assessing drilling findings of several geological parameters and their variation for in the known reservoirs, such as the effective reservoir thickness, area, porosity, permeability, NGH saturation, and others (Ministry of Land and Resources of China 2009; Osadetz and Chen 2010). The third is the gas source of NGH in GHSZ and its total amount available for the formation of potential NGH resource. A scientific foundation for the estimation of the initial gas amount available for NGH reservoirs was provided by test results of the carbon isotopes of natural gas in NGH (Wood et al. 2002), which demonstrated that they were derived from the degradation of organic matter in sedimentary formations similarly to conventional gas resource (Fig. 12.2, Table 12.3). However, most previous studies consider all the gas amount generated by all organic matter in GHSZ as available gas for the formation of NGH resource, and does not consider whether the natural gas is dispersed in mudstone or in high-porosity and permeable reservoirs, and whether it is formed by biodegradation of organic matter within GHSZ or formed by pyrolysis of organic matter in area below the GHSZ (Boswell and Collett 2011; Chong et al. 2016; Table 12.1), this is not consistent with the actual observation facts that only the gas generated and expelled from the source

Author

Trofimuk et al.

Trofimuk et al.

Tsarev and Cherskiy

Trofimuk et al.

Nesterov et al.

McIver

Trofimuk et al.

Kvenvolden

No.

1

2

3

4

5

6

7

8

1988

1983

1981

1977

1979

1977

1975

1973

Time

V

V

V

V

V

V

V

V

Evaluation method

Chemical Geology

Proceedings of the Fifth II ASA Conference on Energy Resources

Long-Term Energy Resources

Long-Term Energy Resources

Priroda 1

Geologiyai Geofizika

Doklady Akademii Nauk SSSR 225

Doklady Akademii Nauk SSSR

Data resources (magazine)

10

–

51.25

–

280.5

360.2

360.2

335.71

Area (106 km2 )

500

400

–

300

85

300

300

Thickness (m)

Table 12.1 The evaluation results of NGH by different scholars in previous periods

Trofimuk et al. (1973)

3014

1120

1553 118 1530

3.06

14.8

39.5

3.053 × 1018

1.135 × 1018

1.573 × 1018 1.2 × 1017 1.550 × 1018

3.1 × 1015

1.5 × 1016

4 × 1016

(continued)

Kvenvolden (1988)

Trofimuk et al. (1983)

McIver (1981)

Nesterov et al. (1977)

Trofimuk et al. (1979)

Tsarev and Cherskiy (1977)

Trofimuk et al. (1975)

References

The estimation of Ratio of GIP for GIP for NGH NGH to (m3 ) conventional resource

416 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Gornitz and Fung

Harvey and Huang

Holbrook et al.

Dickens et al.

Makogon

Kvenvolden

Dickens

Soloviev

Milkov et al. 2003

10

11

12

13

14

15

16

17

18

2002

2001

1999

1997

1997

1996

1995

1994

1990

MacDonald

9

Time

Author

No.

Table 12.1 (continued)

V

V

V

C

V

V

V

V

V

V

Evaluation method

17.5

–

–

10.5

10.5

59.6

36.3–54.7

62.4

Area (106 km2 )

Geology

7

Russian Geology 35.7 and Geophysics

Organic Geochemistry

Proceedings of the National Academy of Sciences

Penn Well

Nature

Science

Journal of Geophysical Research

Global Biogeochemical Cycles

Annual Review of Energy

Data resources (magazine)

300

2.8

400

–

–

400

400

277

379–453.4

500

Thickness (m)

MacDonald (1990)

19.7 26

0.5

6.7 14.8 14.8 20.7

3.95 0.21 3.95

2 × 1016 2.64 × 1016

4.8 × 1014

6.8 × 1015 1.5 × 1016 1.5 × 1016 2.1 × 1016

4 × 1015 2.1 × 1014 4 × 1015

(continued)

Milkov et al. (2003)

Soloviev (2002)

Dickens (2001)

Kvenvolden (1999)

Makogon (1997)

Dickens et al. (1997)

Holbrook et al. (1996)

Harvey and Huang (1995)

Gornitz and Fung (1994)

References

The estimation of Ratio of GIP for GIP for NGH NGH to (m3 ) conventional resource

12.1 Introduction and Issue 417

Author

Milkov

Buffett and Archer

Klauda and Sandler

Ge et al.

Archer et al.

Burwicz et al.

Boswell and Collett

Wallmann et al.

No.

19

20

21

22

23

24

25

26

2012

2011

2011

2009

2005

2005

2004

2004

Time

Table 12.1 (continued)

D

C

D

D

V

V

D

V

Evaluation method

Energies

Energy & Environmental Science

Geochimica Et Cosmochimica Acta

Proceedings of the National Academy of Sciences

Marine Geology and Quaternary Geology

Energy & Fuels

Earth and Planetary Science Letters

Earth-Science Reviews

Data resources (magazine)

147

–

–

13.1

–

13.1

4.5

Area (106 km2 )

300

300

300

300

Thickness (m)

Milkov (2004)

2.47 5.62

114 0.39

3.37

0.49

0.44

0.99

2.5 × 1015 5.7 × 1015

1.154 × 1017 3.97 × 1014

3.4 × 1015

0.5 × 1015

4.5 × 1014

1 × 1015

(continued)

Wallmann et al. (2012)

Boswell and Collett (2011)

Burwicz et al. (2011)

Archer et al. (2009)

Ge et al. (2005)

Klauda and Sandler (200 5)

Buffett and Archer (2004)

References

The estimation of Ratio of GIP for GIP for NGH NGH to (m3 ) conventional resource

418 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Piñero et al.

Cong et al.

Kretschmer et al.

27

28

29

2015

2014

2013

Time

D

C

D

Evaluation method

26

Area (106 km2 )

Global Biogeochemical Cycles

–

Advances in New – and Renewable Energy

Biogeosciences

Data resources (magazine)

300

Thickness (m)

Piñero et al. (2013)

1.04 4.94

3.46

1.05 × 1015 5 × 1015

3.5 × 1015

Kretschmer et al. (2015)

Cong et al. (2014)

References

The estimation of Ratio of GIP for GIP for NGH NGH to (m3 ) conventional resource

Note As for the evaluation method, V—volumetric method; C—comprehensive analysis; deposition rate of particle organic carbon. In the statistics of the distribution area for NGH, the values exceeding the mode values of the total sedimentary basin area (180 × 106 km2 ) are excluded. There are 15 groups of qualified hydrate formation area (×106 km2 ) in the table, with the minimum value of 4.5, maximum value of 147 and average value of 34.9. There are 19 groups of data about the thickness of favorable strata for hydrate accumulation in the world, the smallest is 2.8 m, the most is about 500 m, and the average is about 324 m

Author

No.

Table 12.1 (continued)

12.1 Introduction and Issue 419

420

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Table 12.2 The gas saturation of NGH and other basic characteristics in different lithology reservoirs Location

Lithology

NGH gas saturation

Field testing result

References

Alaska North Slope

Sand-dominated reservoir

60–90%

–

(Burwicz et al. 2011)

Nankai Through Thin sand

> 60%

20,000 m3 /D

(Miyakawa et al. 2014; Wu and Wang 2018)

Shenhu Area

Thin sand, clayey sand and silty clay

13.7–45.2%

5000 m3 /D

(Dai et al. 2017; Wu and Wang 2018)

Dongsha Area

Silty clay and bioclastic limestone

10–33%

–

(Wu and Wang 2018)

2.78–22.81%

–

(Lu et al. 2010)

