Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference 9819926483, 9789819926480
This book is a compilation of selected papers from the 6th International Petroleum and Petrochemical Technology Conferen
209 66 111MB
English Pages 653 [654] Year 2023
Contents
Development of Near-Bit High Precision Imaging Measuring Tool While Drilling
1 Near-Bit High Precision Gamma and Resistivity Imaging Technology
1.1 Near-Bit Gamma Resistivity Imaging Measuring Principle
1.2 Near-Bit Dynamic Azimuth Sector Measuring Principle
2 Near-Bit High Precision Gamma and Resistivity Imaging Circuit System
2.1 Gamma Resistivity Measuring Circuit System
2.2 Measuring Circuit System for Dynamic Azimuth Imaging Sector
2.3 Wireless Data Short Transmission System Across Screw Motor
3 Field Test of Near-Bit High Precision Imaging Measuring Tool While Drilling
4 Conclusion
References
Research on Relative Permeability of Shale Oil Reservoir in Jimsar Area Using Digital Cores
1 Introduction
2 Experimental Method
2.1 Experimental Materials
2.2 Digital Core Acquisition
2.3 Construction of 3D Pore Network Model
2.4 Simulation of Relative Permeability
3 Results and Discussion
3.1 Experimental Materials
3.2 The Results of Relative Permeability
3.3 Analysis of the Relative Permeability
4 Conclusion
References
Feasibility Study on Collaborative Development of Gas Storage and Enhanced Oil Recovery
1 Introduction
2 Reservoir Characteristics and Production History
3 Model Building and Scheme Design
4 Scheme Effect Analysis
5 Conclusions and Cognition
References
Influence of Aquifer Size and Gas Production Rate on Gas-Condensate Reservoir Performance
1 Introduction
2 Methods
3 Results
3.1 Impact of Aquifer Volume on Recovery Efficiency
3.2 Impact of Gas Production Rate on Recovery Efficiency
4 Discussion
4.1 Controlling Factors on Gas and Condensate Production
4.2 Suggestions for Development Optimization
5 Conclusion
References
Standards of Well Fracturing Measures in Class II Grade B Reservoirs in Water Cut Period
1 Introduction
2 Analysis of Fracturing Effect
2.1 Analysis of Technical Standards of Well-Selecting
2.2 Analysis of Technical Standards of Layer-Selecting
2.3 Design Analysis of Technological Parameter of Fracturing
2.4 Multi Linear Regression Forecast Mode
3 Technical Bound of Fracturing Wells of Class II Grade B Reservoirs PII 7-G I 4 + 5 Oil Layer in Water Cut Period
4 Application of the Results
5 Conclusion
5.1 Result of Different Position of Wells
5.2 Standards of Well-Selecting of Fracturing Wells Located on Different Position
5.3 Standards of Layer-Selecting of Different Permeability
5.4 Quantity of Sand Fracturing Design
References
Study and Application on Highly Effective Development Technology in Low Permeability and Tight Gas Reservoirs
1 Introduction
2 Production of Changqing Gas Area
2.1 Background
2.2 Deficient Gas Wells
2.3 Causes for Low Production
3 Stimulating Technologies
3.1 Reservoir Stimulating
3.2 Other Methods
4 Implementation Results
4.1 Overall Results
4.2 Specific Result for Each Methods
5 Conclusions and Suggestions
References
The Downhole Wireless Monitoring in Well Testing
1 Introduction
2 The Components of the Digital Wellbore
2.1 Wireless Transmission System
2.2 Downhole Sensor and Circuit
2.3 The Expert System
3 Field Experimentation Setup
4 Results
5 Conclusions
References
Study on Slippage Effect and Stress Sensitivity of Tight Sandstone
1 Introduction
2 Experimental Scheme
3 Study on Gas Slippage Effect
4 Study on Stress Sensitivity
5 Conclusion
References
Study on Ground Simulation Test Design Method for Multi-pulse Fracturing of Coal-Bed Methane
1 Introduction
2 Test Purpose and Design Principle
3 Design of Test Scheme
3.1 Test Main Material
3.2 Cement Target Design and Production
3.3 Test Propellant Design
3.4 Test Method
4 Test Steps
5 Test Results and Analysis
References
The Common Reservoir Development Pattern of Highly Heterogeneous Bioclastic Limestone Reservoirs and Its Application in Well Completion Design: A Case Study on Mishrif B1-2 Reservoir in H Oilfield in the Middle East
1 Introduction
2 Geological Background
3 Reservoir Development Pattern
3.1 Sedimentary Facies
3.2 Reservoir Rock Types (RRTs)
3.3 Typical Stacking Patterns of Reservoir Rocks
4 Guidance for Perforation Interval Design in Well Completion
4.1 Production Well
4.2 Water-Injection Well
5 Conclusions
References
Application of Multilateral Wells to Increase Well Productivity in Offshore Oil Field Case Study
1 Introduction
2 Methodology and Experimental Setup
2.1 COMPASS
2.2 CasingSeat
2.3 tNavigator
3 Results and Discussion
3.1 Multilateral Well
3.2 Horizontal Well
4 Environmental Impact and Conclusion
4.1 Environmental Impact
4.2 Conclusion
5 Nomenclature
References
Analysis of Drilling Trajectory and Casing Design for Straight and Deviated Wells in a Malaysian Oil Field
1 Introduction
2 Methodology and Experimental Setup
3 Results and Discussion
3.1 Case Description 1 (Compass Software)
3.2 Case Description 2 (Compass Software)
3.3 Case Description 3 (Compass Software)
4 Discussion
5 Environmental Impact
6 Conclusion
References
How the Oil Recovery Factor Changes in Different Polymer Concentrations on in the Basis of Increasing Well Drainage Area
1 Introduction
2 Experimental Part
3 Result and Discussion
References
The Effect of Sand Production to the Well Drainage Area
1 Introduction
2 Conclusion
References
Pressure Minor Losses Coefficient in Cracked Pipelines
1 Introduction
2 Experimental Setup
3 Numerical Simulation
4 Mathematical Model
5 Results and Discussion
6 Conclusion
References
Duvernay Shale Sweet Spot Identification and Resource Evaluation Model Building in Alberta Basin
1 Introduction
2 Geological Overview and Production Situation of Duvernay
2.1 Duvernay Geology Overview
2.2 Duvernay Production Status
3 Resource Evaluation Method Combining Geology and Engineering
3.1 Mapping Based Evaluation Concept
3.2 Duvernay Regional Evaluation in West Shale Basin
4 Kaybob Sweet Spot Identify and Utilization
5 Conclusion
References
Study on Flow Characteristics of Annular Flow in Sudden Expansion and Contraction Pipe
1 Introduction
2 Numerical Model of Oil-Water Annular Flow
2.1 Geometric Model
2.2 Turbulence Model
2.3 Physical Property Parameter
2.4 Boundary Condition
3 Results and Analysis
3.1 Flow Distribution with an Inlet Velocity of 2.0 m/s
3.2 Flow Distribution with an Inlet Velocity of 2.5 m/s
3.3 Flow Distribution with an Inlet Velocity of 3.0 m/s
4 Conclusion
References
Prediction of Sedimentary Reservoir in Dayangshu Basin
1 Introduction
2 Regional Overview
3 Characteristics of Sedimentary Reservoir
3.1 Physical Properties of Sedimentary Reservoir
3.2 Electrical Properties and Seismic Response Characteristics of Sedimentary Reservoir
4 Sedimentary Reservoir Prediction
4.1 Waveform Indication Inversion
4.2 Analysis of Sensitive Parameters and Construction of Characteristic Curve
4.3 Application Effect Analysis
5 Conclusion
References
New Reservoir Quality Evaluation Technique for Fractured Carbonates
1 Introduction
2 New Reservoir Quality Evaluation Technique for Fractured Carbonates
2.1 Method and Theory
2.2 Conductive Fracture Classification - FMI Images Analysis
2.3 Producible Fracture Identification- Sonic Behaviour
2.4 Reservoir Evaluation Standard (RES)
3 Example
4 Conclusion
References
Application of Integration of Geophysics, Geology and Engineering in Hydraulic Fracturing
1 Introduction
2 Theory and Method
3 Application
3.1 Design and Optimization Before Fracturing
3.2 Adjustment and Optimization During Fracturing
3.3 Analysis and Optimization After Fracturing
4 Conclusions
References
Application of “Two Widths and One Height” 3D Seismic Technology in the Exploration of Lithological Reservoirs in the Southeastern Margin of the Caspian Basin
1 Introduction
2 Solutions and Technology
3 Implementation and Application Effect Analysis
4 Conclusion
References
Scanning Electron Microscope Analysis and Evaluation Technology of Heavy Oil Reservoir Rock
1 Introduction
2 Experimental Design
2.1 Introduction of Experimental Work Area
2.2 Experimental Equipment
2.3 Pretreatment of Test Samples
2.4 Basic Operation of the Instrument
3 Study and Application of Scanning Electron Microscope in Oil and Gas Reservoir of Santanghu Basin in Work Area
3.1 Observation of Rock Structure Characteristics
3.2 Determination of Mineral Type and Content
3.3 Study on Diagenesis
3.4 Clay Mineral Analysis
3.5 Reservoir Pore Structure Analysis
3.6 Reservoir Protection
4 Conclusion
References
Foams Enhanced by Functionalized Nanoparticles for Improving Oil Production
1 Introduction
2 Experimental Section
2.1 Materials
2.2 Aqueous Phase Viscosity
2.3 Surface Tension
2.4 Zeta Potential
2.5 Bulk Foam Tests
2.6 Microfluidic Tests
3 Results and Discussion
3.1 Characterizations on Foaming Solution
3.2 Bulk Foam Stability
3.3 Oil Displacement in Microfluidic Test
4 Conclusions
References
Experimental Study on Oil Sands Pyrolysis
1 Introduction
2 Pyrolysis Experiment
2.1 Apparatus
2.2 Experimental Scheme
3 Results and Discussion
3.1 Temperature
3.2 Time
3.3 SARA Content
3.4 Hydrocarbon Distribution
3.5 CHNS/O Element Content
4 Conclusions
References
Development and Performance Evaluation of Low Damage Fracturing Fluid of Tuff-Containing Reservoir in Hailar Basin
1 Introduction
2 Characteristics of Tuff-Bearing Reservoir in Hailar Area and Requirements for Stimulation
2.1 Issues and Countermeasures
2.2 Acid-Low-Damage Cellulose Fracturing System
3 Cross-Linking of Cellulose Fracturing Fluid
3.1 Instruments and Agents
3.2 Experimental Methods
4 Experimental Result and Discuss
4.1 Viscosity of Base Fluid
4.2 Dispersion Inhibition of Cuttings by Anti-expansion Materials
4.3 Clay Mineral Expansion Test
4.4 Temperature and Shear Resistance Test
4.5 Rubber Breaking Performance Test
4.6 Anti-filtration Performance of Fracturing Fluid
4.7 Reservoir Damage Test
5 Conclusion
References
Process Design and Application of Autonomous Inflow Control Device
1 Preface
2 Principle of Equipment
3 Process Design
4 Field Test Analysis
5 Conclusion
References
The Design and Application of Perforation Cluster Parameters for Staged Fracturing of Horizontal Wells in Jimsar Shale Oil
1 Introduction
2 Development Status of Jimsar Shale Oil
3 Comparative Analysis of Fracturing Effects of Different Segmented Cluster Processes
3.1 Analysis of Fracture Reconstruction Scope
3.2 Analysis of Liquid Inlet Equilibrium Degree of Each Cluster
3.3 Optimization of Optimal Hole Layout Parameters
4 Case Study
5 Conclusion
References
Long-Term Chemical Stability of Anionic Surfactants at an Elevated Temperature
1 Introduction
2 Experimental
2.1 Materials
2.2 Surface and Rheology Property Measurement
2.3 Long-Term Stability Test
3 Results and Discussion
3.1 TGA Analysis
3.2 Surface Property
4 Conclusions
References
Study on Feasibility of Surface Concentric Pipe Type Zonal Water Injection Technology in Middle East
1 Introduction
2 Optimization of Zonal Water Injection in Middle East
2.1 Application Status of Zonal Water Injection Technology in Middle East
2.2 Development of Zonal Water Injection in Middle East
2.3 Optimization of Zonal Water Injection in Middle East
3 Principle and Tools of Surface Concentric Pipe Zonal Water Injection Technology
3.1 Structure and Principle
3.2 Matching Tools
4 Adaptability Analysis of Surface Concentric Pipe Zonal Water Injection Technology in Middle East
4.1 Checking the Running Depth of Tubing
4.2 Adaptability Analysis of Water Injection Rate
5 Conclusion
References
Analysis and Measures Research on Inefficiency of Produced Water Treatment Station in Water Injection Development of Low Permeability Oilfield
1 Introduction
2 Analysis and Solutions of Low Efficiency of Produced Water Treatment Station
2.1 Analysis of Low Efficiency of Produced Water Treatment Station
2.2 Solutions of Low Efficiency of Produced Water Treatment Station
3 Materials and Methods
3.1 Reagents and Instruments
3.2 Evaluation Method of Reagent Screening
4 Results and Discussion
4.1 Water Quality Analysis
4.2 Flocculant Screening and Evaluation
4.3 Screening and Evaluation of Iron Removal Reagents
4.4 Screening and Evaluation of Scale Inhibitors
4.5 Screening and Evaluation of Corrosion Inhibitors
4.6 Screening and Evaluation of Fungicides
4.7 Reagent Cost
5 Conclusion
References
Laboratory Experimental Study of Air Foam Flooding in Low Permeability Reservoirs
1 Introduction
2 Air Foam Agent Screening
3 Evaluation and Preparation of Basic Performance of Foaming Agent
3.1 Foaming Ability and Stabilizing Ability of Foaming Agent
3.2 Foaming Agent Solubility
3.3 The pH Value of the Foaming Agent
3.4 Evaluation of Interfacial Tension of Foaming Agent
3.5 Strengthen Foam System Performance Evaluation
4 Evaluation of Influencing Factors of Foam Performance
4.1 The Influence of Different Foaming Agents and Concentrations on Foam Performance
4.2 Temperature Resistance of Foaming Agent
4.3 Long-Term Thermal Stability of Foaming Agent
4.4 Salt Resistance of Foaming Agent
4.5 Adsorption Resistance
4.6 Oil Resistance
4.7 Emulsifying
4.8 Evaluation of Foam Regeneration Ability
5 Conclusion
References
Research and Improvement of Downhole Injection Production Device for Oil Production
1 Introduction
1.1 A Subsection Sample
2 Application Analysis of Downhole Injection Production Device in Oil Production
3 Research and Improvement
4 Working Principle
5 Experimental Evaluation of Improved Device