Qilian Mountain Argillaceous siltstone (with fractures) and siltstone

rock with larger TOC and gas saturated can migrate and accumulate dominantlydriven by buoyance in reservoir layers with high porosity and permeability to form potential NGH resources, and that more than 95% of NGH are scattered in mudstones with lower TOC and NGH saturation < 5% in porosity, which is not significant for commercial exploitation (Boswell and Collett 2011; Chong et al. 2016); In addition, the gas in one third of 13 well studied NGH reservoirs in the world has been proven to be originated from pyrolysis of organic matter in area below the GHSZ (Fig. 12.2, Table 12.3), reflecting that the natural gas generated and expelled from deep source rocks in petroliferous basins can migrate upward along carrier strata or faults with high-porosity permeability dominantly-driven by buoyancy and form the potential NGH resource within GHSZ (Collett and Ginsburg 1998; Hornbach et al. 2004; Osadetz and Chen 2010), it is the first challenge we are facing that how to consider the contribution of all possible truly effective source rocks in a sedimentary basin to the formation of NGH resource. The fourth is the recovery factor for evaluating the global NGH recoverable resource, Japan (Konno et al. 2017), Canada (Katsube et al. 2005) and China (Zhang et al. 2018) have conducted NGH production tests, proving the feasibility of exploiting such resources, but their recovery factors have not yet been obtained. In fact, there has not been a NGH reservoirs developed commercially in the world, recovery factors used in literature are set by researchers themselves or by indirect methods as numerical simulations (Jang and Santamarina 2011; Konno et al. 2014), it should be after 2050 academically to obtain meaningful recovery factors for evaluating recoverable NGH resource when at least one NGH reservoirs has been commercially exploited, it is the second problem we are facing that how to determine the NGH recovery factors in the modern level of technology. In order to solve these two problems, the analogical methods and reasoning techniques are proposed to realize the global NGH recoverable resource without directly

12.1 Introduction and Issue

421

Fig. 12.2 a Carbon isotope characteristics of marsh gas and biodegradable gas during organic matter evolution and its correlation with temperature, indicating that the generation temperature of marsh gas is mainly 20–35 °C, corresponding δ13 C1 ≤ −80‰, while that of biogenetic gas is 35–65 °C, corresponding δ13 C1 ≥ −80‰, data from (Whiticar et al. 1986). b The classification of gas based on carbon isotope of methane; data is listed in Table 12.3

using these two essential factors. This paper studies the correlation and difference between NGH and conventional oil and gas resources, takes the NGH reservoirs with saturation > 20% in porosity as a special kind of commercial conventional gas reservoirs trapped in area with high pressure and low temperature, considering the contribution of all possible gas source within and below GHSZ to its formation, establish a unified model and mass balanced equations among different conventional resources to evaluate the global recoverable NGH resource by utilizing the geological data and

–

Oregon coastal hydration roof

Vancouver Island nearshore Barkley canyon

Coastal – Sino-US trench in Costa Rica

South Korea East, Yuling Basin

1

2

3

4

Pliocene–Quaternary

Miocene–Oligocene

Strata

No. Area

–

120 to − 259 (194)

-

16–101 (72)

0.0454 0.135 0.1015

99.95 99.87 99.9 0.034

0.0269

99.97

79.91

0.0213

14.9

99.98

17.3

0.161

99.14

84.3

0.002

99.48

81.9

–

100

13.8

–

100

85.1

0.002

99.61

29.7

0.002

99.76

68.1

0.002

99.54

–

–

–

–

–

–

–

–

–

–

0.699

0.012

–

–

0.387

0.238

0.458

− 64.1 − 63.6

− 42.9

− 138

− 189

− 42.6

− 139

− 63.7

− 43.4

− 143

− 197

− 42.7

− 140

− 195

− 63.2

− 198

− 64.7

− 69.4

− 200

− 206

− 68.3

− 208

− 66.0

− 70

− 202

− 67.7

− 67.8

− 205

− 204

− 67.5

− 188

− 189

− 69.1

− 203

References

(Pohlman et al. 2005)

(continued)

CO2 reduction (Kim et al. 2011) biogenic gas

CO2 reduction (Lückge et al. 2002) biogenic gas

Mixed gas

CO2 reduction (Milkov et al. 2005) biogenic gas

Depth Natural gas component (%) Isotope Genetic type below Methane Heavy Non-hydrocarbon δ13 D1 (VSMOW)/ δ13 C1 (VPDB)/ sea floor hydrocarbon gas ‰ ‰ (m) gas min–max (mean)

Table 12.3 The composition, hydrogen and carbon isotope characteristics of discovered hydrate natural gas in the world

422 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

–

Kitami in Sakhalin Island nearshore

Norwegian Pliocene–Pleistocene sea Nyegga

The Gulf of Mexico

5

6

7

0.005 0.0024 0.0022 0.0032 0.0145 0.0053

98.5 99.6 98.7 99.7 100 99.4

27.5 19.5 28.145 22.2 24.576

80.2 71.66 77.4 75.22

0.29

71.7

99.71

0.0024

100

–

0.0032

100

0.329

0.112

97.8

99.67

0.0022

98.2

–

–

–

0.4

–

–

–

–

–

0.6

0.3

1.3

0.4

1.5

–

–

2.2

1.8

− 65.6 − 65 − 65.1 − 65.1 − 65.7 − 63.6 − 64.1 − 63.8 − 64.2 − 64.1 − 70.8 − 69.9 − 42.2 − 43.5 − 46.5 − 49.9 − 45.1

− 199 − 200 − 198 − 202 − 197 − 199 − 202 − 203 − 202 − 203 − 202 − 198 − 190 − 177 − 160 − 156 − 166

References

Mixed gas

Pyrolysis gas

(continued)

(Klapp et al. 2010)

(Charlou et al. 2004)

(Vaular et al. 2010)

CO2 reduction (Svensen et al. 2005) biogenic gas

CO2 reduction (Hachikubo et al. 2010) biogenic gas

Depth Natural gas component (%) Isotope Genetic type below Methane Heavy Non-hydrocarbon δ13 D1 (VSMOW)/ δ13 C1 (VPDB)/ sea floor hydrocarbon gas ‰ ‰ (m) gas min–max (mean)

Upper – Pleistocene–Holocene

Strata

No. Area

Table 12.3 (continued)

12.1 Introduction and Issue 423

Pleistocene

Black Ridge in South Carolina coast

Baikal Basin

Marmara Sea

Mackenzie Upper Basin Oligocene–Miocene

8

9

10

11

–

–

Miocene- Holocene

Strata

No. Area

Table 12.3 (continued)

85.22 96.74 96.24 95.7

–

–

–

–

898–915 (908)*

99.62

66.1

99.98

–

99.97

–

0.02

29.72

4.243

3.728

3.246

14.78

0.02

0.03

0.024

98.38

–

0.019

0.0729

0.0772

99.98

99.73

–

330–331 (331)

99.62

–

4.995

94.81 0.018

21.679

77.22 99.98

11.39

88.31

259

1

99

0.36

4

0.007

–

–

–

–

–

1.6

–

0.2

0.3

–

–

–

–

–

− 51.6 − 49.4 − 49.3 − 50.1 − 67.4 − 66.6 − 70.7 − 66.5 − 65.8 − 66.6 − 66.5 − 57.4 − 57.6 − 57 − 58.3 − 44.1 − 41.2

− 173 − 183 − 148 − 171 − 205 − 175 − 193 − 206 − 196 − 304 − 302 − 303 − 303 − 304 − 305 − 219 − 220

(MacDonald 1990)

(Sassen et al. 2011)

References

Pyrolysis gas

Acetate fermentation biogenetic gas

(continued)

(Uchida 1999)

(Bourry et al. 2009)

(Kida et al. 2006)

CO2 reduction (Matsumoto et al. 2000) biogenic gas

CO2 reduction (Lorenson and biogenic gas Collett 2000)

Depth Natural gas component (%) Isotope Genetic type below Methane Heavy Non-hydrocarbon δ13 D1 (VSMOW)/ δ13 C1 (VPDB)/ sea floor hydrocarbon gas ‰ ‰ (m) gas min–max (mean)

424 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Strata

Jurassic Jiangcang formation

No. Area

Tundra of Qilian Mountains

Pearl River Upper Mouth Miocene–Pliocene Basin

12

13

Table 12.3 (continued)

34.27 3.64

62.52 86.95

99.82

33.43

59.02

99.49

34.04

62.98

–

32.69

62.45

–

41.39

34.85

–

0.51

0.035

29.2

52.2

99.96

25.87

0.0 3

99.87 24.82

0.022

99.89

46.06

0.04

99.82

69.79

0.04

99.82

–

267–395 (347)*

0.13

99.66

–

–

–

8.75

0.71

1.87

0.11

2.72

3.83

16.03

27.63

3.51

0.1

0.09

0.14

0.14

0.21

− 48.7 − 39.6 − 39.6 − 42.8 − 40.8 − 50.5 − 39.5 − 48.1 − 49 − 49.3 − 48.7 − 48.8 − 48.4 − 52.6 − 71.2 − 31.1 − 56.7

− 231 − 230 − 230 − 214 − 242 − 262 − 266 − 245 − 227 − 285 − 266 − 279 − 271 − 255 − 226 − 194 − 199

Mixed gas

Pyrolysis gas

CO2 reduction biogenic gas

Mixed gas

Pyrolysis gas

Pyrolysis gas

Mixed gas

Depth Natural gas component (%) Isotope Genetic type below Methane Heavy Non-hydrocarbon δ13 D1 (VSMOW)/ δ13 C1 (VPDB)/ sea floor hydrocarbon gas ‰ ‰ (m) gas min–max (mean)

(continued)

(Wu et al. 2011)

(Liu et al. 2017)

(Tan et al. 2017)

(Huang et al. 2011)

(Lu et al. 2010)

(Lorenson et al. 2003)

References

12.1 Introduction and Issue 425

Strata

98.69 99.97 97

–

–

–

–

0.028

1.31 –

–

– Mixed gas

− 70.9 − 54.1

− 180

CO2 reduction (Liu et al. 2015) biogenic gas

− 61.8

− 203

References

− 220

Depth Natural gas component (%) Isotope Genetic type below Methane Heavy Non-hydrocarbon δ13 D1 (VSMOW)/ δ13 C1 (VPDB)/ sea floor hydrocarbon gas ‰ ‰ (m) gas min–max (mean)

Note * represent land exploratory wells, whose sample depth are calculated from the earth surface; – represent no data

No. Area

Table 12.3 (continued)

426 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

427

knowledge accumulated over 200 years in the exploration and exploitation of conventional oil and gas resources in 1186 basins worldwide, to make the result uncertainty narrowed down to the level of conventional oil and gas resource evaluation results, which can be applied to make investment decisions. For clarity, in this study, we refer potential NGH resource as methane hydrate concentrations in the form, quality and quantity that there are reasonable prospects for eventual economic extraction in foreseeable future, a definition similar to other types of mineral resources (USGS 1980). From our current understanding, those resources are associated with coarse grained sediments with high porosity of > 12%, permeability of > 1 md and hydrate saturation of > 20% (Holland et al. 2019, Table 12.2). In lack of commercial production example from the NGH, we use the form, quality and quantity from known conventional petroleum resource as a reference to infer the economic significance of gas hydrate accumulation, and constrain our global hydrate resource estimate. Here we report the scientific basis, present the estimates, and demonstrate show exploration and assessment histories from Shenhu and Mallik gas hydrate study sites helped constrain our global NGH resource estimates. This study employs three different methods to evaluate the global NGH resources. We introduce a mass-balanced total global petroleum system approach. The results are compared with those from reservoir volumetric approaches using analogs of best-studied hydrate sites in Shenhu and Mallik hydrate fields, and statistical trend analysis of 29 previously estimates of global NGH resources in literatures.

12.2 Evaluation of the NGH Resource by Mass-Balanced Method 12.2.1 Geological Model for NGH Formation and Distribution We first define a total global petroleum system that encompasses all active source rocks and all generically related petroleum accumulations, including NGH (Fig. 12.3). The following three facts form the basis for our inference of global NGH by the mass-balanced approach. (1) Methane in NGH is of organic origin. At least 13 NGH accumulations have been extensively studied around the world (Table 12.3, Fig. 12.2). Methane carbon isotope data from samples in these 13 NGH accumulations show that all δ13 C1 values are < −30‰, indicative of organic origin (Dai et al. 2017). Among them, 55% is of biogenic origin with δ13 C1 ≤ −55‰, and 20% is thermogenic with δ13 C1 varying between − 55 and − 30‰; and the other 25% having δ13 C1 ranging from − 80 to − 30‰ shows signatures of mixed biogenic and thermogenic origins. NGH shares the same source rocks with conventional petroleum accumulations. NGH resource accounts for only a fraction of the total oil and gas of the petroleum system in the

428

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Fig. 12.3 Total global petroleum system showing the occurrence of NGH resource and its relation to conventional, tight and shale oil and gas accumulations (a), and the distributions of generated petroleum resources from source rocks as a function burial depth (b). Data form petroliferous basins in China and over the world (USGS 1980) were used to determine essential parameters above the BHAD as additional constraints in global NGH resource appraisal. C—conventional oil/gas accumulations controlled by buoyancy (C1 —NGH, (C11 —thermogenic origin, C12 — biogenetic, C13 —mix-origin), C2 —conventional oil and gas accumulation (C21 —fault trap, C22 — anticlinal trap), and C3 —biodegraded heavy oil/asphalt reservoirs. U—unconventional tight oil/ gas accumulation where buoyancy is nonessential. S—shale oil/gas accumulation where buoyancy is nonessential. QEC —expelled from source rock for conventional reservoirs (QECa —thermogenetic, QECb —biogenetic). QEU —for tight oil/gas reservoirs. QRS —for shale oil/gas reservoirs. BHAD—hydrocarbon buoyancy-driven depth limit

free hydrocarbon dynamic field (F-HDF, Pang et al. 2012) above the hydrocarbon buoyancy-driven depth limit (BHAD, Pang et al. 2021a, b). (2) Enrichment process of NGH is similar to conventional oil/gas accumulation. NGH deposits share many common characteristics with conventional oil/gas accumulations, such as being sourced by thermogenic or/and biogenic methane, requiring porous media for storage, taking an anticlinal shape with an impeding cap enhancing accumulation among others, and often co-occurring with conventional gas fields (Hornbach et al. 2004). The Messoyakha gas hydrate field in the West Siberian Basin (Collett and Ginsburg 1998) and the Mallik hydrate field in the Beaufort-Mackenzie Basin (BMB) in Canada (Dallimore et al. 2005) are good examples. Osadetz and Chen (2010) showed that 75% of the wells studied with natural occurrence of hydrate are associated with significant oil and gas discoveries in BMB. To form a NGH deposit, there needs to be an intersection of sufficient natural gas flux, available storage space and a series of petroleum enrichment conditions functioning in GHSZ. This genetic relationship makes NGH a part of the total global petroleum system and enables the inference of NGH resource using petroleum system concepts and information from conventional oil and gas exploration. (3) NGH is in crystal water molecule and forms under phase equilibrium conditions. Although gas hydrate is part of the total global petroleum system, it appears to