5.1 Installation of New Downhole Injection Production Device for Oil Production
5.2 Reverse Sealing Test
5.3 Live Simulation Experiment of New Downhole Injection Production Device for Oil Production
5.4 Opening and Closing Test
6 Conclusion
References
Engineering Solution for Variable Curvature Trajectory Design of Extended Reach Well
1 Introduction
2 Multi-arc Curve Approximation
2.1 Calculate the Tangents T1 and T2 of the Two Points P1 and P2
2.2 Determine Common Tangent Point P, Multi-arc L1, L2
2.3 Piecewise Approximation Error Analysis
3 Instance Calculation
3.1 Variable Curvature Trajectory Design and Multi-arc Curve Approximation
3.2 Error Diagram of Multi-arc Curve Approximation
4 Conclusion
References
Effect of Ca-Alginate Beads on the Rheological Properties of the Oil Well Cement Paste
1 Introduction
2 Experimental
2.1 Materials
2.2 Preparation and Characterization of Ca-Alg Beads
2.3 Rheological Properties of Cement Slurry with Ca-Alg Beads
3 Results and Discussion
3.1 Structure Characterization of Ca-Alg Beads
3.2 Water Absorption of Ca-Alg Beads
3.3 Rheological Properties of Cement Slurries Containing Ca-Alg Beads
4 Conclusion
References
Friction Calculation of Annular Fracturing String in Sulige Gas Field
1 Introduction
2 The Annular Fracturing Process
3 Sample the Annular Fracturing Process
4 Calculation of Friction Resistance Along the Pipe String
5 Example of Fracturing Fluid Friction Calculation
6 Conclusion
References
Research on Pressure Drop Law of Drilling Shutdown in Oil Layer a and Implementation Effect of Relaxing Pressure Limits
1 Introduction
2 Research on the Law of Pressure Drop in Natural Pressure Relief Wells
2.1 The Poorer the Reservoir Connection, the Slower the Pressure Drop
2.2 The Less the Pressure Relief Direction, the Slower the Pressure Drop Rate
2.3 The Greater the Cumulative Injection-Production Ratio, the Slower the Pressure Drop
2.4 The Smaller the Apparent Water Absorption Index, the Slower the Pressure Drop
3 Analysis of the Overflow Flow Rate of Different Types of Water Injection Wells
3.1 The Larger the Thickness of the Injection Well, the Well with More Accumulated Injection Volume Will Release More Overflow Water
3.2 The Larger the Thickness of the Injection Well, the Smaller the Cumulative Injection Volume, the Overflow Water Volume is Moderate
3.3 Poor Well Development, Low Cumulative Injection Volume Will Release Low Overflow Water
4 The Implementation of the Effect of Relaxing the Boundary of Drilling Pressure
4.1 Shorter Drilling Cycle
4.2 Reduced Production Loss of Old Wells
4.3 High Cementing Quality Rate Ratio
4.4 Realize Safe Drilling
5 Conclusion
References
Treatment of Waste Oil-Based Drilling Mud During Shale Oil Development by Vacuum Thermal Distillation
1 Introduction
2 Experimental Materials and Methods
2.1 Experimental Materials and Instruments
3 Experimental Results and Discussion
3.1 Centrifugal Pretreatment
3.2 Comparative Study on Atmospheric and Vacuum Thermal Distillation Technology
3.3 Study on the Performance of Recycled Drilling Fluid
4 Conclusion
References
Development and Application of Mechanical Two-Way Anchor Fracturing Technology in Horizontal Wells
1 Introduction
2 Study on the Influence of Fracturing Operation on the Stability of Pipe String
3 Pipe String of Mechanical Two-Way Anchor Fracturing Technology in Horizontal Well
4 Research on Key Fracturing Tools
4.1 Structural Design of the Novel Y211 Compression Packer
4.2 Sealing Performance Optimization
4.3 Anchoring Performance Optimization
5 Field Application and Effect
6 Conclusion and Understanding
References
Immovable Pipeline Decompression and Augmented Injection Integrated Technology Apply to Low Permeability Reservoir
1 Introduction
2 Immovable String Extruding Device for High Pressure Water Injection Well
2.1 High Pressure Wellhead Protector
2.2 With Pressure Delivery Technology Under Situation of Immobile Wellhead
2.3 The High Pressure Acid Extruding Process of Stationary Wellhead of Injection Well is Formed
3 Polyacid Acid System
3.1 Analysis of the Main Factors Affecting the Acidification Effect
3.2 Develop Organic Phosphonic Acid Main Agent to Form a New Multi-acid Acid System
3.3 Optimization of the Additive of Multi-acid Acid System [3]
3.4 Based on the Characteristics of Low Permeability and Strong Water Sensitive Reservoirs, the Performance Evaluation of the New Multi-acid Acid System is Carried Out [4]
3.5 Field Application of the New Acid System
4 Typical Examples and Conclusions
4.1 Typical Examples
4.2 Conclusion
References
Performance Analysis of Transient Pressure Wave Method for Detecting Partial Blockage of CO2 Pipeline
1 Introduction
2 Computational Model
2.1 Continuity Equation
2.2 Equation of Motion
2.3 Equation of State
2.4 Compression Factor Calculation
2.5 Transient Flow Propagation Model
3 Transient Pressure Wave Analysis Method for Blocked Pipes
3.1 Modeling of Pipe Blockages
3.2 Pipeline Model Validation
3.3 Blockage Detection by Transient Pressure Waves
3.4 Analysis Strategy of Transient Pressure Wave Method
4 Result
4.1 Input Parameter Setting
4.2 Calculation of Characteristic Parameters and Analysis of Results
5 Conclusions and Recommendations
References
Failure Case Analysis and Prevention of Facilities in Oil and Gas Transmission Station
1 Introduction
2 Typical Failure Case Analysis
2.1 Failure Caused by Fatigue
2.2 Failure Caused by Corrosion
2.3 Failure Case Analysis Caused by Welding Defects
2.4 Failure Caused by Quality Defects
3 Failure Cause Summary
4 Suggestions for Preventing the Failure of Facilities in the Station
References
Effects of Gas Condition and Baffle Installation on Bed Hydrodynamics in FCC Regenerators
1 Introduction
2 MP-PIC Model and Simulation Setup
2.1 Governing Equations
2.2 Drag and Kinetic Models
2.3 Simulation Setup
3 Results and Discussion
3.1 Grid Verification and Kinetic Validation
3.2 Axial Profiles of Solids Fraction
3.3 Radial Profiles of Solids Fraction
3.4 Effect on Pressure Fluctuation
3.5 Lateral Mal-Distribution of Solids
4 Conclusions
References
An Applied Research of Factory Prefabrication Techniques in the Overseas Oil and Gas Storage and Transportation Engineering Construction
1 Introduction
2 Significance of Factory Prefabrication
2.1 Improve Project Construction Efficiency and Ensure Project Construction Quality
2.2 Save Project Resources and Reduce Project Investment
2.3 Reduce Material Transportation Volume and Transportation Cost
3 Development and Application of Factory Prefabrication in Petroleum Construction Industry
3.1 Current Situation Abroad
3.2 Current Domestic Situation
3.3 Problems of Factory Prefabrication in China
4 Key Strategies for the Application and Implementation of Factory Prefabrication
4.1 Factory Prefabrication Planning
4.2 Key Technologies of Prefabrication
4.3 Prefabrication System
4.4 Prefabrication Management
5 Application Examples
5.1 Project Overview
5.2 Determine the Production Object and Capacity of Prefabrication
5.3 Determine the Key Technologies of Prefabrication
5.4 Determine the Content and Scale of Prefabrication System
5.5 Implementation and Management of Factory Prefabrication
6 Conclusion
References
Investigating Non-uniform Corrosion Behavior of Pipe Weldment Using an Array of Coupled Multi-ring Form Sensor in the CO2-Contained Corrosion Environment
1 Introduction
2 Materials and Methods
2.1 The Processing and Assembly of the Weldments and the CMRFSA
2.2 The Monitoring Principle of the CMRFSA
2.3 The Experimental Setup
2.4 Corrosion Morphology Characterization and Corrosion Product Analysis
2.5 Numerical Model Description
3 Results
3.1 The Corrosion Depth Results of the CMRFSA
3.2 Numerical Calculation of CO2 Corrosion
3.3 Surface Characterization
4 Conclusions
References
Low-Height Security Control Strategy of Unmanned Rotorcraft for Oil and Gas Pipeline Inspection in Low-Height Complex Terrains
1 Introduction
2 Height Control Strategy of Unmanned Rotorcraft Inspection
3 Design of Multi-height Source of Unmanned Rotorcraft
4 Low-Height Security Control Strategy of Unmanned Rotorcraft
4.1 Low-Height Security Strategy for Flight in Fluctuation Terrains
4.2 Low-Height Security Strategy for Flight in Near-Ground Terrains
5 Simulation of Low-Height Security Control Strategy of Unmanned Rotorcraft
5.1 Low-Height Security Strategy for Flight in Fluctuation Terrains
5.2 Low-Height Security Strategy for Flight in Fluctuation Terrains
5.3 Low-Height Security Strategy for Flight in Near-Ground Terrains
6 Conclusion
References
Research and Application of Intelligent Auxiliary Decision-Making Platform for Lost Circulation Based on Big Data Technology
1 Introduction
2 Composition and Principle of Intelligent Auxiliary Decision-Making Platform
2.1 Framework Design
2.2 Data Collection
2.3 Data Conversion
2.4 Data Cleaning
2.5 Correlation between Data Parameters and Lost Circulation
3 Data Mining Model
3.1 Numerical Processing of Textual Parameters
3.2 Clustering of Similar Well Intervals with Lost Circulation Tendency
3.3 Apriori Association Rules Mining
3.4 Platform Building
3.5 Filed Application
4 Conclusion
References
Application of Intelligent Rodless Artificial Lift Technology in Shale Oil of Changqing Oilfield
1 Introduction
1.1 A Subsection Sample
2 Rodless Artificial Lift Technology Used in Changqing Shale Oil Reservoir
2.1 Selection of Rodless Artificial Lift System
2.2 Optimization of ESPCP System
2.3 Wellbore Matching Technology
2.4 Intelligent Control System
3 Achievement of Field Application
3.1 Construction of Demonstration Area
3.2 Technical Indicators
3.3 Economic Benefit
4 Discussion
5 Conclusion
References
Rapid Petroleum Engineering Technique Check and Applications
1 Introduction
2 Petroleum Engineering Technique Check
2.1 Characteristics of Petroleum Engineering
2.2 PETC and Rapid PETC
2.3 Different Types of PETC
3 Development Trends of PETC
3.1 CETIC Development Trends
3.2 ETAC Development Trends
3.3 CEEKSC Development Trends
4 Mobile Application System for Rapid PETC
4.1 Technical Requirements
4.2 Engineering Technology Check and Application System
4.3 System Applications and Next Development Plan
5 Conclusion
References
A Long-Term Production Prediction Method for Horizontal Wells in Shale Gas Reservoirs Based on DSTP Recurrent Neural Network
1 Introduction
2 Description of DSTP-RNN Model
3 Methodology
3.1 Data Preprocessing
3.2 Training and Prediction Schemes
3.3 Evaluation Indices
4 Results and Discussion
4.1 Production Forecast Results
4.2 Model Comparison
5 Conclusion
References
The Effect of the Novel Agricultural Photovoltaic System on Water Evaporation Reduction and Sweet Potato Yield
1 Introduction
2 Spectrum Splitting and Concentrated APV (SCAPV)
3 Experimental Materials and Method
3.1 Experimental Site
3.2 Experimental Method
4 Results and Discussion
5 Conclusion
References
Study on Plugging Mechanism of Sand Control Medium in Hydrate Argillaceous Silt Reservoir
1 Introduction
2 Experiment
2.1 Experimental Principle and Equipment
2.2 Experimental Materials
2.3 Plugging Rule of Sand Control Medium
3 Plugging Mechanism of Sand Control Medium in Hydrate Argillaceous Silty Sand Reservoir
3.1 Medium Plugging Mechanism with High Sand Control Accuracy
3.2 Medium Plugging Principle When Sand Control Accuracy is Low
4 Conclusion
References
Simulation and Testing of Intelligent PV Modules via Matlab/Simulink
1 Introduction
1.1 The Demand for PV as Alternative
1.2 Application Scenarios of PV Modules
1.3 Optimization via Simulation
2 Modeling Establishment and Discussion
2.1 PV Phenomenon
2.2 Solar Cell Single Diode Model
2.3 Solar Cell Dual Diode Model
2.4 Modeling of Intelligent Half-Chip Components Based on Matlab/Simulink
2.5 Modeling of Intelligent Half-Cell Module Array Based on Matlab/Simulink
2.6 Power Gain of a Single Smart Module
3 Results and Analysis of Hot Spot Experiments
4 Conclusion
References
Finite Element Model for Prediction of Buckling Phenomenon in Oil and Gas Wells
1 Introduction
1.1 Recent Advancements in Drill String Mechanics Modelling
1.2 Critical Load
2 Methodology
2.1 Finite Element Model Input
2.2 Model Property
2.3 FE Large Deformation
2.4 Steps, Increments, and Iterations
2.5 Contact Interaction
2.6 FE Analysis
2.7 BHA and Rock Brick
2.8 Post Buckling
3 The Experimental Procedure
3.1 Drag-Buckling Relationship
3.2 Case Study
4 Results and Discussions
5 Conclusion
6 Recommendation
References
The Impact of Acid Fracking Injection Pressure on the Carbonate-Mishrif Reservoir: A Field Investigation
1 Introduction
2 Methodology
2.1 Analysis of Fracture Pressure
2.2 Basic Performance of Gelled Acid
2.3 Mini Frac Analysis
2.4 G Function Analysis
2.5 Log–log Diagnostic Graph
2.6 Acid Frac Analysis
2.7 Acid Penetration in Fractures
2.8 Conductivity of Acid Fracture
2.9 Buildup Test Analysis ISIP (Instantaneous Shut-In Pressure)
3 Results and Discussion
3.1 Properties of Geology and Petrophysics of Well ADM7-X
3.2 Basic Performance of Gelled Acid
3.3 Mini Frac Analysis
3.4 Acid Frac Analysis
3.5 Buildup Test Analysis ISIP (Instantaneous Shut-In Pressure)
3.6 Log-Log Plot Analysis
3.7 Productivity Assessment
4 Conclusions
References
Author Index
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Citation preview
Jia’en Lin Editor
Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference
Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference
Jia’en Lin Editor
Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference
Editor Jia’en Lin College of Petroleum Engineering Xi’an Shiyou University Xi’an, Shaanxi, China
ISBN 978-981-99-2648-0 ISBN 978-981-99-2649-7 (eBook) https://doi.org/10.1007/978-981-99-2649-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 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 translation, 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 publisher, 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 publisher 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 publisher remains 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
Contents
Development of Near-Bit High Precision Imaging Measuring Tool While Drilling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hengtian Jia, Weiping Ai, Weimin Mao, Liexin Peng, Limin Sheng, Xiurong Dou, Dezhou Yu, and Wenyi Chen
1
Research on Relative Permeability of Shale Oil Reservoir in Jimsar Area Using Digital Cores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shen-gen Chen, Yuan-kai Xiang, Lei-ming Cheng, and Jun-xiu Ma
14
Feasibility Study on Collaborative Development of Gas Storage and Enhanced Oil Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiao-chen Wang, Xin-wei Liao, and Kang Tang
27
Influence of Aquifer Size and Gas Production Rate on Gas-Condensate Reservoir Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yi-fang Wu, Wei-hong Na, Ben Wang, Yan Li, Xin-xin Zhong, and Li Ma
39
Standards of Well Fracturing Measures in Class II Grade B Reservoirs in Water Cut Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yao-Zhou
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Study and Application on Highly Effective Development Technology in Low Permeability and Tight Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Peng Zhang, Min Xu, Rui Zhang, Xiao-chuang Ye, Jie Qiu, Mei-ji We, and Yan-rong Li
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The Downhole Wireless Monitoring in Well Testing . . . . . . . . . . . . . . . . . . . . . . . . Xiong Han, Dong-xiao Pang, Zhi-lin Li, Hu Deng, and Qiu-yun He
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Study on Slippage Effect and Stress Sensitivity of Tight Sandstone . . . . . . . . . . . Heng-yang Wang
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Study on Ground Simulation Test Design Method for Multi-pulse Fracturing of Coal-Bed Methane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jin-jun Wu, Jing Liu, Jun-rui Duan, Ren-jie Zhang, and Kai Wang
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The Common Reservoir Development Pattern of Highly Heterogeneous Bioclastic Limestone Reservoirs and Its Application in Well Completion Design: A Case Study on Mishrif B1-2 Reservoir in H Oilfield in the Middle East . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Min Gao, Lei Shao, Hai-ying Han, Guan-ming Shao, and Xiao-wei Sun
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Application of Multilateral Wells to Increase Well Productivity in Offshore Oil Field Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Salma Osama Taha Taha El Daly, Elhassan Mostafa Abdallah, and Yasir Mukhtar Analysis of Drilling Trajectory and Casing Design for Straight and Deviated Wells in a Malaysian Oil Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Nada Ahmed Abbas Ahmed Malek, Elhassan M. Abdallah, Mohd Azraai Miswan, and Yasir M. F. Mukhta How the Oil Recovery Factor Changes in Different Polymer Concentrations on in the Basis of Increasing Well Drainage Area . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Jabrayil Eyvazov, Mehri Guliyeva, and Urfan Guliyev The Effect of Sand Production to the Well Drainage Area . . . . . . . . . . . . . . . . . . . 141 Jabrayil Eyvazov, Mehri Guliyeva, and Urfan Guliyev Pressure Minor Losses Coefficient in Cracked Pipelines . . . . . . . . . . . . . . . . . . . . . 147 Jafar A. Ali Duvernay Shale Sweet Spot Identification and Resource Evaluation Model Building in Alberta Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Jing Ran, Rui Zhou, Jin-rui Guo, and Na-xin Tian Study on Flow Characteristics of Annular Flow in Sudden Expansion and Contraction Pipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Jun-hong Huang, Fan Jiang, and Ju Yan Prediction of Sedimentary Reservoir in Dayangshu Basin . . . . . . . . . . . . . . . . . . . 186 Jin-xin Han New Reservoir Quality Evaluation Technique for Fractured Carbonates . . . . . . . 200 Ping Yan, Lan Luo, De-fang Liu, Jin-yu Chang, and Jia-yu Chen Application of Integration of Geophysics, Geology and Engineering in Hydraulic Fracturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Qi-hu Jin, He Lin, Chao Feng, Gang Xu, Na Li, and Jin-ling Du
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Application of “Two Widths and One Height” 3D Seismic Technology in the Exploration of Lithological Reservoirs in the Southeastern Margin of the Caspian Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Bao Li, Jinshu Tang, Shan-bo Sheng, Zi-ping Liu, Ke-Baijiang Al, Xue-yin Ding, Fu-tian Zhang, and Wei-xiang Zhong Scanning Electron Microscope Analysis and Evaluation Technology of Heavy Oil Reservoir Rock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 Qing-fa Xu and Jian-zhong Wang Foams Enhanced by Functionalized Nanoparticles for Improving Oil Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 Chang Da, Ming Han, Ying Wang, and Abdulkareem Alsofi Experimental Study on Oil Sands Pyrolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 Xue-qi Liu, Shi-jia Zhu, Jian Liu, Li-kun Xu, Yun-bo Li, Yu-bing Zhou, Zhong-zhen Ma, Chao-qian Zhang, Jian Li, Li-hong Fan, Xiao-yan Geng, Yang Liu, Ke-xin Zhang, Mei Qi, and Shang-qi Liu Development and Performance Evaluation of Low Damage Fracturing Fluid of Tuff-Containing Reservoir in Hailar Basin . . . . . . . . . . . . . . . . . . . . . . . . . 268 Xian-jun Wang, Yong-chang Wang, Qing-guo Wang, Qing-song Li, Li Wang, and Ke-ming Fan Process Design and Application of Autonomous Inflow Control Device . . . . . . . 281 Yi-long Dong, Meng Cai, Chong-jiang Liu, Xing-liang Song, Xiao-yu Xu, and Zhi-rui Wang The Design and Application of Perforation Cluster Parameters for Staged Fracturing of Horizontal Wells in Jimsar Shale Oil . . . . . . . . . . . . . . . . . . . . . . . . . 287 Lei-ming Cheng, Jian-min Li, Yuan-kai Xiang, Ming Lv, and Bo-yao Wei Long-Term Chemical Stability of Anionic Surfactants at an Elevated Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 Jian Hou, Ming Han, and Abdulkareem Alsofi Study on Feasibility of Surface Concentric Pipe Type Zonal Water Injection Technology in Middle East . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 Xue-qin Huang, Zheng-xue Du, Gui Hu, Zhen Nie, and Chun-peng Wang Analysis and Measures Research on Inefficiency of Produced Water Treatment Station in Water Injection Development of Low Permeability Oilfield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 Zhen-peng Ma, Zhi-gang Yang, Tian-qi Ma, and Hui Li
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Laboratory Experimental Study of Air Foam Flooding in Low Permeability Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Jin-yuan Zhang, Jun-bin Chen, Xu Jiang, Chen Sun, Yuan-yuan Kou, and Wen-xin Liu Research and Improvement of Downhole Injection Production Device for Oil Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Tao Zhao, Huan Liang, Hao-jie Meng, Zhichao Wang, Lihao Zhou, Jiayi Zhang, and Weili Yin Engineering Solution for Variable Curvature Trajectory Design of Extended Reach Well . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 Quan-zhi Yang Effect of Ca-Alginate Beads on the Rheological Properties of the Oil Well Cement Paste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 Ming Liu, Miao-miao Hu, and Jin-tang Guo Friction Calculation of Annular Fracturing String in Sulige Gas Field . . . . . . . . . 377 Jian-chao Tian, Ji-li Hu, Chang-jun Long, Jiang-fen Jia, and Zheng-dong Xu Research on Pressure Drop Law of Drilling Shutdown in Oil Layer a and Implementation Effect of Relaxing Pressure Limits . . . . . . . . . . . . . . . . . . . . 383 Hui-ying Gao and Jian-qi Li Treatment of Waste Oil-Based Drilling Mud During Shale Oil Development by Vacuum Thermal Distillation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Tian-qi Ma, Zhi-gang Yang, Chen-xi Dong, Wang Ke, and Zhen-peng Ma Development and Application of Mechanical Two-Way Anchor Fracturing Technology in Horizontal Wells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Meng Cai, Xiao-chuan Zhang, Li Ban, Li-hong Kong, and Xiu-hong Chen Immovable Pipeline Decompression and Augmented Injection Integrated Technology Apply to Low Permeability Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . 412 Xue-ying Li, Qi-fan Si, Meng-meng Ning, and Hua Huang Performance Analysis of Transient Pressure Wave Method for Detecting Partial Blockage of CO2 Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427 Bing Chen, Jian Bi, Qing-hua Kang, and Xiang-zeng Wang Failure Case Analysis and Prevention of Facilities in Oil and Gas Transmission Station . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 Guo-qi Ren, Ju-tao He, Xi-cheng Wang, and Gao-feng Wang
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Effects of Gas Condition and Baffle Installation on Bed Hydrodynamics in FCC Regenerators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 458 Adefarati Oloruntoba, Yong-min Zhang, and Yasir M. F. Mukhtar An Applied Research of Factory Prefabrication Techniques in the Overseas Oil and Gas Storage and Transportation Engineering Construction . . . . . . . . . . . . 477 Yu Wang, Yun-xiu Sai, Lin-hao Qiu, and Guo-zhu Chen Investigating Non-uniform Corrosion Behavior of Pipe Weldment Using an Array of Coupled Multi-ring Form Sensor in the CO2 -Contained Corrosion Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487 Ye-sen Zhu, Tao Ren, Yi-feng Han, Tao-yong Hu, and Bao-wen Hu Low-Height Security Control Strategy of Unmanned Rotorcraft for Oil and Gas Pipeline Inspection in Low-Height Complex Terrains . . . . . . . . . . . . . . . 509 Chen-xi Dong, Tian-qi Yang, Tian-qi Ma, Lei Hou, and Si-yuan He Research and Application of Intelligent Auxiliary Decision-Making Platform for Lost Circulation Based on Big Data Technology . . . . . . . . . . . . . . . . 521 Feng-feng Xiao, Zheng-qiang Deng, Mei Qi, Xian-tao Xie, and Guan-cheng Jiang Application of Intelligent Rodless Artificial Lift Technology in Shale Oil of Changqing Oilfield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Ze-Kun Deng, Peng-Xu Chang, Zhi-Ping Zhou, Yu-Ping Chen, Jing Guo, and Qing-Ming Gan Rapid Petroleum Engineering Technique Check and Applications . . . . . . . . . . . . 545 Gui Hu, Ming-yue Cui, Ye Tao, Xue-qin Huang, Shu Yang, Xin Chang, and Shi-tang Chen A Long-Term Production Prediction Method for Horizontal Wells in Shale Gas Reservoirs Based on DSTP Recurrent Neural Network . . . . . . . . . . . . . . . . . . 555 Zhao Hong-Yan, Liao Xin-Wei, Dong Peng, and Wang Xiao-Yan The Effect of the Novel Agricultural Photovoltaic System on Water Evaporation Reduction and Sweet Potato Yield . . . . . . . . . . . . . . . . . . . . . . . . . . . . 567 Altyeb Ali Abaker Omer, Ming Li, Xin-liang Liu, Wen-jun Liu, Yang Liu, Yasir M. F. Mukhtar, Jan Ingenhoff, and Wen Liu Study on Plugging Mechanism of Sand Control Medium in Hydrate Argillaceous Silt Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 579 Fu-li Li
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Simulation and Testing of Intelligent PV Modules via Matlab/Simulink . . . . . . . 591 Alaeldin M. Tairab, Yasir M. F. Mukhtar, and Khalaf Osamah Ibrahim Finite Element Model for Prediction of Buckling Phenomenon in Oil and Gas Wells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 Yousif Eltahir Bagadi, Yasir M. F. Mukhtar, and Faleh H. M. Almahdawi The Impact of Acid Fracking Injection Pressure on the Carbonate-Mishrif Reservoir: A Field Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622 Faleh H. Almahdawi, Usama Alameedy, Ahmed Almomen, Ayad A. Al-Haleem, Ali Saadi, and Yasir M. F. Mukhtar Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643
Development of Near-Bit High Precision Imaging Measuring Tool While Drilling Hengtian Jia(B) , Weiping Ai, Weimin Mao, Liexin Peng, Limin Sheng, Xiurong Dou, Dezhou Yu, and Wenyi Chen CNPC Engineering Technology R&D Company Limited, Beijing, China [email protected]
Abstract. The exploration and development of low-permeability and ultra-lowpermeability reservoirs have been focused at home and abroad. Low-permeability oil and gas reserve resources are huge in China. However, difficult problems are available such as low productivity in reservoir drilling and development because of the limitations of existing drilling technologies. Conventional geosteering tools can be used for identifying the overall geological and stratigraphic structure as well as reservoir-related information characteristics at the borehole trajectory direction only. However, low-permeability reservoirs are characterized by strong heterogeneity, poor stratum physical properties, thin reservoirs and complex structures, therefore more precise borehole trajectory control and reservoir evaluation technologies are required accordingly. The near-bit resistivity gamma imaging while drilling is combined with the wireless short transmission technology of electromagnetic waves across the screw in the geosteering system, and the system can be used for accurately obtaining the 360-degree high-resolution image information of borehole walls, and wirelessly transmitting the near-bit reservoir data information to the MWD system on the upper part of the screw motor through electromagnetic wave propagation effect suitable for various drilling fluid systems. The information is supplied to geoscientists for research and judgment. The stratum dip angle is calculated, and the stratum boundary is identified according to the information, thereby controlling the borehole trajectory more accurately, and providing technical tools for the drilling and development of low-permeability and ultra-low-permeability oil and gas reservoirs. Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 1–13, 2023. https://doi.org/10.1007/978-981-99-2649-7_1