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

429

be in different forms of crystal structure (Loveday et al. 2001; Lu et al. 2007; Falenty et al. 2014). These unstable structure forms make NGH occur only in GHSZ under special environments with high pressure and low temperature (Sloan 2003) which limits its spatial occurrence to the uppermost part of sedimentary column vertically, and to the deep permafrost region and deep-water setting geographically (Fig. 12.3a). In permafrost region, the depth of the NGH ranges from 250 to 1100 m (Dallimore et al. 2005; Chong et al. 2016), such as down to sediment depths of about 300 m in West Antarctica and 700 m in East Antarctica (Wadham et al. 2012). In marine setting, the reported maximum depth is less than 1200 m below seafloor (Chong et al. 2016), even possibly appearing at water depths as shallow as about 200 m and at a depth of 500 m below the sea floor in the Barkley canyon region, and it was influenced by the random upward flow of warmer fluids (Wood et al. 2002), such as the Gulf Stream (Phrampus and Hornbach 2012). In contrast, the conventional natural gas and oil occurs in sedimentary column of depth range from 300 to 7000 m with an average around 2600 m in basins (Fig. 12.4). For example, the bottom simulating reflector (BSR) in the Pearl River Mouth Basin in the South China Sea (Fig. 12.5) was found at a depth up to 500 m below seafloor with water depth between 500 and 1500 m. BSR represents an acoustic reflection interface between the gas hydrate-containing overlaying sediments and the gas hydrate-free underlying sediments. Comparatively, the maximum burial depth of the known conventional oil/gas reservoirs in this basin is around 3400 m (Fig. 12.6). Studies estimated the global area for NGH (Dickens et al. 1997) including under marine area (Solov’Ev 2012), permafrost area (Collett et al. 2011; Huang et al. 2017), plateau basins and alpine basins (Konno et al. 2014), Tables 12.1, 12.4, 12.5, the values vary from 5.0 × 106 to 150.0 × 106 km2 with an average of 50 × 106 km2 .In contrast, the area of all kinds of petroleum accumulations of all known sedimentary basins ranges from 162 to 240 × 106 km2 , with an average value of 180 × 106 km2 . In contrast to the hydrocarbon amounts available for unconventional tight and shale oil and gas resources, which account for about 90% of the total generated hydrocarbon amounts, the hydrocarbon amounts available for conventional resources including NGH in six representative petroliferous basins of China are only 10% of the total amounts generated (Figs. 12.3b and 12.7). Permafrost area on the Qinghai-Tibet Plateau accounts for about 42.4% of the total area (Zou et al. 2017). The area of sedimentary basins above the Qinghai-Tibet Plateau account for about 50% of the total area. The favorable area for hydrate accumulation is about 20% of the Qinghai-Tibet Plateau; Based on this ratio, the favorable area for NGH accumulation in Alpine area is estimated to be 71.38 × 104 km2 .

Fig. 12.4 Vertical distribution of hydrocarbon reservoirs discovered in the world. a Distribution patterns of 52,926 reservoirs in global 1186 petroliferous basins. The number of discovered reservoirs versus their burial depth in all different basins; b the number of discovered reservoirs versus their burial depth in basins with Low-gradient (≤ 2.5 °C/100 m); c The number of discovered reservoirs versus their burial depth in basins with Relative low-gradient (2.5–3.0 °C/100 m); d the number of discovered reservoirs versus their burial depth in basins with relative high-gradient (3.0–3.5 °C/100 m), e the number of discovered reservoirs versus their burial depth in basins with High-gradient (≥ 3.5 °C/100 m), all the data from Pang et al. (2001). Buoyance-driven Hydrocarbon Accumulation Depth is the lower boundary of conventional oil and gas accumulation, their depth varies from 1500 to 8000 m with average value of 3500 m

430 12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

431

Fig. 12.5 The geological characteristics and distribution pattern of BSR in Pearl River Mouth Basin in the South China Sea. a The location of Liwan exploration area 2 miles from Shenhu area in the Pearl River Mouth Basin, South China Sea. b The geological features of BSR (Bottom Simulating Reflector) and seismic section of No. 3 Structural Belt in Liwan area. c The wave impedance inversion results of the south-north seismic section of No. 3 Structural Belt in Liwan area, showing the close relationship between the distribution of NGH and BSR on the bottom, i.e. the NGH is distributed between the seabed and BSR, and the thickness of sediments ranges from 0 to 500 m, with an average value of 300 m. d The predicted favorable development area of NGH in No. 3 Structural Belt based on the seismic interpretation

Fig. 12.6 The distribution features and maximum burial depth of conventional hydrocarbon reservoirs in the Pearl River Mouth Basin, South China Sea. a The depth distribution range and the basic development features of conventional hydrocarbon reservoirs in the Pearl River Mouth Basin in the South China Sea. b The relationship between the porosity and depth in HZ25 region, indicating the porosity and depth of LBBA are 10 ± 2% and 3400–3500 m, respectively

12.2.2 Mass-Balanced Model and Equations for NGH Resource Evaluation From mass balance principles, petroleum accumulations in conventional and unconventional reservoirs account for a part of the oil and gas generated in the total global petroleum system (Fig. 12.3). Let QC , QU , and QS be the petroleum resource in conventional reservoirs (including hydrate), in tight reservoir, and in shale reservoir, respectively, and QP denote the total oil and gas generated from source rocks in the total global petroleum system (Fig. 12.3a). We have Eq. 12.1:

432

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Table 12.4 Alpine area and the area favorable for NGH formation in the Northern Hemisphere Locality

Total area (×1000, km2 /mile2 )

Area for NGH formation (× 104 km2 )

Qinghai-Tibet Plateau

1300/500

26.00

Khangai-Altai Mountains

1000/390

20.00

Brooks Range

263/102

5.26

Siberian Mountains

255/98

5.10

Greenland

251/97

5.02

Ural Mountains

125/48

2.50

Andes

100/39

2.00

Rocky Mountains

100/39

2.00

Fennoscandian Mountain

75/29

1.50

Remaining

< 100/39

2.00

SUM

3569/1381

71.38

Table 12.5 Essential parameters for natural gas hydrate potential resource calculation from literatures Parameters

Distribution range

Mode values

Instruction

References

Area AHGSZ (×106 km2 )

5.0–150

50

This result is obtained by statistical analysis of previous relevant parameters, but the data points where the distribution area of hydrate exceeds the area of sedimentary basin are removed, which includes areas of favorable permafrost, marine and alpine plateaus

(Trofimuk et al. 1973; Tsarev and Cherskiy 1977; Trofimuk et al. 1979; McIver 1981; Kvenvolden 1988; MacDonald 1990; Gornitz and Fung 1994; Harvey and Huang 1995; Dickens et al. 1997; Dickens 2001; Soloviev 2002; Milkov et al. 2003; Milkov 2004; Buffett and Archer 2004; Archer et al. 2009; Burwicz et al. 2011; Wallmann et al. 2012; Piñero et al. 2013) (continued)

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

433

Table 12.5 (continued) Parameters

Distribution range

Mode values

Instruction

References

Depth H HGSZ (m)

10–1200

500

Taking into account the parameter values in the evaluation of NGH resources of 29 group results around the world; Taking into account the geophysical exploration results of different hydrate research sites around the world; Taking into account the simulation results of global hydrate distribution depth

(MacDonald 1990; Uchida 1999; Lorenson and Collett 2000; Matsumoto et al. 2000; Lorenson et al. 2003; Charlou et al. 2004; Milkov et al. 2005; Pohlman et al. 2005; Svensen et al. 2005; Kida et al. 2006; Bourry et al. 2009; Hachikubo et al. 2010; Klapp et al. 2010; Lu et al. 2010; Vaular et al. 2010; Huang et al. 2011; Kim et al. 2011; Sassen et al. 2011; Wu et al. 2011; Liu et al. 2015; Liu et al. 2017; Tan et al. 2017)

Gas ratio of hydrocarbon fluids (%)

37.9–90.7

71.5

The minimum value (Pang et al. 2001; HIS (37.9%) is expressed by 2010; Dai et al. 2017) the proportion of the world’s discovered conventional gas reserves (including biogas reserve) in oil and gas reserves (including biogas reserve, conventional hydrocarbons, heavy oil bitumen); the maximum value (90.7%) is expressed in the natural gas ratio in the generated hydrocarbon amount by type III organic parent material at the biochemical stage. The maximum possible value (71.5%) is the weighted average value of the gas generation ratio at the biochemical stage and the pyrolysis stage of the three types of parent materials, and the weight of the two is expressed by the ratio of the number of gas hydrate deposits formed by their gas generation

434

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Fig. 12.7 The hydrocarbon amount of generated, expelled and remained for major source rocks of six petroliferous basins in China. a Songliao Basin with Qingshankou and Nenjing Formation shale as the main source rocks. b Bohai Bay Basin with the Shahejie and Dongying Formation shale as the main source rocks. c Ordos Basin with the Carboniferous, Permian, Triassic shale as the main source rocks. d Sichuan Basin with the Cambrian limestone and Silurian, Permian, Triassic, Jurassic mud shale as the main source rocks. e Junggar Basin with the Permian and Jurassic shale as the main source rocks. f Tarim Basin with the Cambrian and Ordovician limestone and Triassic and Jurassic shale as the main source rocks. The six petroliferous basins are the most representative significant in China with the largest distribution area, the highest exploration degree, the largest resource potential, and the largest proven hydrocarbon reserves. Among the six representative basins, the original hydrocarbon amounts for conventional, tight, and shale resources account for about 8.7–11.8% (average 10.3%), 35.0–54.3% (average 44.7%), and 34.7–54.1% (average 44.4%), respectively. QET —hydrocarbon amount expelled from source above LBBA, available for conventional trap reservoir formation. QEU —hydrocarbon amount expelled from source rocks below LBBA, available for unconventional tight reservoir formation. QRS —hydrocarbon amount remaining in source rock, available for shale oil/gas reservoir formation