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H. Jia et al. Keywords: near-bit · imaging while drilling · geosteering
The demand for drilling instruments of ultra-thin-layer horizontal wells, unconventional multi-branch horizontal wells and other highly difficult horizontal wells is also increasing constantly with the large-scale development of deep and complex oil and gas resources [1]. 360-degree high-resolution image logging is realized on borehole walls through underground rotation with drill string by near-bit high precision imaging instruments with drilling. The instrument can be used for meticulous depiction on complex geological structures such as faults, cavities, fractures, etc. on the one hand, it is also used for evaluating oil and gas reservoirs more accurately, optimizing and adjusting the borehole trajectory timely, and improving the reservoir drilling ratio [2]. Many foreign oil service companies have launched their own imaging instruments while drilling. The instruments are used for realizing wellbore scanning imaging by integrating azimuth resistivity measuring electrode and natural gamma sensors [3]. The domestic near-bit image logging technology while drilling is still in its infancy, therefore it is urgent to develop near-bit high precision gamma and resistivity imaging instrument with independent intellectual property rights. Technical tools are provided for complex horizontal well geosteering assignments in oil and gas reservoirs [4].
1 Near-Bit High Precision Gamma and Resistivity Imaging Technology The azimuth sector, resistivity and gamma sensors are installed on the positions within 1 m above the bit according to the near-bit high precision gamma and resistivity imaging instrument. The instrument is rotated with the drilling tool together during drilling. The azimuth sector sensor is used for measuring the sector positions of resistivity and gamma sensors in the wellbore. The resistivity and gamma sensors are used for measuring the natural gamma radiation intensity and rock resistivity values of the faced stratum in the wellbore. The measured stratum resistance, natural gamma and azimuth sectors are combined for judging the lithology of the drilled stratum around the wellbore, and forming image information. The stratum interface can be accurately distinguished through the change tendency of the lithology. The stratum dip angle can be obtained [5] as shown in (see Fig. 1). Geosteering engineers can apply the information for optimizing drilling activity schemes instantly and accurately, thereby ensuring that borehole trajectory penetration across oil and gas reservoirs, increasing reservoir drilling ratio and drilling efficiency finally, and reducing drilling costs. The near-bit high precision gamma and resistivity imaging measurement system is shown in (see Fig. 2). The system is composed of the follows: a near-bit gamma resistivity imaging measuring instrument, a wireless data transmission system across the screw motor, an MWD drilling fluid pulse information transmission system, a ground survey data interpretation system and other key units.
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Fig. 1. Near-bit high precision gamma and resistivity imaging technology
Fig. 2. Near-bit high precision gamma and resistivity imaging measurement system
1.1 Near-Bit Gamma Resistivity Imaging Measuring Principle The content and properties of natural radioactive elements are different due to the different geological characteristics of different strata, and the gamma intensity generated by them is also different accordingly. Therefore, the gamma ray sensor is used for monitoring the gamma ray of the stratum, thereby distinguishing different geological layers and judging the stratum of the borehole [6]. (see Fig. 3.) shows that the gamma sensor of the near-bit high precision gamma and resistivity imaging instrument is installed in the installation cabin on the upper portion of the drilling bit near the drill collar surface. The gamma rays emitted by a specific azimuth sector of the stratum are detected by
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partially shielding the sensor and opening a window. The stratum around the wellbore can be scanned when the gamma sensor is rotated with the drilling tool, thereby finally presenting the gamma image information of the drilled borehole. Rogowski coils are installed on both ends of the resistivity imaging instrument [7]. The focus alternating current circuit flowing instrument drill collar and geological media can be formed under the action of alternating excitation voltage. The current signal strength is affected by the strata resistivity value. The stratum resistivity image information around the drilled borehole can be obtained by the measuring circuit through measuring the alternating current values flowing in the stratum and inverting the calibration formula [8].
Fig. 3. Near-bit high precision gamma and resistivity imaging instrument
1.2 Near-Bit Dynamic Azimuth Sector Measuring Principle Since the near-bit high precision gamma and resistivity imaging instrument is operated while drilling, and it is close to the drilling bit, the drilling bit is strongly vibrated during drilling in the stratum. The triaxial accelerometer, an important core sector in azimuth sensor measurement, is seriously interfered by vibration, thereby affecting the the precision of instrument dynamic azimuth sector angle measurement seriously [9]. It is necessary to combine the triaxial gravity acceleration sensor and the triaxial magnetoresistive sensor accordingly, and the dynamic azimuth sector angle is measured by the attitude fusion algorithm. (see Fig. 4) shows that the triaxial magnetoresistive sensor is used for obtaining the instrument azimuth information by measuring the weak magnetic field of the earth, and it is slightly affected by downhole vibration interference. However, the gravity direction information of the earth is not reflected in the measuring azimuth sector thereof. Therefore, it is impossible to distinguish the upper, lower, left and right directions of the sector angle, and it is impossible to guide borehole trajectory adjustment accordingly. The triaxial gravity acceleration sensor and the triaxial
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magnetoresistive sensor should be combined. The drilling motion of the drilling bit is suspended, and the instrument is also not rotated when the single drill string is connected during drilling ground construction. Vibration has the minimum influence on triaxial acceleration measurement of the instrument under the circumstance. Therefore, when the acceleration sensor detects the suspension of the drilling operation vibration, the gravity tool face angle, the magnetic tool face angle and the angle difference thereof of the instrument under the circumstance can be measured immediately through the triaxial acceleration and magnetoresistive sensors, which are preserved by the circuit system. When single drill string connection is finished, drilling vibration and instrument rotation are started, the magnetic tool face angle can be measured in real time through the triaxial magnetoresistive sensor, and the angle difference between the gravity tool face angle and the magnetic tool face angle measured during static state can be compensated to the magnetic tool face angle by the drilling tool, thereby obtaining the gravity tool face angle capable of reflecting the wellbore azimuth information. The wellbore is divided into many sectors according to the 360° around the wellbore divided by the gravity tool face angle. The measured gamma and resistivity information in each sector is combined for real-time imaging of the stratum around the wellbore.
Fig. 4. Near-bit dynamic azimuth sector measuring principle
2 Near-Bit High Precision Gamma and Resistivity Imaging Circuit System 2.1 Gamma Resistivity Measuring Circuit System The gamma resistivity measuring circuit system is shown in (see Fig. 5). The gamma measuring circuit is composed of the follows: a natural gamma sensor, a gamma pulse signal conditioning unit, a pulse comparison shaping unit, a digital signal processing control unit, an underground real time clock unit, a gamma sensor high voltage power supply unit, a temperature coefficient compensation memory and other key components.
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Fig. 5. Gamma resistivity measuring circuit system
After stratum gamma rays near the gamma sensor are transmitted into the gamma sensor, they generate photoelectric effects to form a luminous flux with the NaI crystal inside the gamma sensor, the optical signal is converted into a weak charge pulse signal by the luminous flux through thephotomultiplier supplied by the high-voltage power source. The charge is amplified by the pulse signal conditioning circuit, thereby forming voltage pulse signals. The TTL level pulse with certain time width can be generated by the pulse signal through the pulse comparison shaping circuit. The pulse counting with fixed time interval is implemented on the pulse capture unit and the timer unit processed and controlled by the digital model. The content of radioactive elements in the measured stratum can be reflected by the count value within the unit time, thereby determining the formation of geological features. Resistivity measuring circuit is composed of the follows: upper and the lower transmitting coils, a transmitting coil excitation circuit, a transmitting coil monitoring circuit, a resistivity measurement button electrode, a front-end filtering differential amplifier, a program-controlled variable gain amplifier, a high-resolution AD collector, a DSP digital signal processor, a large capacity data storage unit, a 485 bus unit and other key parts. The Rogowski transmitting coils installed on both ends of the instrument drill collar is driven by the 900 Hz square-wave power voltage signal generated by the exciting circuit. Alternating current signals are generated on both ends of the insulating tape on the upper portion of the transmitting coils of the drill collar surface. The focusing effect is generated by the current signal under the alternating voltage action of the upper and the lower transmitting coils with the same size and opposite directions, therefore the alternating current can flow into the stratum more deeply, and then they can return to the resistivity measurement button electrode. The alternating current signal flowing into the button electrode is changed into the alternating voltage signal through the transformer installed in the instrument. The front-end filtering differential amplifier is used for filtering and amplifying the alternating votlage signals, which is further amplified through
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the program-controlled variable gain amplifier. Finally, the DSP digital signal processor is used for controlling the high resolution AD collector for alternating voltage signal acquisition. The voltage signal is changed into a digital signal, which is calculated by the digital synchronous detection processing program, finally obtaining the digital signal capable of reflecting the stratum resistivity change. The signal undergoes inversion calculation through the mathematical formula calibrated on the ground, thereby obtaining the measured stratum resistivity value. The gamma value and resistivity value measured by the gamma and resistivity measuring circuit are saved into the underground large capacity data storage unit through the digital signal processor, which can be transmitted to the wireless data transmission system across the screw motor through the 485 bus according to the program instruction requirements and then to the ground survey data interpretation system through the MWD drilling fluid pulse information transmission system, thereby providing important basis for geosteering projects in adjustment of borehole trajectory construction operation. 2.2 Measuring Circuit System for Dynamic Azimuth Imaging Sector The dynamic azimuth sector measurement is shown as follows: the instrument gravity tool face angle is accurately measured under the strong vibration working environment by using the triaxial accelerometer and the triaxial magnetoresistive sensor mainly. The measuring principle and circuit structure are shown in (see Fig. 6). The measuring circuit system of the dynamic azimuth sector is composed of the follows: triaxial accelerometer, triaxial magnetoresistive sensor, multi-channel signal amplification filter, multi-channel synchronous AD acquisition converter and digital signal processing controller.
Fig. 6. Dynamic azimuth sector measurement principle and circuit structure
The positions of the gamma sensor and resistivity button electrode on the instrument drill collar and the Z axis component of triaxial accelerometer are located in the same straight line. The straight line position is called gravity high side when the Z axis component is superposed with the earth gravity field. The included angle between the accelerometer Z axis and gravity high side is called the gravity tool face angle when the
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instrument is rotated. The gravity tool face angle reflecting the azimuthal imaging sector is solved by the following steps: the analog signals output by the triaxial accelerometer and triaxial magnetoresistive sensor are firstly synchronously sampled, and they are converted into corresponding digital signals. Then, the imaging sector is calculated through the firmware algorithm procedures of the digital signal processor. The calculation process is shown as follows: the magnetic tool face angle, the geomagnetic inclination, the magnetic azimuth and the hole drift angle are respectively calculated according to three components of the triaxial accelerometer and triaxial magnetoresistive sensor, while the gravity tool face angle can not be calculated directly and accurately according to the measurement components of the triaxial accelerometer due to underground instrument vibration and rotation interference. The angle difference between the gravity tool face angle and magnetic tool face angle is obtained according to the geomagnetic inclination, magnetic azimuth and the hole drift angle, thereby finally obtaining the gravity tool face angle according to the magnetic tool face angle and the angle difference as shown in formulas (2-1) to (2-8). hx , hy and hz refer to projection components of the earth magnetic field H on the x, y and z axes of the triaxial magnetoresistive sensor. gx , gy and gz refer to the projection components of earth gravity G on the x, y and z axes of the triaxial accelerometer. hy the θm = arctan (2-1) hz Magnetic tool face: hx gx + hy gy + hz gz the Dm = arcsin (2-2) h2x + h2y + h2z × gx2 + gy2 + gz2 Geomagnetic inclination:
hz gy − hy gz × gx2 + gy2 + gz2 the Am = arctan hx gy2 + gz2 − hy gy gx − hz gx gz
(2-3)
Magnetic azinuth: gx thel lg = arccos gx2 + gy2 + gz2
(2-4)
S = cos( the Dm ) × sin( the Am )
(2-5)
Hole drift angle: C = cos thel g × cos( the Dm ) × cos( the m ) − sin thel g × sin( the Dm )
(2-6)
The angle difference between the gravity tool face and the magnetic tool face theGM = arctan(S/C)
(2-7)
the θg = the θm − theGM
(2-8)
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2.3 Wireless Data Short Transmission System Across Screw Motor The screw motor is always in a high-speed rotation state driven by the drilling fluid because the rock breaking power for rotary drilling is supplied by the screw motor in the drill string assembly. Therefore, the stratum information measured near the bit can not be transmitted to the MWD drilling fluid pulse information transmission system above the screw motor by the near-bit high precision gamma and resistivity imaging instrument through wired connection [10], and the information can not be transmitted to the ground by MWD. However, the problem can be solved by the wireless data short transmission system across the screw motor through wireless data transmission. Alternating current is adopted to form a data information transmission channel in the instrument drill collar, the conductive drilling fluid and the stratum according to the conventional wireless data short transmission system across the screw motor, thereby realizing wireless transmission of stratum resistivity and gamma information measured by the near-bit system across the screw motor. However, drilling fluid is required as the conducting medium in the transmission channel. However, non-conductive oil-based drilling fluid is used during exploration and development of shale gas and shale oil, thereby blocking the conventional current wireless data short transmission system across the screw motor. The wireless data short transmission system across the screw motor based on the electromagnetic wave transmission mode is developed for data transmission in conductive and non-conductive drilling fluids. The shortcomings in the conventional wireless data short transmission system are overcome, thereby expanding the application scope of the system. The wireless data short transmission system across the screw motor based on the electromagnetic wave transmission mode is shown in (see Fig. 7). The system is composed of the follows: a wireless short transmission sending tool short section, a receiving tool short section and an electromagnetic wave sending-receiving antenna system. The wireless short transmission sending tool short section across the screw motor controls the signal generator circuit to produce 2FSK modulation coded signals through
Fig. 7. Wireless data short transmission system across screw motor based on electromagnetic wave transmitting
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the digital signal processor installed in the tool. The signals are sent to the stratum through H bridge amplifier circuit and electromagnetic wave sending tuning coil antenna. The receiving tool short section above the screw motor 12m away from the sending antenna receives the modulated electromagnetic wave signals through the receiving tuning coil antenna. The signals undergo multistage amplifier filtering, which are collected and converted into digital signals through the digital signal processor, and noncoherent digital demodulation is conducted, thereby obtaining the stratum resistivity and gamma measurement information transmitted by the near-bit sending short section in a wireless mode. High frequency electromagnetic wave signals are attenuated seriously in low resistivity stratum due to large range of stratum resistivity change. Therefore, the electromagnetic wave signals at two frequency points of 900 Hz and 1.2 kHz are adopted in the electromagnetic wave wireless short transmission system across the screw motor as the carriers for gamma resistivity measurement data transmission. 2FSK coding modulation mode and noncoherent demodulation method are adopted as shown in (see Fig. 8). 900 Hz electromagnetic waves are used to represent digital bit 0 and 1.2 KHZ electromagnetic waves are used to represent digital bit 1 to encode and modulate the tobe-transmitted measurement data according to 2FSK coding modulation mode, while the received and sampled 2FSK modulation signals are respectively filtered respectively through the digital bandpass filters with passband of 900 Hz and 1.2 kHz firstly according to the wireless short transmission receiving digital incoherent demodulation system. Detection treatment is respectively implemented through the digital detector. Finally, the data information transmitted by the electromagnetic wave sending system are judged and demodulated through digital low-pass filter and digital sampling.
Fig. 8. Wireless data short transmission noncoherent demodulation across screw motor
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3 Field Test of Near-Bit High Precision Imaging Measuring Tool While Drilling The 2-well field test of the near-bit high precision imaging measuring tools while drilling in Jilin Oilfield is shown in (see Fig. 9). The total penetration time of the instrument is longer than 318 h, and the penetration pure drilling time is 196.7 h. The MWD drilling information transmission system is applied to transmit the top sector and bottom sector data measured by the near-bit gamma imaging measurement system while drilling into
Fig. 9. Field test of near-bit high precision imaging measuring tool while drilling
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the ground survey data interpretation system software in real time in the field test. The position of the drilling bit in the reservoirs can be monitored in real time through data interpretation, thereby adjusting the drilling direction timely on the ground, and ensuring the penetration of borehole track gauge in reservoirs. The data measured by the nearbit gamma imaging measurement system while drilling is analyzed. It can be judged that the drilling bit is approaching to the upper boundary or the lower boundary of oil and gas reservoirs when the top sector gamma value or the bottom sector gamma value are increasing continuously. It can be judged that the drilling bit is penetrated in the middle position of the oil and gas reservoirs when the top sector gamma value or the bottom sector gamma value are similar or equal. Therefore, the near-bit high precision imaging measuring tool while drilling not only can be used for determining whether the borehole trajectory deviates from the reservoirs or not, but also can be used for judging the outgoing direction according to the sector azimuth information. Field engineers determine the outgoing direction according to the gamma imaging information, thereby making correct callback measures.
4 Conclusion The stratum dip angle, fault, fracture and other geological structure information along the trajectory direction can be extracted timely from high-resolution resistivity 和 gamma measurement data of the near-bit high precision imaging measuring tool while drilling. The drilling stratum local tectonic fluctuations, reservoir thickness changes and physical property changes can be directly reflected through the wellbore imaging function. The positions of the tectonic characteristics and trajectory in the reservoirs can be judged accurately during drilling and development of low-permeability oil and gas reservoirs, shale gas reservoirs, tight gas reservoirs as well as other unconventional oil and gas reservoirs.
References 1. Zhang, X., Wang, J., Guo, Y.: Progress and development trend of well logging technology while drilling. Well Log. Technol. 30(1), 10–15 (2006) 2. Yang, S., Lei, X., Cai, J., et al.: Comprehensive application of resistivity image logging while drilling in Beibu Gulf carbonate reservoirs. Log. Technol. 34(2), 177–182 (2010) 3. Sun, R.: Application of near-bit geosteering system in thin oil reservoir horizontal well. J. Changjiang Univ. (Nature) (5), 102–105 (2013) 4. He, Q.: Application of near-bit geosteering drilling technology in Zhang 3_2HF wells. Oil Gas Eval. Dev. (6), 50–53 (2013) 5. Kang, Z., et al.: Research on detection characteristics of drilling bit resistivity logging instrument. Bull. Pet. Sci. (04), 457–465 (2017) 6. Tang, H.: Imaging processing method of azimuth gamma data while drilling. Lithological Oil Gas Res. (01), 110–115 (2017) 7. Li, M., Ke, S., Kang, Z., Li, X., Ni, W.: Influencing factors and response characteristics of measurement strength of torus excitation lateral logger while drilling. Oil Drill. Technol. (01), 128–134 (2018)
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8. Li, A., Li, Q., Zhu, J., et al.: Investigation characteristic numerical simulation analysis of azimuth lateral resistivity imaging logger while drilling. Log. Technol. 38(4), 407–410 (2014) 9. Yang, Z., Yang, Z., Fan, C., Wang, G., Ren, W.: Development of near-bit electromagnetic wave resistivity logging instrument. J. Daqing Pet. Inst. (06), 87–90 (2010) 10. Duan, Y., Zhang, L., Chen, J., Wang, H., Ding, Z.: Research on near-bit measurement instrument based on electrical signal transmission data. China Pet. Mach. (02), 41–44 (2017)
Research on Relative Permeability of Shale Oil Reservoir in Jimsar Area Using Digital Cores Shen-gen Chen(B) , Yuan-kai Xiang, Lei-ming Cheng, and Jun-xiu Ma Research Institute of Engineering and Technology, Xinjiang Oilfield Company, PetroChina, Karamay, China [email protected]
Abstract. Clarifying the laws of relative permeability of Jimsar shale reservoir holds the most promising potential in the optimization of fracturing design. There is, however, as an unconventional tight reservoir, the shale oil reservoir in Jimsar area has ultra-low porosity and permeability, which leads the difficulty to clarify its seepage characteristics with conventional physical model experiments. Therefore, in this work, constructing the digital cores of Jimsar shale characteristic reservoir, and forming three-dimensional pore network model of the upper and lower sweet spots. Afterward, under the formation condition, the digital cores displacement simulation was carried out, and the complete relative permeability characteristics were obtained. Furthermore, the wettability physical model test was carried out to investigate its effect for relative permeability. Combining with the analysis results of the microscopic pore throat structure of the digital cores, the law of Jimsar shale relative permeability is clarified. The results show that the digital cores can finely describe the difference between the upper and the lower sweet pots in pore throat structure. The upper sweet spot has a larger pore size (about 3 times, compared with the lower sweet pot), but its connectivity is less difference (the coordination number is about 13% lower than the lower sweet pot). The displacement simulation demonstrate that the upper sweet spot has a higher irreducible water saturation (about 36%) and a higher residual oil saturation (about 34%), indicating that the lower sweet spot fluid has stronger fluidity. After wettability analysis, the upper sweet spot is weakly water-wet (Wetting angle 40–80°), the lower sweet spot is weakly oil-wet (wetting angle 100–130°), which had a significant impact Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 14–26, 2023. https://doi.org/10.1007/978-981-99-2649-7_2
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on the relative permeability. Combining with the pore structure characteristics of the upper and lower sweet spots, it shows that the water-wet shale reservoir with a relatively high pore size has an adversely affect in fluid flow. Furthermore, we can get a clear understanding of the relative permeability characteristics in the upper and lower sweet spots of the Jimsar characteristic shale reservoirs by combining the digital cores, and which will helpful for forming a targeted strategy in reservoir reconstruction designs. The results of this research have certain reference significance for the stimulation and reconstruction of tight reservoirs such as the shale oil. Keywords: Jimsar Shale · Digital cores · Relative permeability · Pore structure · Wettability
1 Introduction As the rising of the demand for oil and gas resources, unconventional oil and gas reservoirs such as shale oil have gradually become the key of petroleum exploration and development in the world, and effective development will greatly alleviate the contradiction between the world’s energy supply and demand [1–4]. Statistics show that the world’s recoverable shale oil resources amount to 277 billion tons, and China’s recoverable shale oil reserves exceed 10 billion tons, ranking third in the world, second only to the United States and Russia, and widely distributed in the Junggar, Ordos, and Sichuan basins [5–7]. The Jimsar shale oil resource in the Junggar Basin is 15.8 × 108t, which has great development potential. Due to its ultra-low permeability and porosity, it is non-productive capacity under natural conditions [8–10]. Drawing on the successful development experience of shale oil in North America, commercial development of shale oil is mainly carried out by multistage hydraulic fracturing of long horizontal wells at present [11–13]. However, the Jimsar shale oil is a continental reservoir with diverse lithology, thin single layer, and difficult to reform, which is quite different from the North American marine shale oil layer. What’s worse is that even for North America shale oil, its initial recovery rate is only 5–10%, resulted in the difficult to form an efficient development by completely copying the development strategies of the North America [14–16]. Therefore, in view of the difficulties in the reconstruction of Jimsar shale oil reservoirs, it is necessary to deepen the core analysis of shale oil reservoirs, such as the micro pore-throat structure and its relative permeability rules, which will guide fracturing reforms. In recent years, with the development of complex oil and gas reservoirs, traditional core analysis techniques have increasingly shown certain limitations in core analysis of shale oil reservoirs. The core of the Jimsar shale oil reservoir is affected by the development of weak plane structures, such as lamellation and natural micro-fractures. The samples breakage rate of physical model test is high, so the repeating utilization factor of those cores is low. Meanwhile, the shale is mainly composed of micro-nanoscale non-organic inter-granular pores and nano-scale organic intra-granular pores, with a permeability level of 0.01mD. The complex nano-scale pore-throat system accounts for a huge proportion in the formation, so nano-scale pore-throat plays a dominant role in the
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porosity and permeability, resulting in a low success rate of core flooding experiments and the difficulty in charactering the relative permeability [17–22]. Digital core analysis technology has the advantages of accurate prediction, rapid analysis, repeatable testing, etc. It can obtain unconventional reservoir cores experimental data that is difficult to measure the laboratory, and assists traditional laboratory analytical techniques to provide more comprehensive and systematic analytical testing during the reservoir description [23]. Scholars have used CT and SEM scanning imaging to construct digital cores in different media, exploring the multi-scale pore structure and shale oil flow capacity in shale oil reservoirs. What’s more, based on the digital cores, they can effectively establish the three-dimensional pore structure of shale oil reservoirs for simulating the relative permeability of shale oil [24–27]. Therefore, on the basis of the original CT scanning technology, this paper obtains the digital scanning images of the characteristic full-diameter core samples’ microscopic pore-throat structure from the Jimsar shale oil reservoir by using micro-nanometer CT scanning strategy. Then, constructing multi-scale digital cores by using visualizing threedimensional (3D) images of the characteristic samples’ pore-throat structure, which will become the basis for extracting and forming corresponding three-dimensional porethroat network model. In the pore-throat network model, we can identify the structure of full-diameter cores and carry out digital core displacement simulate to obtain its complete relative permeability under in-situ condition. Furthermore, we can explore the fluid flow mechanism of shale oil reservoirs and clarify its relative permeability rules by analyzing samples’ wettability and the results of digital core micro pore-throat structure, which may prove the potential for optimize the fracturing technology in Jimsar shale oil reservoirs and similar formations.