QC + QU + Q S ≤ Q P

(12.1)

Let QC1 denote the NGH resource in Gas Hydrate Stable Zone (GHSZ), and QC2 the conventional oil and gas resources in traditional accumulations, and QC3 the biodegraded heavy oil and bitumen resources. The sum of the three is petroleum resources in conventional reservoirs, which is less than the oil and gas expelled from the source rocks (QEC ) above BHAD (Fig. 12.3b): Q C = Q C1 + Q C2 + Q C3 ≤ Q EC

(12.2)

Equation 12.2 provides an upper bound for NGH resource estimation, a fraction of the petroleum resource available above the BHAD. We can express the NGH resource as a function of petroleum resource in conventional reservoir in Eq. 12.3:

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

Q C1 = Q C − Q C2 − Q C3 = f × Q C

435

(12.3)

where, f (in fraction) is the percentage of gas hydrate resource in total petroleum resource in conventional reservoirs above the BHAD. By substituting Eq. 12.2 into Eq. 12.3, we have the global NGH resource expressed as a function of the two other types of petroleum resources in conventional reservoirs, showed in Eq. 12.4. Q C1 =

f 1− f

(Q C2 + Q C3 )

(12.4)

The parameter f can be approximated by a ratio of the sedimentary rock volume in GHSZ (VG H S Z = A G H S Z HG H S Z ) to the total rock volume (Vconv = Aconv Hconv ) hosting petroleum fluids in conventional petroleum reservoir, weighted by gas availability and conversion factors from subsurface to surface in Eq. 12.5: f =g

Bgh VG H S Z Bg Vconv

=g

Bgh A G H S Z HG H S Z Bg Aconv Hconv

(12.5)

where, A G H S Z and HG H S Z are distributions of global areal extent (km2 ) and column height (m) of GHSZ, respectively; Aconv and Hconv are distributions of areal extent (km2 ) and column height (m) of petroliferous basins hosting conventional petroleum accumulations respectively; Bgh , gas hydrate volume factor (a ratio of methane hydrate volume at standard surface condition to the gas volume at reservoir condition); Bg natural gas volume factor (a ratio of natural gas volumes at the standard surface condition to reservoir condition). All the 7 parameters in Eq. 12.5 affect the size of f and global hydrate resources evaluation results, determined by statistical analysis of parameters obtained by predecessors (Tables 12.6 and 12.7). AGHSZ , HG H S Z and g is list in Tables 12.4 and 12.5. g (fraction) is the percentage of gas by mass in petroleum fluids expelled from source rocks and available for conventional reservoirs above the BHAD, it is difficult to make sure of its real value because of the different lost for oil and gas in their migration and accumulation. Its possible maximum value (gmax ) is expressed in the gas ratio in generated hydrocarbon amount by the source rock with type III organic parent material at the biochemical stage (Ro < 0.5%), 90.7% as showed in Fig. 12.8c1, its possible minimum value (gmin ) is expressed in the ratio of natural gas reserve in the world’s total proven oil and gas reserves in conventional reservoirs, 37.9% as showed in Fig. 12.8c3, its maximum possible value (gmode ) is expressed in a weighted average value of the gas ratios in generated hydrocarbon amounts at the biochemical and pyrolysis stages by source rocks with three type of parent materials (I, II, III) above the BHAD, the weights of biogas and pyrolytic gas are expressed in terms of their reservoir number ratios (2/ 3, 1/3) in the 13 NGH deposits proved globally, 71.5% as showed in Fig. 12.8c2.

436

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Table 12.6 Global conventional oil and gas resource estimates (input parameters in Eq. 12.4). In conversion, oil density = 0.82 tone/m3 and 1 m3 oil = 1000 m3 natural gas equivalent were used Resource type

Recoverable

In-place

Recoverable factor used

References

Original oil resource (109 m3 )

595.0

1983.3

0.3

(Zou et al. 2015)

Original gas resource (1012 m3 )

470.5

672.1

0.7

(Zou et al. 2015)

Original bitumen resource (109 m3 )

296.5

1438.0

0.2

(Meyer et al. 2007)

Total HC resource 1012 m3 gas eq.

1362.0

4093.5

0.2–0.7

(Meyer et al. 2007; Zou et al. 2015)

Table 12.7 Physical parameters for assessing global NGH resources by mass-balanced approach (required for calculation of parameter f in Eq. 12.5) in this study Parameters

Minimum

Mode

Maximum

Geological meaning

References

A G H S Z (106 km2 )

5.0

50.0

150

Areal extend of GHSZ

(Table 12.1, Fig. 12.8, Burwicz et al., 2011)

HG H S Z (m)

10

500

1200

Column height of GHSZ

(Table 12.1, Fig. 12.8, Zhang et al. 2008)

Aconv (106 km2 )

162

180

240

Areal extent of sedimentary basins

(Table 12.1; Fig. 12.8; Meyer et al. 2007; Zou et al. 2015)

Hconv (m)

300

2600

7000

Column height of conventional oil/gas

(Table 12.1; Fig. 12.8; Meyer et al. 2007; Zou et al. 2015)

Bgh

160

164

168

Gas hydrate (Boswell and Collett volume factor 2011)

Bg

35

210

360

Natural gas PVT calculation volume factor

G

0.379

0.715

0.907

Gas fraction (Figs. 12.4 and 12.7; above BHAD Wood and Jung 2008; Wadham et al. 2012)

R

0.15

0.3

0.7

Hydrate recovery factor

(Jang and Santamarina 2011; Konno et al. 2014)

12.2 Evaluation of the NGH Resource by Mass-Balanced Method

437

Fig. 12.8 Statistical results of three coefficients for global natural gas hydrate resource evaluation. a The global distribution area of natural gas hydrate in previous evaluation (1973–2017), data from reference list in the supplementary table 1; b Range of burial depth of discovered natural gas hydrate in previous exploration; c ratio distribution of natural gas amount ratio to total hydrocarbons amount (G) in Free Hydrocarbon Dynamic Field (F-HDF) above BHAD, including gmax of 90.7% from (C1), the proportion of gas amount in total hydrocarbon amount generated from source rocks during biogenetic stage (Ro < 0.5%), data from Pang et al. (2001), including gmin of 37.9% from (C3), the proportions of proven gas reserve in total proven oil & gas reserves above the BHAD in Chinese and global basins, data from BP (2008), including gmod of 71.5% from (C2), the gas amount ratio in petroleum fluids generated and provided by source rocks during biogenetic stage (Ro < 0.5%) and thermal genetic stage (Ro = 0.5–1.1%) above BHAD, data from Pang et al. (2001) and HIS (2010). BHAD refers to the Buoyance-driven Hydrocarbon Accumulation Depth

12.2.3 Simulation Results and Variation Scope of NGH Resource The total oil and gas resources in conventional reservoirs above the BHAD in the total global petroleum system are presented in Table 12.6, forming the reference for inferring global NGH resource. Table 12.7 compares the physical parameters of

438

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

petroleum accumulation in conventional reservoirs above BHAD and NGH in GHSZ for determining f in Eq. 12.5. Recovery factor is poorly constrained because of lack of commercial extraction examples. A moderate, but a wide range of recovery factor distribution from 10 to 70% with a mode at 30%, based on numerical simulations (Jang and Santamarina 2011; Konno et al. 2014), is used for TRR of NGH resource in this study. Regarding each of the unknown parameters as a variable, Monte Carlo simulation was used to generate equal probable scenarios for global NGH resource estimates, resulting in resource distributions of the GIP and TRR (Fig. 12.9). The global GIP estimates varies from 58 × 1012 m3 at 90th fractile (F90) to 338 × 1012 m3 at 10th fractile (F10) with a mode value of 84.36 × 1012 m3 , and the global TRR estimates have a range from 18 × 1012 m3 (P90) to 108 × 1012 m3 (F10) with a mode value of 25.55 × 1012 m3 (Fig. 12.9). Comparing with natural gas resources in conventional reservoirs, the global NGH resources is about 5.43% in recoverable, and 12.55% of in-place. The GIP and TRR estimates of NGH are 2.06% and 1.87% respectively, of the total conventional petroleum resources (Table 12.6).