2 Experimental Method 2.1 Experimental Materials The materials used in the experiment were the full-diameter cores of the upper and lower sweet spots of Well M in the Jimsar shale oil reservoir, and 12 rock samples were respectively extracted from the upper and lower sweet spots (Table 1), of which No. 1–6 come from the upper sweet spot, No. 7-12 come from the lower sweet spot. 2.2 Digital Core Acquisition Based on the top and bottom sweet spot samples of Jimsar shale oil, the core images of different resolutions were obtained through micro-nano CT scanning (Fig. 1). After reconstructing the scanned image, a three-dimensional grayscale image of the Jimsar shale micro-sample is obtained. Because the gray value of the CT image reflects the relative density of the material inside the rock, the bright part of the CT image is considered to be high-density material, and the dark part is considered to be the pore-throat structure. The segmented image of the pore-throat structure is extracted by performing region selection and noise reduction processing on the gray image (Fig. 2).
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Table 1. Micro-nano CT scan test rock samples. Serial number Core number Layer Sampling depth (m) Porosity (∅) Sweet spot area 1
5–16sp1
P2 l 2
3484.66
8.71
2
5–17sp1
P2 l 2
3484.83
11.22
3
5–25sp1
P2 l 2
3485.85
6.9
4
5–37sp1
P2 l 2
3487.97
6.5
5
6–11sp1
P2 l 2
3490.46
9.87
6
9–8sp1
P2 l 2
3512.47
6.56
7
10–13sp1
P2 l 1
3612.87
9.39
8
10–13sp2
P2 l 1
3612.96
9.51
9
10–21sp1
P2 l 1
3614.32
8.76
10
11–28sp1
P2 l 1
3625.31
8.58
11
11–30sp1
P2 l 1
3625.56
10.91
12
12–22sp1
P2 l 1
3631.96
7.57
Upper sweet spot
Lower sweet spot
Fig. 1. Micro-nano CT scan a: micron-level scan, b: nano-level scan
2.3 Construction of 3D Pore Network Model In order to describe the connectivity of the pore space and the spatial distribution inside the core, the pore space in the Jimsar digital core is accurately divided into the space occupied by the pores and throat units, and the erosion-expansion method is used to extract the pore network model. As shown in Fig. 3, it mainly includes the erosion of core pore space, the expansion of core pores and the characterization of pore throat units. During the construction of the pore network model, the shape of the real pores and throats in the pore space of Jimsar Shale is very complicated. In order to facilitate the simulation of the flow of multiphase fluid in the pore network model, the crosssectional shape of the pore-throat simplify into circles, squares and arbitrary triangles, and characterizes the pore-throat network by using column-shaped units with crosssectional shapes of circles, squares and arbitrary triangles. Analyzing the statistical
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Fig. 2. Digital core
Fig. 3. Process of extracting pore network model by erosion-expansion method
geometric topological structure parameters of the regular units, which will useful for evaluating the pore network structure in detail. 2.4 Simulation of Relative Permeability Previously, the pseudo-static flow simulation model was widely used to simulate the seepage flow of the 3D pore network. The quasi-static model assumes that the flow is completely controlled by capillary force, and the pressure drop caused by the viscous force in the model is negligible compared with the capillary pressure. Meanwhile, this model assumes that the fluid is an incompressible Newtonian fluid, and the multiphase fluid is immiscible. In addition, according to the intrusion-percolation theory, the flow fluid from one pore to another is instantaneous, and regardless of the flow process in the pore throat. Based on the basic physical property parameters of Jimusaer’s upper and lower sweet spots (Table 2), the basic process of oil-water two-phase flow simulation in the 3D pore network of rock sample is as follows: First, the 3D pore network model is saturated with water, so the model has strong affinity for water. Then, simulating the process of forming oil reservoir (oil displacing water as a sucking process) until the irreducible water saturation is reached, and the oil flooding process will cause the wettability of the network model to change. Finally, the water flooding simulation is performed, which is similar with the oilfield development process. Aa a result, the relative permeability curve of oil-water displacement and the relative permeability curve of sucking can be calculated in the process of oil flooding and water flooding.
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Table 2. Basic physical parameters of top and bottom desserts. layer
Upper sweet pot of M well
lower sweet pot of M well
Oil-water surface tension
30 mN/m
30 mN/m
Density of water
1030 kg/m3
1030 kg/m3
Oil density
850 kg/m3
850 kg/m3
Water viscosity
0.888 mPa · s
0.888 mPa · s
Oil viscosity
8.946 mPa · s
8.946 mPa · s
Wetting angle distribution
40–80°
100–130°
3 Results and Discussion 3.1 Experimental Materials As shown in Fig. 4, this is the pore radius distribution of upper and lower sweet spot’ core samples of Jimsar shale oil by analyzing the statistical data of characteristic 3D pore network model. The left picture of Fig. 4 shows the pore radius distribution of the upper sweet spot with an average value of about 1.5 µm, and the right picture of Fig. 4 shows the pore radius distribution of the lower sweet spot with an average value of about 0.75 µm. Therefore, the pore radius distribution of the upper core samples is about twice that of the lower characteristic samples.
Fig. 4. Process of extracting pore network model by erosion-expansion method
Figure 5 is the throat radius distribution of upper and lower sweet spot. We can see from the left picture is that the upper sweet spot throat radius distribution with an average value of about 0.6 µm, while the right picture shows the lower sweet spot throat radius distribution with an average value of about 0.30 µm. The results also show that the throat radius distribution of the upper sweet spot is about twice that of the lower sweet spot. Giving both the pore-radius and throat-radius of the 3D network model an overall consideration, Fig. 6 shows the different distribution frequency between the upper sweet spot and lower sweet spot in pore-throat radius. The results find the pore-throat radius (average value of about 1.8 µm) of upper samples is nearly 3 times that of the bottom sweet spot (average value of about 0.60 µm).
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Fig. 5. The distribution of the upper and lower sweet spot throat radius
Fig. 6. Distribution of the pore throat radius of the upper and lower sweet spot
Coordination number plays an important role in the core connectivity. As shown in Fig. 7, the left picture shows the distribution frequency of the upper samples’ coordination number (with a mean value of approximately 2.84 to 3.02), the right picture shows the distribution frequency of the lower samples’ coordination number (with a mean value of approximately 3.14 to 3.38). According to the statistical data of the coordination number, the coordination number of lower sweet spot is about 13% higher than the upper sweet spot, which indicates that there is no significant difference in coordination number of the upper and lower core samples.
Fig. 7. Distribution of upper and lower dessert coordination numbers
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Through the comparison of the microstructure characteristics (pore radius, throat radius, pore-throat radius and coordination number) between the upper and lower sweet spot in Jimsar shale oil, it can be found that the upper samples have a larger pore-throat size than the lower samples, but its connectivity no a significant difference. 3.2 The Results of Relative Permeability As shown in Fig. 8, a three-dimensional (3D) pore network structure is constructed based on the upper sweet spot digital core from well M in Jimsar, the forming process of reservoir (Fig. 8a to Fig. 8b) and the water flooding process (Fig. 8c to Fig. 8f) are simulated based on the oil-water two phases. And in the whole process, the permeability characteristics of different periods are counted, the data is collected and sorted, and the oil-water phase permeability curve during the accumulation and displacement process of the upper sweet spot is drawn (Fig. 9).
Fig. 8. Forming reservior and water flooding process of upper sweet spot
As shown in Fig. 8, through drawing the oil-water two-phase relative permeability curve of the upper sweet spot in forming reservoir and displacement process, it can be seen that the upper sweet spot irreducible water saturation is 0.29–0.35, and its residual oil saturation is 0.33–0.42. Furthermore, the results also identify that the ideal recovery is about 44.5% in upper sweet spot by analyzing the irreducible water saturation and the residual oil saturation. Figure 10 shows the process of oil accumulation (Fig. 10a to Fig. 10b) and water flooding (Fig. 10c to Fig. 10f) with the 3D digital pore network model of the lower sweet spot from well M in Jimsar. The way of analyzing relative permeability is similar with the upper sweet spot, and the oil-water relative permeability curve during the forming reservoir and displacement of the lower sweet spot is drawn (Fig. 11).
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Fig. 9. The relative permeability curve of the upper sweet spot reservoir formation and displacement process
Fig. 10. The accumulation and water flooding process of lower sweets
As shown in Fig. 11, it can be seen that the irreducible water saturation is 0.19–0.28 and its residual oil saturation is 0.23–0.33 in lower sweet spot. Meanwhile, similar to the analysis method of the upper sweet spot, it can be seen that the ideal water flooding recovery is about 63.4% in lower sweet spot.
Fig. 11. Correlation curve of reservoir formation and displacement process of lower sweets
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Comparing the upper and lower samples, it can be found that the upper reservoir has a higher Irreducible water saturation (about 36.2% higher than the lower spot). However, the upper reservoir also has higher residual oil saturation (about 34% higher than the lower spot), which indicates that the fluid has worse fluidity in the upper sweet spot compared with the lower sweet spot (the reason why the ideal recovery is 44.5% in upper spot while the lower spot is 63.4% after the water flooding). 3.3 Analysis of the Relative Permeability As shown in Table 1–2, the basic physical parameters of the upper and lower sweet spot are basically the same except for the wettability. Comparing the wetting angle between the upper sweet spot (40–80° , water wettability) and lower sweet spot (100–130° , oil wettability), it clearly indicate the wettability of upper and lower spot are quite different. At the same time, referring to the previous analysis results (Fig. 12)[28], the wettability tests of the top sweet spot are 40.2° , 75.1° , 63.1° , and the wettability tests of the bottom sweet spot are 132.2° , 101.9° , 118.2° , respectively. Wettability not only influences sweep efficiency, but also influences remaining oil distribution. Those results indicating that the difference in wettability between upper and lower spot is universal.
Fig. 12. Results of wettability test of Jimsar shale oil reservoir, top sweet spot: a-c; bottom sweet spot: d-f
In addition, based on the same three-dimensional pore network structure and the same conditions of other basic physical parameters, the matrix wettability is adjusted to water wettability and oil wettability, respectively. Then, the water flooding is simulating
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in the model, and the results are shown in Fig. 13. It can be seen from Fig. 13 that there is still a large amount of visible residual oil in the water-wet sample (Fig. 13a) after completing the displacement. As a comparison, the oil-wet sample (Fig. 13b) is basically invisible residual oil in the large pore path after the water displacement. The wettability has a significant impact on the displacement, and the residual oil saturation under water-wet conditions is lower. Therefore, the analysis believes that the throats in the upper sweet spot with waterwet are easily occupied by water, so that the oil will be trapped in the large pores and jammed, and the overall residual oil saturation is higher. In the lower sweet spot with the oil-wet sample, the permeability of the water phase is low in the initial stage, which is conducive to the flow of the oil phase, and the overall residual oil saturation is low.
Fig. 13. (a) Simulation of water drive oil process in water-wet sample, (b) Simulation of water drive oil process in oil-wet sample.
4 Conclusion In this paper, based on the top and bottom sweet spot coring data of Jimsar characteristic well M, the digital core is constructed by micro-nano CT scanning. Its three-dimensional pore structure model is obtained from the digital core, and the flow simulation experiment is carried out in the model to explore the relative permeability difference and the reasons for the difference in the top and bottom sweet spots. The main conclusions are as follows: (1) The digital core can finely describe the difference in the pore-throat structure of the upper and lower sweet spot in the Jimsar well M. The average pore-throat radius of the upper dessert is 0.6–3 µm (about 3 times of the lower dessert), and the
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coordination number is 2.84–3.02 (approximately 13% lower than the lower spot). Indicating that the pore size of the upper spot is larger, but the connectivity is no significant difference between the two sweet spot. (2) Based on the displacement numerical simulation test, the seepage characteristics of the upper and lower sweet spots in the Jimsar M well are clarified. The upper sweet spot irreducible water saturation is 0.29–0.35 (about 36% higher than the lower sweet spot), and the upper sweet spot also has Higher residual oil saturation (0.33–0.42, about 34% higher than the lower sweet spot), indicating that the lower sweet spot fluid has stronger fluidity and better displacement effect. (3) The wettability of the upper and lower spots has a significant difference. The upper spot is water-wet (the wetting angle is 40– 80°), and the lower spot is oil-wet (the wetting angle is 100– 130°). Due to the influence of wettability, the throat of the upper spot is are easily occupied by water during the water flooding, and the oil is trapped in the large pores, resulting in oil jamming and the high residual oil.
References 1. Jia, C.: On the breakthrough and significance of unconventional oil and gas to classical oil and gas geology theory. Pet. Explor. Dev. 44(1), 1–11 (2017) 2. Wei, B., Zhang, X., et al.: Progress and enlightenment of field test for enhanced oil recovery in tight oil reservoirs. Xinjiang Pet. Geol. 42(2), 495–505 (2021) 3. Jia, J., Liu, Z.: Particle-size fractionation and thermal variation of oil shales in the songliao basin, NE China: implication for hydrocarbon-generated process. Energies 14(21), 191–197 (2021) 4. Zhao, P., Fan, X., et al.: Characteristics of hydration damage and its influence on permeability of lamellar shale oil reservoirs in ordos basin. Geofluids 14(21), 1–15 (2021) 5. Li, Y., He, T., et al.: Technology and prospects for enhanced oil recovery in shale reservoirs. J. Southwest Pet. Univ. (Nat. Sci. Ed.) 43(3), 101–110 (2021) 6. Li, G., Liu, G., et al.: Favorable facies optimization and fracturing parameter optimization method for continental shale oil. Acta Petrolei Sinica 42(11), 1405–1416 (2021) 7. Xia, D., Yang, Z., et al.: Characteristics of micro- and nano-pores in shale oil reservoirs. Pet. Explor. Prod. Technol. 11, 157–169 (2021) 8. Wu, C., Xu, C., Chen, Y., et al.: Development practice of Jimsar shale oil horizontal well. J. Southwest Pet. Univ. (Nat. Sci. Ed.) 43(5), 33–41 (2021) 9. Xia, Y., Zhang, L., Chu, H., Li, J., Ma, S.: “Low-cost sweet spot” technology for Jimsar shale oil. Oil Gas Res. Eval. Dev. 11(04), 536–541 (2021) 10. Li, J., Wu, J., Xie, S., et al.: Integrity failure characteristics and control methods of Jimsar shale oil wellbore. Xinjiang Oil Gas 17(3), 37–43 (2021) 11. Zhang, S., Li, S., Zou, Y., et al.: Multi-stage fracturing fracture height propagation test for horizontal shale oil wells. J. China Univ. Pet. (Ed. Nat. Sci.) 45(01), 77–86 (2021) 12. Lu, Y., Zeng, L., Xie, Q., Jin, Y., Hossain, M., Saeedi, A.: Analytical modelling of wettability alteration-induced micro-fractures during hydraulic fracturing in tight oil reservoirs. Fuel 249, 434–440 (2019) 13. Peng, H., Ran, Q., Li, Y., Tong, M.: Performance analysis and flow regime identification of fractured horizontal wells in tight oil reservoirs. In: Paper SPE-188071 presented at SPE Kingdom of Saudi Arabia annual technical symposium and exhibition, Dammam, Saudi Arabia (2017)
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14. Sheng, J.J., Herd, B.L.: Critical review of field EOR projects in shale and tight reservoirs. J. Pet. Sci. Eng. 159, 654–665 (2017) 15. Liu, X., An, F., Chen, Q., Qin, J.: Analyses of the EOR techniques for tight oil reservoirs: taking Bakken formation as an example. Pet. Geol. Oil Dev. 35(6), 164–169 (2017) 16. Sun, R., Pu, H., Yu, W., Miao, J., Zhao, J.: Simulation-based enhanced oil recovery predictions from wettability alteration in the Middle Bakken tight reservoir with hydraulic fractures. Fuel 253, 229–237 (2019) 17. Li, J., Deng, S., Kannizati, et al.: Development characteristics and accumulation conditions of shale oil reservoirs in Lucaogou Formation in Jimsar Depression. World Geol. 40(4), 881888 (2021) 18. Wang, J., Zhou, L., Liu, J., et al.: Influencing factors of hydrocarbon fluidity of sweet spots in the Lucaogou Formation shale strata in the Jimsar Sag, Junggar Basin. Nat. Gas Geosci. (2021) 19. Wang, J., Zhou, L., Jin, J., et al.: Pore structure, hydrocarbon occurrence and their relationship with mobility in Lucaogou Formation shale oil reservoir in Jimsar Sag, Junggar Basin. Pet. Geol. Exp. 43(06), 941–948 (2021) 20. Zou, C., Yang, Z., Cui, J., et al.: Formation mechanism, geological characteristics and development strategy of nonmarine shale oil in China. Pet. Explor. Dev. 40(1), 14–26 (2013) 21. Yuan, Y., Zhao, J., Er, C., et al.: Study on types and features of the pore in Mesozoic and Upper Palaeozoic shales in Ordos Basin. J. Xi’an Shiyou Univ. (Nat. Sci. Ed.) 29(2), 14–19 (2014) 22. Cao, T., Song, Z., Wang, S., et al.: A comparative study of the specific surface area and pore structure of different shales and their kerogens. Sci. China Earth Sci. 58(4), 510–522 (2015) 23. Ma, T., Chen, P.: Study of meso-damage characteristics of shale hydration based on CT scanning technology. Pet. Explor. Dev. 41(2), 249–256 (2014) 24. Song, W., Liu, L., Sun, H., et al.: Study on the pore structure characterization and flow capability of shale oil reservoir based on digital core. Oil Gas Res. Eval. Dev. 11(04), 497–505 (2021) 25. Dong, H., Yang, J., Wu, G., et al.: The microstructure characteristics and main controlling factors of continental shale oil based on digital core technology: Taking the shale of the first member of Qingshankou Formation of Cretaceous in Songliao Basin as an example. Geol. Res. 30(03), 377–384 (2021) 26. Wang, J., Zhou, Z., Wei, H., Cui, C.: Oil-water two-phase flow simulation based on shale pore network model. Lithol. Res. 33(05), 148–154 (2021) 27. Li, J., Chen, B., Kong, M., et al.: Digital core reconstruction and micro-scale seepage characteristics of shale oil reservoirs: taking shale oil from Permian Lucaogou Formation in Jimsar Depression as an example. Xinjiang Pet. Geol. 40(03), 319–327 (2019) 28. Ma, M., Zhu, J., Li, J., et al.: Imbibition law of shale oil reservoir of Lucaogou Formation in Jimsar Depression. Xinjiang Pet. Geol. 42(06), 702–708 (2021)
Feasibility Study on Collaborative Development of Gas Storage and Enhanced Oil Recovery Xiao-chen Wang, Xin-wei Liao(B) , and Kang Tang Department of Petroleum Engineering, China University of Petroleum (Beijing), Beijing, China [email protected], [email protected]
Abstract. Underground gas storage (UGS) is an effective way to alleviate the shortage of natural gas supply and improve oil recovery. Ma 19 block is located in the west of Liaohe Oilfield. It is a gas cap and bottom water reservoir with a production history of more than 48 years since 1973. In the later stage of production, oil production and gas production are extremely low, water content reaches more than 95%, and the benefit is very poor. The block is currently being studied for co-development of enhanced oil recovery in the UGS process. The component model was established by numerical simulation software, PVTI fitting and historical fitting were carried out, and the parameters of each phase in the next 15 years were predicted for the three operating pressure intervals of the underground gas storage and the original water injection recovery plan. It was found that Ma19 block is suitable for the collaborative construction scheme of UGS to enhance oil recovery. The results show 12–26 MPa is the optimal working pressure range of UGS. Compared with the original production scheme, the crude oil production is increased by 13 times and the oil recovery factor is increased by 4.65% . UGS has accumulated 99.7 × 108 m3 of gas injection, 13.83 × 104 m3 of oil production and 96.2 × 108 m3 of gas production in 15 years of operation. The peak load adjustment and supply capacity of natural gas exceeds 550 × 104 m3 /d.This paper puts forward the operation strategy of enhancing oil recovery during the operation of gas storage, which can greatly improve oil recovery, gas storage capacity. It provides a certain reference value for enhancing oil recovery through UGS operation in Ma 19 block.
Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information con-tained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been re-viewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial pur-poses without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 27–38, 2023. https://doi.org/10.1007/978-981-99-2649-7_3
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X. Wang et al. Keywords: Underground Gas Storage · Enhanced Oil Recovery · Numerical Simulation
1 Introduction With the gradual control of COVID-19, China’s economic development has recovered rapidly, and the demand for natural gas has grown rapidly, with an annual increase of 20 billion cubic meters, and the contradiction of seasonal peak adjustment has become increasingly severe [1–3]. Low-carbon economy and environmental protection have become the theme of today’s world development. To develop low-carbon economy, the first step is to build a stable, economic, clean and safe energy supply system. As a kind of efficient, clean and high-quality energy, natural gas causes far less pollution to the environment than oil and coal. It is the inevitable choice for developing low-carbon economy and realizing energy conservation and emission reduction in recent decades. China has also put forward the natural gas pipeline development goal of “reasonable distribution of natural gas pipelines and supporting facilities, basically forming the basic natural gas pipe network covering the whole country, and realizing the diversification of gas sources, network of pipelines, matching of gas storage, automation of management and unification of dispatching” [4–8]. The establishment of underground gas storage is the most effective and mature means of natural gas peak regulation and supply protection in the world. For countries with more than 50% external dependence on natural gas, according to foreign experience, the working gas of underground gas storage should account for about 15% of the national natural gas consumption, while China’s gas consumption is only 4.4%, only a quarter of that of developed countries. (Table 1) The peak load regulation and supply capacity of gas storage is very low, and there is a great development space and prospect [9–12]. At present, most of the domestic gas storage is reconstructed from depleted oil and gas reservoirs, and there is still a huge potential for enhancing oil recovery during the operation of the gas storage. The combination of enhanced oil recovery and gas storage can shorten the construction period of gas storage and reduce the construction cost. Ensure natural gas imports to meet seasonal demand and prevent supply shortages. Through the establishment of collaborative gas storage, gas injection in spring, summer and autumn, and gas recovery in winter can give full play to the oil displacement mechanism of pulse imbibition, improve oil recovery, and realize the benefits of both reservoir construction and oil displacement [13–15]. The collaborative construction of gas storage and oilfield development can be divided into two categories: one is based on oilfield development and the other on gas storage. The main task of Coordinated construction based on oilfield development is to greatly improve oil recovery by injecting natural gas into the top of reservoir. Through the evaluation of remaining oil distribution and optimization and adjustment of injectionproduction parameters, the formation pressure is kept above the minimum miscible pressure for natural gas injection, so as to ensure miscible state to improve oil displacement efficiency and oil recovery. The pressure operating interval of this scheme is narrow, and it is necessary to control reasonable injection-production speed to prevent gas channeling. The main task of Coordinated construction based on gas storage is gas injection
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29
Table 1. China and major developed countries gas storage construction statistical table. Countries
Annual consumption /108 m3
China
3316
27
147
4.40%
America
7786
393
1360
17.50%
Russia
3909
23
718
18.40%
Canada
999
66
265
26.50%
Germany
805
49
238
29.60%
Italy
645
12
173
26.80%
Sum/a
Annual peak regulation capacity /108 m3
Proportion
and gas recovery and peak regulation and supply protection. After the stable operation of the gas storage is achieved by expanding the capacity of the gas storage, the upper and lower working pressures should be reasonably determined to gradually improve the working gas capacity of the gas storage. Based on the understanding of geological conditions and surface conditions, natural gas should be injected as soon as possible to reduce the number of injection-production Wells, reduce operating costs, avoid edge and bottom water intrusion as much as possible, and improve oil displacement and reservoir construction benefits [16, 17]. The production and operation model of the gas storage is that the natural gas received by the external pipeline system is injected into the gas storage layer by compressors. According to the market demand, the gas is injected in summer and extracted in winter, and the natural gas is extracted from the gas storage layer and transported to the external pipeline network during the peak gas consumption period. In addition, there are three basic requirements for underground gas storage: one is to ensure that the reservoir has a certain good sealing, to prevent the injection of natural gas loss; Second, the reservoir must have certain permeability so that the high-pressure gas can enter the reservoir smoothly. The third is in the gas production stage can be successful gas production, ensure a certain gas production capacity, and must have emergency peak adjustment ability. Based on the in-depth study of Ma 19 block, it is found that the minimum miscibility pressure in this block is high, and it is not easy to produce miscibility by injecting natural gas. Therefore, the coordinated construction based on displacement of reservoir oil is not suitable for this block. This block is suitable for the coordinated construction based on gas storage, which basically maintains the medium pressure scale gas injection, and generally maintains the operation mode of massive gas injection and massive gas extraction. To sum up, in view of the importance of peak regulation of Qinshen Pipeline, ChinaRussia pipeline and Da Shen pipeline and the favorable conditions of underground gas storage in Liaohe oilfield area, it is necessary to build Ma19 gas storage in order to ensure the safe operation of long-distance pipeline and the long-term planning of national strategic energy reserve.