Fig. 12.9 Histograms and cumulative probabilistic distributions of estimated global NGH resources of GIP (a and b) and TRR (c and d) from Mass Balance Approach and Monte Carlo simulation

12.3 Evaluation of the NGH Resource by Drilling Analogy Method

439

12.3 Evaluation of the NGH Resource by Drilling Analogy Method 12.3.1 Principle for Drilling Analogy Method For comparison with the proposed mass-balanced approach, we also use reservoir volumetric equations to calculate NGH resources. For a known NGH reservoir, the calculations of its GIP are related to six parameters, including hydrate distribution area (A), average thickness (H), porosity (Ø), saturation of NGH (S), gas volume conversion coefficient (Bgh ) and hydrate resource conversion coefficient (KR ), the concentrated resource of NGH is identified by criteria of H > 2 m, S > 10%, Ø > 15%, the relation of 6 parameters is expressed in Eq. 12.6. Four essential parameters of them were get through detailed analysis of NGH reservoir features in the study area, including (1) the plane NGH-display area ratio coefficient (KS ), theoretically, similar with the ratio of the distribution range of the effective source rocks in whole basin, but expressed in the area ratio with BSR-displaying characteristics in research area; (2) plane NGH-bearing area ratio coefficient (KA ), expressed in the area ratio of proved NGH in research area; (3) vertical NGH-bearing thickness ratio coefficient (Kh ), expressed in the thickness ratio of proved NGH in research area; (4) commercial NGH resource ratio coefficient (KR ), expressed in the ratio of concentrated hydrate amount to total NGH amount. The global NGH resource of GIP is expressed in Eq. 12.7 and simulated by using Monde Carlo Simulation. As there are no truly commercial gas hydrate reservoirs in the world, and production tests for reservoirs are very limited, so it is difficult to obtain these parameters and their range required for resource evaluation in the volumetric approach. In this paper, the volumetric approach employs the risk concept from conventional petroleum resource assessment, which considers all essential elements of forming gas hydrate accumulation in the total global petroleum system. The global area of GHSZ (AGHSZ ), a measurable parameter, is converted to global reservoir area by multiplying the probability of intersection of all elements that necessitate for forming gas hydrate accumulation, expressed in Eq. 12.8. After obtaining the global GIP of NGH, the recoverable resource quantity is calculated by multiplying the recovery factor according to Eq. 12.9. GIP = K R × A × H × ∅ × S × Bgh

(12.6)

G I P = K R × (K A · A B S R ) × (K h · HG H S Z ) × ∅ × S × Bgh

(12.6a)

GIP = K R × (K R · K S · A G H S Z ) × (K h · HG H S Z ) × ∅ × S × Bgh

(12.6b)

GIP = P × A G H S Z × HG H S Z × ∅ × S × Bgh

(12.7)

P = K R × K S × K A × Kh

(12.7a)

440

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

GIP = VRock × ∅ × S × Bgh

(12.8)

VRock = P × A G H S Z × Δz

(12.8a)

P = Pr ob PS R ∩ PR SV ∩ PM GT ∩ PE N R

(12.8b)

TRR = G I P × R

(12.9)

where in Eq. 12.8, the VRock is the sedimentary rock volume that hosts potential NGH resource, Δz (m) is the net NGH reservoir thickness, A G H S Z (km2 ) is the global GHSZ distribution area, Ø (%) is reservoir porosity, S (%) is gas hydrate saturation, and R is the recoverable factor. P is the probability of intersection of all essential elements of forming concentrated gas hydrate accumulations in GHSZ, which is the product of the distribution probabilities of adequate source (PS R ), presence of porous and permeable reservoir (PR SV ), gas migration ranges from source rock to reservoir (PM GT ) and presence of enrichment mechanism for high concentration hydrate (PE N R ). The geological meaning of these four probability parameters of PS R , PR SV , PM GT , PE N R is similar to the physical meaning of the four geological parameters of K S , K A , K h , K R in Eq. 12.7a to some extent, respectively. The probability values of PSR , PRSV , PMGT and PENR are determined based on our understanding of each pre-required condition and observations from hydrate study sites around the world. The reservoir volumetric parameters were determined from statistics of well-studied gas hydrate research and production test sites, mostly from marine site of Shenhu Area in South China Sea (Fig. 12.10) and permafrost region of the Beaufort-Mackenzie Basin in Canada (Holland et al. 2019).

12.3.2 Two Case Studies in the World The history of gas hydrate resource evaluation in the Shenhu area is an epitome of the global gas hydrate assessment. The Shenhu area in the Pearl River Mouth Basin of South China Sea covers about 3000 km2 (Fig. 12.10a). Early NGH resource assessment in 1999 would be based on BSR anomalies from seismic survey, resulting in an overly optimistic in-place gas resource of 29 × 1012 m3 . During 1999–2007, five exploration wells were drilled and newly acquired data lead to much reduction of in-place resource to 199 × 109 m3 . In the next following 10 years, 14 wells were drilled and 60-day full scale production test was conducted in 2017. The updated in-place resource was further reduced to one third of the previous assessment, with a mode of 66 × 109 m3 . The resource estimate shrunk almost three orders of magnitude compared to the first assessment. A close examination of the NGH resource assessment history in the region (Table 12.8) demonstrates that the area, thickness and hydrate saturation are the three parameters that have decreased the greatest. In

12.3 Evaluation of the NGH Resource by Drilling Analogy Method

441

Fig. 12.10 The essential geological parameters and drilling result of Shenhu Exploration Area, Pearl River Mouth Basin, South China Sea. a Location of the Shenhu area and prediction results of favorable area for hydrate development. The Shenhu area (3000 km2 in red frame) predicted by seismic data; BSR area in Shenhu (727.7 km2 in yellow frame, a1) determined after drilling 5 wells; obvious BSR (350 km2 in green color, a2) determined after drilling 19 wells, and the favorable area for production (22 km2 ). b The effective thickness of NGH reservoir in 2015, data from Yang et al. 2017. c The saturation of NGH, data from reference Yang et al. 2017. d NGH porosity of W2 well in Shenhu area in 2007, data from Lu et al. (2008) and Wang et al. (2010)

the early time, BSR was regarded as a good indicator for gas hydrate occurrence. The Shanhu exploration drilling results suggest that the significant gas hydrate accumulations account for only about 1/10 of the area indicated by BSR anomalies. The reservoir thickness based on the column height of GHSZ was proven wrong, and only 3 in 19 wells contain high concentration of gas hydrate (saturation > 30%) that are commonly associated with turbidities deposited in deep-water canyons in this region

442

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

(Fig. 12.10). The overly optimism without distinguishing significant accumulation from the dispersed occurrence is typical in early NGH resource assessment. Mallik is one of the best-studied methane hydrate accumulations worldwide in a permafrost environment. Gas hydrate studies in Mallik site were carried out in the 1980s and continued to 2010s (Dallimore et al. 2005; Council of Canadian Academies 2008; Osadetz and Chen 2010). The Mallik gas hydrate accumulation occurs below thick permafrost and overlays directly on a free gas field sourced by thermal genetic gas from the deep part of the basin. A basin wide study in the Beaufort-Mackenzie Basin (BMB) based on petrophysical logs from 251 petroleum exploration wells showed that although gas hydrate occurs in 122 wells (about 50%), only 7 wells contain net reservoir thickness greater than 5 m, accounting for < 3% of the total wells studied (Katsube et al. 2005; Osadetz and Chen 2010). The statistics from the Shenhu area, BMB and other well-studied hydrate sites elsewhere, coupled with governing principles of deposition of source and reservoir rocks in sedimentary basins, were used to evaluate the chances of presence of essential elements for NGH accumulations and constrain the range of volumetric parameters in our global NGH resource calculation. The reservoir parameters and probability values for the global NGH resource assessment are summarized in Table 12.9. The reservoir volumetric method through Monte Carlo simulation yielded a distribution of global GIP and TRR of NGH resource. Figure 12.11 depict the statistical distributions of the estimated global GIP and TRR in gas hydrate graphically, demonstrating the uncertainties of the assessment. The GIP vary from 45 × 1012 m3 (F90) to 367 × 1012 m3 (F10), with a mode of 64.51 × 1012 m3 (Fig. 12.11a and b), and the TRR from 14 × 1012 m3 (F90) to 119 × 1012 m3 (F10), with a mode of 22.09 × 1012 m3 (Fig. 12.11c and d). Table 12.8 Showing volumetric parameters used and resulting NGH resource estimates in different exploration periods in Shenhu gas hydrate area Period

Condition

Area (km2 )

Thickness (m)

Porosity (%)

Saturation (%)

Gas volume factor

Gas in-place (×109 m3 )

Before 1999 Seismic only

3000

300

20

100

160

29,000

1999–2007

5 wells

425

25

45

25

164

199

2007–2017

19 wells

22–600

1–77.3

15–60

5–50

160

66

300

14.18

35

28

The hydrate resource estimates ware plotted in Fig. 12.13 as a comparison with the global trend of NGH resource estimates. Resource estimates data in Shenhu area are from Wang et al. (2010) and Gong et al. (2013)

12.4 Evaluation of the NGH Resource by Trend Analysis Method

443

Table 12.9 Volumetric parameters and risk factors used for the global NGH resource assessment using the volumetric approach in this study Physical parameters

Symbol Min

Mode Max References

AGHSZ

5

50

150

(Zhang et al. 2008; Burwicz et al. 2011)

Net reservoir thickness (m)

Δz

2

15

80

(Dallimore et al. 2005; Wang et al. 2010)

Porosity (%)

Ø

15

35

50

(Katsube et al. 2005; Zhang et al. 2018)

Hydrate saturation (%)

S

10

35

90

(Katsube et al. 2005; Zhang et al. 2018)

Hydrate volume factor

BGH

160

164

168

(Katsube et al. 2005; Zhang et al. 2018)

Recovery factor (%)

R

10

30

70

(Boswell and Collett 2011; Jang and Santamarina 2011; Konno et al. 2014)

Probability of source rock

PS R

0.15 0.35

0.65

(HIS 2020), and Pearl River Mouth Basin

Probability of reservoir

PRSV

0.05 0.20

0.35

(Chong et al. 2016), and BMB and Shenhu statistics

Probability of migration

PM GT

0.05 0.50

0.75

(Chong et al. 2016), and BMB and Shenhu statistics

Probability of enrichment

PE N R

0.1

0.35

(Chong et al. 2016), and BMB and Shenhu statistics

GHSZ area extent

(106

km2 )

0.25

12.4 Evaluation of the NGH Resource by Trend Analysis Method 12.4.1 Principle by Trend Analysis Approach Taking previous global GIP estimates since 1973 as a time series, a statistical trend analysis was performed to project the ultimate resources at present time and future time. The 29 global NGH estimates (Table 12.1) were fitted to an empirical model as a function of time (Year). Before 1980, the global GIP estimate was in the order of 8 × 1018 m3 , the resource estimates decreased gradually to around 7.0 × 1014 m3 in 2010s’, about four orders of magnitude less, which is comparable to the general decline trend of resource estimates in Shenhu Area of the South China Sea (Table 12.8). The drastic drop in gas hydrate estimate is due to improved understanding of the nature of NGH occurrence and better constrained volumetric parameters, such as area of occurrence, net reservoir thickness, and hydrate saturation. In the latest gas hydrate resource assessment of North Slope of Alaska (Burwicz et al. 2011), USGS used a field size distribution and number of gas hydrate fields, a method used for conventional discrete petroleum accumulation, in recognition of the modes

444

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

Fig. 12.11 Results of statistical distributions (histograms, a, c; cumulative, b, d) of GIP and TRR for global NGH resources by reservoir volumetric approach using analogues from well-studied gas hydrate accumulations in the world: Shenhu area of China in marine and Mallik area of Canada in permafrost

of hydrate resource enrichment in nature. Similar to shale gas resource, resource is often located in “sweet-spots” of highly enriched accumulation.

12.4.2 Results of Resource Estimates Based on the statistical trend analysis model, the projected mode value of global GIP of NGH resource is 711.20 × 1012 m3 at 2020. The projected resource (GIP) at the year of 2050 ranges from 45 (F90) to 367 (F10) × 1012 with a mode of 148.22 × 1012 m3 (Fig. 12.12a and b), comparable to the mode estimates of 84.36 × 1012 m3 and 64.51 × 1012 m3 from the mass-balanced and volumetric approaches respectively. The projected TRR resource at 2050 ranges from 28 (F90) to 145 (F10) with a mode of 41.46 × 1012 m3 (Fig. 12.12c and d), consistent with the mode estimates of 25.55 × 1012 m3 and 22.09 × 1012 m3 from the mass-balanced total global petroleum system and reservoir volumetric approaches respectively, implying the overall trend of different scholars’ estimates of global NGH resources (GIP) will continue to decline in the next 30 years (Fig. 12.13). We expect that as more and more gas hydrate exploration and research results are disclosed to the public, it will allow better distinguishing potential economic resources from the occurrence of natural hydrates. This gained knowledge from resource exploration will be gradually translated into resource estimates, so that

12.4 Evaluation of the NGH Resource by Trend Analysis Method

445

Fig. 12.12 Results statistical distributions (histograms a, c; cumulative b, d) of GIP and TRR for global NGH resources from statistical trend analysis of 29 previous estimates at the year of 2050

Fig. 12.13 Historical global original gas in-place of NGH resource estimates showing a general tendency of decreasing resource estimates with time, superimposed with fitted statistical trends to project future estimate. See Table 12.1 for details of the historical estimates (only selected numbers are plotted). The estimates of mode values for GIP of NGH from mass-balanced (MB) and volumetric approaches are shown with their uncertainty ranges. Projected resource estimates of mode values for GIP of NGH at 2020 and 2050 and uncertainty range from the statistical trend analysis are added to the plot. The historical resource estimates for GIP of NGH from 1999 to 2017 in Shenhu area are plotted to show the learning curve

446

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

the estimates become more consistent, realistic, and less uncertain. However, as suggested by the pattern of resource estimates during the 20-year hydrate exploration in the Shenhu Area, this may take decades to achieve. The projected trend of global NGH resources from 2020 to 2050 (Fig. 12.13) also support a long time period of learning.

12.5 Comparison of NGH Resource Estimates from Three Methods 12.5.1 Estimated Results from Three Approaches Comparing the resource estimates from three different approaches (Table 12.10), we argue that the estimates from mass-balanced total global petroleum system approach are more robust and reliable than those from the other two for the following reasons. (A) In lack of commercial production from gas hydrate accumulation, the form, quality and quantity of known petroleum resources from conventional reservoirs were used as references to infer the economic significance of gas hydrate concentrations, enabling distinguishing enriched resource from dispersed natural occurrence. (B) Under the total global petroleum system, hydrate is regarded as one of the products in the system. The gas resource in hydrate was constrained by the capacity of the total global petroleum system, and quantified by its fair share in physical space and chemical properties in the system. (C) The oil and gas resources in conventional reservoirs are estimates based on data and knowledge accumulated over 200 years of searching for and producing from the deposits in sedimentary basins around the world. The referenced parameters or data of oil and gas resources are reliable, and the physical constraints of forming gas hydrate are measurable, the inferred global NGH resource from known petroleum resources brings the confidence of global NGH resource estimate to the same level in conventional petroleum resource assessment. In contrast, for volumetric methods, the volumetric parameters vary greatly from place to place. In addition, obtaining a probability value that quantifies the risk of presence and adequacy of essential physical conditions of forming hydrate accumulation requires a large number of case studies and may involve subjective judgment in the absence of data. While the statistical trend analysis of historical evaluation methods relies on the historical estimates from different groups of people who have different assumptions and used different methods for various purposes. Both the amplitude and the uncertainty range will vary greatly. Because the time effect of transforming the knowledge gained from exploration and research into resource assessment, it quires personal judgement in resource extrapolation, resulting in large uncertainty in resource projection. We put forward a Reliability Index (RI) to quantitatively represent the reliability of the evaluation results from three different methods, RI = 100 × (1 − 0.2)/(P10–P90) × 1012 m3 ≤ 1.0. The closer the estimated resource value at P90 and at P10 are, the

12.5 Comparison of NGH Resource Estimates from Three Methods

447

Table 12.10 Comparison of Estimated global NGH resources (GIP, TRR) from three different methods in this study and their reliability index (RI) and sustainable time (year) analysis Type of resource

Method

F90

F50

F10

141

338

84.36

11.1/0.29

45

135

367

64.51

8.5/0.25

Statistical 95 analysis project at 2040

225

536

148.22

19.5/0.18

Mass balanced 18 approach

43

108

25.55

3.4/0.89

Reservoirs volumetric approach

14

42

119

22.09

2.9/0.76

Statistical analysis projected at 2050

28

70

145

41.46

5.5/0.68

In-place gas (GIP) Mass balanced 58 approach (1012 m3 ) Reservoirs volumetric approach

Technically recoverable gas (TRR) (1012 m3 )

Mode

Sustainable time (year)/reliability index (RI)

Note Sustainable time (year) = mode value/annual consumption of gas equivalent with 7.6 × 1012 m3 in 2017. Reliability index = 100 × (1 − 0.2)/(P10–P90) × 1012 m3 ≤ 1.0

greater the index RI, and then the higher the reliability of the results (Table 12.10). The reliability index (RI) of TRR evaluated by the three methods ranged from 0.68 to 0.89, generally higher than the reliability index (RI) of GIP with 0.18–0.29, indicating that the TRR is closer to the objective reality value than the GIP. The values of RI for GIP or TRR, obtained by material balance method, volumetric approach and trend analysis, decreased successively, indicating that the results from the material balance method were the most reliable, followed by the results from the volumetric approach, and that from the trend analysis were the worst.

12.5.2 Implications to Future Oil and Gas Energy Supply The mode value of 25.55 × 1012 m3 for TRR of mass-balanced approach, accounts for 1.87% of the total technically recoverable oil and gas resources (1362 × 1012 m3 ) in conventional reservoirs, much less than previously thought. Based on the world petroleum consumption of 7.6 × 1012 m3 (gas equivalent) at 2017 level (BP 2008), this NGH TRR resource can meet global oil and gas demands for 3.4 years. In comparison, oil and gas resources in unconventional reservoirs have much great potential (McJeon et al. 2014; Whitelaw et al. 2019), which are replacing the diminishing

448

12 Evaluation of the Global Potential Resource of the Natural Gas Hydrate

conventional oil/gas resources in North America (Schelly 2016). The world annual renewable energy production, such as nuclear, solar, wind, geothermal, hydropower, and others accounts for 15.1% in total energy consumption in 2017 (BP 2008), it is expected that it will reach 30% by 2050. However, the NGH resource may not be exploited commercially until 2030 and it is difficult to compete with other alternative energy resources by at least 2050 (Kerr 2004). Meanwhile, rapid development of unconventional oil and gas resources (Manzano 2016) will account for over 65%–75% of the total annual energy consumption before 2050 (EIA 2010). Although Japan and China have made progresses in marine hydrate production tests, and US and Canada in permafrost settings, it still has a long way to go to achieve commercial production status (Boswell 2009). The current cost of methane hydrate gas production is much higher than that from unconventional reservoirs, and significantly higher than those from conventional reservoirs as it requires additional energy input to disassociate hydrate prior to production (Chong et al. 2016). Harsh environments of deep water (Wood et al. 2002; Phrampus and Hornbach 2012) or remote permafrost region (Wadham et al. 2012), and associated geohazards with dissociation of hydrate present additional challenges. In addition, NGH exploitation may have environmental consequences. Methane is one of the most potent greenhouse gasses with capacity of absorbing heat about 21 times of carbon dioxide (Hope 2006). Hydrate dissociation in production (Klauda and Sandler 2005), hydrate structural transition throughout differentiation (Loveday et al. 2001), and critical pressure change of free-gas reservoirs below gas hydrate provinces (Hornbach et al. 2004) could lead to leakage of methane, causing greenhouse effect. Increased concentration of methane in water due to hydrate production could reduce water density, causing marine acidification (Knittel and Boetius 2009), while, the dissociation of hydrate in marine sediments would weaken slope stability, leading to submarine landslides, triggering earthquakes, and tsunamis (Chong et al. 2016). The increasing temperature of the earth caused by the massive consumption of oil and gas is much higher than we once estimated (Petrenko et al. 2017), it is necessary to drastically reduce the consumption of oil and gas to be compatible with a global warming limit of 2 °C (Mcglade and Ekins 2015), the exploitation cost for the NGH is extremely high and the technology is not yet mature, therefore, its development should be controlled. All of these are unfavorable for the NGH resource exploitation.

12.6 Summary In 1973, Trofimuk estimated that the world’s natural gas hydrate (NGH) resources totaled 3.02–3.09 × 1018 m3 , which, if fully utilized, could sustain human civilization for 400,000 years. Consequently, many believe that natural gas hydrate will eventually replace conventional petroleum supplies. Nevertheless, other academics and governmental organizations have since studied this topic and produced conflicting findings, with the maximum and minimum values changing by more than 10,000 times, mostly because of the ambiguity of two crucial factors: (1) The total gas amount

References

449

available from the potential NGH resource in Gas Hydrate Stable Zone (GHSZ); (2) The recovery factor for evaluating recoverable NGH resource. Most earlier studies did not take into account whether the gas was disseminated in mudstone rocks or stored in reservoirs with high porosity and permeability and instead considered all gas created in GHSZ as a potential gas source for the creation of prospective NGH resource. This contradicts the findings that only gas produced and expelled from source rocks with higher TOC and gas saturation can migrate and accumulate primarily driven by buoyancy in reservoir layers with high porosity and permeability to form potential NGH resources, that 95% of NGH were dispersed in mudstone with its saturation at or below 5%, and that the gas in one-third of the 13 established NGH reservoirs originates from the pyrolysis of organic matter in the region beneath the GHSZ. Since there are currently no hydrate gas reservoirs being exploited commercially and the recovery factor data used to evaluate recoverable resources in the literature are all artificially constrained or obtained through indirect means, such as simulations, it will likely take until at least 2050 for academics to be able to evaluate the global recoverable NGH resource. The geological data and research findings from the exploration and exploitation of conventional oil and gas resources in 1,186 basins worldwide are used in this paper to evaluate the global recoverable NGH resource in order to solve these two problems by studying the correlation and difference between NGH and conventional oil and gas resources, establishing a unified model, and developing mass balanced equations among them. The results of the Monte Carlo simulation show that the global NGH recoverable resource is only 25.55 billion cubic meters, or 1.87% of the total conventional resource, and can only sustain human society for 3.4 years if based on the global consumption of 7.6 billion cubic meters of gas equivalent in 2017. This is significantly less than many people had previously assumed, but it is in line with estimates from the volumetric approach using analogs of wellstudied hydrate sites and with the value predicted for the year 2050 by statistical trend analysis of time series of 29 earlier estimates from literatures. We came to the conclusion that NGH cannot take over as the primary source of energy supply in the future due to the much smaller anticipated resource, potential environmental risks in development, and lack of competitive advantage against rapidly expanding new and renewable resources. The core content of this chapter has been published in Petroleum Science (Pang et al. 2021b, 2022).

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