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X. Wang et al.
2 Reservoir Characteristics and Production History Ma 19 block is located in the south of The Xinglongtai fault anticline structural belt in the western depression of Liaohe Oilfield. The block is mainly developed in Dongying Formation, with an oil-bearing area of 10.33 km2 and oil geological reserves of 763 × 104 t. It has been more than 40 years since the development of The Ma 19 block in 1973 [18–27]. After more than 47 years of water-flooding, the reservoir is in the late stage of development and has a complex fluid distribution in which oil, gas and water coexist. The original reservoir pressure in this block is 30.6 MPa, and the current reservoir pressure is 19.4 MPa (the pressure dropped to the lowest in 1986, and the production wells with too high water cut were shut down and the water injection wells continued to maintain pressure, and the pressure gradually recovered). As of July 2020, The Ma19 block has produced 200.4 × 104 m3 of crude oil, plus 20.09 × 108 m3 of gas cap gas and dissolved gas. It is important to note that the volume of expected working gas in the storage is of the same order of magnitude as the volume of produced gas. The recovery factor of oil and gas was 38.26% and 63.24%, respectively. Converting fields to UGS provides opportunities for enhanced oil recovery as gas circulation in the reservoir generates additional oil production. Figure 1 shows the production history of Block Ma 19 from 1973 to 2021.
Fig. 1. Production history of Block Ma 19
In 1973–2021: Oil and gas development with water injection in Block Ma 19. During the first 14 years of production, the formation pressure decreased rapidly from 306 bar to 112 bar. (Fig. 2) Crude oil production peaked in 1975 at 690 m3 /d.
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Fig. 2. Reservoir pressure history of Block Ma 19
3 Model Building and Scheme Design In order to improve the development effect of Ma19 block, enhance oil recovery and effectively develop existing remaining oil, the following four basic principles are followed: combining geology and surface, designing reasonable well location, matching reservoir reserves, determining reasonable well type, classifying and evaluating zones, optimizing reasonable well spacing, unifying the construction of reservoir, construction and production, and giving reasonable consideration to oil and gas. Six production wells and three injection and production wells were selected (Fig. 3). Based on the deep understanding of the geological characteristics of Ma19 block, tNavigator software is used to build the numerical simulation model of the reservoir, and the historical fitting of its production time is made. The model is modeled by component model, and the total number of grids is 83808.
Fig. 3. Reservoir numerical simulation model scheme.
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X. Wang et al. Table 2. The reservoir model
Rock properties
Fluid properties
Property/Parameter (units)
Value
Property/Parameter (units)
Value
Reservoir dimensions
97 × 48 × 18
Water saturation, Sw (%)
54
Grid size
35 × 35 × 13
Initial oil saturation (%)
46
Average Perm,K (µm2 )
200
Water density (kg/m3 )
1001
Porosity, (%)
0.05
Water viscosity (cp)
0.33
Perm.V/Perm.H,Kv/Kh
0.1
Oil specific gravity (kg/m3 )
593
Reservoir temperature, (°C)
100
Initial reservoir pressure (MPa)
40
Formation depth (m)
2800
Rock compressibility (1/bar)
0.0003
(a) Oil-water relative permeability curve; (b) Oil-gas relative permeability curve.
Fig. 4. (a) Oil-water relative permeability curve; (b) Oil-gas relative permeability curve.
Table 2 shows the parameters of Block Ma 19, Fig. 4 shows the oil-water relative permeability curve and oil-gas relative permeability curve, and Table 3 shows the parameters of component model.
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Table 3. Compositional reservoir parameters based on the reservoir system. Component
Molecular weight
Tc (K)
Acentric factor
Pc (bar)
CO2
44.01
304.7
0.225
73.8659
N2
28.01
126.2
0.04
33.9439
C1
16.04
190.6
0.013
46.0421
C2
25
305.43
0.0986
48.8387
C3
44.1
369.8
0.1524
42.4552
C4–6
66.87
447.68
0.200028115
36.6415
C7+
120
567.13
0.344560888
29.6899
C16+
250
713.62
0.645319505
18.1739
C27+
420
851.15
1.3
10.1592
The influence of operating pressure range on working gas volume and storage capacity is mainly considered, so three schemes are designed for comparison. Scheme 1: The operating pressure range is 14−24 MPa; Scheme 2: Operating pressure range is 12– 25.5 MPa; Scheme three: the operating pressure range is 10−26 MPa. In terms of time allocation in injection-production period and balance period, monthly peak adjustment coefficients are predicted according to the non-uniformity of monthly gas consumption in Liaoning, as shown in Fig. 5 considering that the main function of shuang6 gas storage is seasonal peak regulation and emergency gas supply capability, natural gas is injected into the formation in summer and recovered in winter, usually completing a complete injection and production cycle of 365 days. The specific arrangement is shown in Table 4.
Fig. 5. Monthly peak regulation coefficients in Liaoning
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X. Wang et al. Table 4. Ma19 gas storage operation parameters
Operating pressure range
Operation cycle
14 MPa−24 MPa
April 1 - September 30 October 1st - October 31th
November 1st March 31st
12 MPa−25.5 MPa
April 1 - September 30 October 1st - October 31th
November 1st March 31st
10 MPa−26 MPa
April 1 - September 30 October 1st - October 31th
November 1st March 31st
Gas injection cycle
Phase equilibrium
Gas recovery cycle
4 Scheme Effect Analysis As shown in Fig. 6 and Fig. 7, compared with the other two schemes, Case 3 has a larger operating pressure range. The accumulative working gas volume in 15 years reaches 111.79 × 108 m3 , which is 14.7 × 108 m3 higher than Case 1 and 33.19 × 108 m3 higher than Case 2, and the accumulative gas volume in 15 years reaches 99.7 × 108 m3 . The gas injection capacity and gas recovery capacity of Case 3 are significantly improved, and the oil recovery ratio of Case 1 and Case 2 is increased by 1.15% and 0.76% respectively after 15 years of operation. Therefore, the third scheme is optimized from the three cases.
Fig. 6. Operating pressure diagram of the three cases
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Fig. 7. Cumulative gas production of the three cases
The original plan is to extend the prediction of oilfield water injection development for 15 years. Compared with the original case, Case 3 is expected to increase the oil recovery by 4.65% after 15 years, with the maximum daily gas injection of 450 × 104 m3 , winter daily gas injection of 560 × 104 m3 and annual working gas of 6.86 × 108 m3 . The cumulative working gas volume in 15 years is 96.2 × 108 m3 . By 2036, a strategic peak-adjusted gas storage with storage capacity of 13.4 × 108 m3 and annual working gas capacity of 6.21 × 108 m3 will be formed. In the case of underground gas storage operation, the oil recovery is 43.76%, while in the case of continuous waterflooding, the oil recovery is less than 40%. It can also be seen from Fig. 8 that on the basis of stable gas injection and production, the remaining oil in the oil ring is gradually recovered with the increase of the injection-production cycle. As ma 19 block is a bottom-water reservoir, the amount of injection-production gas should be controlled as much as possible to prevent bottom-water coning. In the absence of special requirements, the gas storage can be operated according to Case 3, but in the case of emergency peak regulation, the peak regulation amount of the gas storage can be appropriately increased according to the actual conditions. From the comparison of the two schemes, it can be concluded that migration of injected gas in reservoir is an effective means to improve oil recovery. At the micro scale, after each injection-production cycle, more and more gas is trapped in the reservoir without being liquid, thus reducing the relative permeability of the gas phase. Therefore, the gas/oil fluidity ratio and the stability of oil-gas front at the micro scale are more favorable to oil and gas development and gas channelling mitigation. At the macro scale, the alternation of injection-production cycles is beneficial to the stability of the oil-gas front. The gas in the reservoir must connect bubbles in the pores in each cycle stage to recover oil. The wide variation of operating pressure of gas storage helps to drive more oil to production wells. In the gas production stage, with the decrease of formation pressure, the oil degassing, the increase of gas saturation is beneficial to the remaining oil in the reservoir out of the pores. In the gas injection stage, the formation pressure
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Fig. 8. Comparison of daily oil production and oil recovery between Case 3 and the original development plan
increases gradually with the increasing injection volume, and the compressibility of gas leaves more room for the oil to flow. Due to these different phenomena, the oil recovery of Block Ma 19 is predicted to increase by 4.65% after 15 years of operation in the gas storage phase.
5 Conclusions and Cognition 1) The construction of collaborative gas storage can take advantage of the gravity differentiation and mixing mechanism of natural gas injected at the top of oil and gas reservoir, which can not only greatly improve oil recovery, but also gradually build gas storage, shorten the construction period, and realize the dual benefits of oil displacement and construction. 2) Compared with the gas reservoir type, the synergistic gas storage has a better effect by considering both enhanced oil recovery and peak-adjustment gas storage models. 3) Through the production mode of collaborative gas storage, compared with the original development plan, the crude oil production is increased by 13 times, the accumulative gas injection is 99.7 × 108 m3 , the accumulative oil production is 13.83 × 104 m3 , the accumulative gas production is 96.2 × 108 m3 , and the peak adjustment and supply protection capacity of natural gas is more than 550 × 104 m3 /d. 4) Based on the numerical simulation of reservoir in Block Ma 19, the feasibility of constructing collaborative gas storage is preliminarily discussed. The results show that it is feasible and can be further studied.
References 1. Xiao, X.: Research status and suggestions of underground gas storage construction technology. Natl. Gas Ind. 32(02), 79–82+120 (2012)
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2. Ding, G.: Demand and challenge of underground gas storage in China. Natl. Gas Ind. 31(12), 90–93+131 (2011) 3. Ding, G.: Development trend and driving force of global underground gas storage. Natl. Gas Ind. 30(08), 59–61+117 (2010) 4. Yao, H.U., Weigang, H.U., Xiaohong, W., Yali, W., Qiaojing, L.: Experience and enlightenment from the construction of natural gas storage in North America. Natl. Gas Ind. 30(11), 83–86+124–125 (2010) 5. Rostami, B., Kharrat, R., Pooladi-Darvish, M., Ghotbi, C.: Identification of fluid dynamics in forced gravity drainage using dimensionless groups. Transp. Porous Media, 83(3), 725–740 (2010) 6. Xin, S., Lin, Z., Daniel, L.: Present situation and development trend of underground gas storage at home and abroad. Natl. Gas Petrol. (04), 1–4+7+66 (2007) 7. Yang, W., Wang, X., Ma, C.: Present situation and development trend of underground gas storage at home and abroad. Oil Gas Storage Transp. (06), 15–19+64 (2007) 8. Ding, G., Xie, P.: Present situation and development prospect of underground gas storage in China. Natl. Gas Ind. (06), 111–113+170 (2006) 9. Ding, G., Li, W.: Present situation and development trend of underground gas storage at home and abroad. Int. Petrol. Econ. (06), 23–26+63 (2002) 10. Wang, B., et al.: Probabilistic-based geomechanical assessment of maximum operating pressure for an underground gas storage reservoir, NW China. Geomech. Energy Environ. 31, 100279 (2022) 11. Zhou, J., Peng, J., Huang, X., Chen, Y.L., Liang, G., Li, Q.: Research on long-term operation stability of salt rock underground gas storage with interlayers. Arab. J. Geosci. 15(5), 389 (2022) 12. Wang, H., Zhang, B., Xu, N., Yu, X.: Stability analysis of anhydrite mine-out as an underground gas storage based on DEM and similarity theory: a case study. Bull. Eng. Geol. Environ. 81(3), 99 (2022) 13. Wang, Z., Wang, C., Dong, C.: Analysis of changes in magnetic anomalies in the largest underground gas storage area in China. Geomag. Aeronomy, 61(8), 1251–1262 (2022) 14. Zhang, Y., et al.: Advanced monitoring and simulation for underground gas storage risk management. J. Petrol. Sci. Eng. 208(PE), 109763 (2022) 15. Wang, J.: Change mechanism of pore structure and filling efficiency during injection production of sandstone underground gas storage. J. Natl. Gas Sci. Eng. 97, 104366 (2022) 16. Nazina, T.N., et al.: Diversity and possible activity of microorganisms in underground gas storage aquifers. Microbiology 90(5), 621–631 (2021) 17. Jiqiang, L.I, et al.: Stress sensitivity of formation during multi-cycle gas injection and production in an underground gas storage rebuilt from gas reservoirs. Petrol. Exploration Dev. Online, 48(4), 968–977 (2021) 18. Chun-qiang, Z.: Research on secondary development of well Ma 19. Chem. Manag. 22, 199 (2017) 19. Minghan, B.I.: Study on reservoir characteristics of well Ma 19 in Liaohe oilfield. Chem. Eng. Des. Commun. 42(08), 13–14 (2016) 20. Wei, L.: Study on the Distribution Law of Remaining oil in Ma 19 Well Area in the Western Depression of Liaohe Depression. Northeast Petroleum University (2016) 21. Yan, F.: Study on sedimentary characteristics of Dongying formation in Ma 19 well area of Xinglongtai oilfield. Sci. Technol. Innov. (08), 106+109 (2015). https://doi.org/10.15913/j. cnki.kjycx.2015.08.106 22. Shu, L.: Study on the Remaining Oil Distribution and Potential Tapping Measures of Dongying Formation in Block Ma 19 in the Eastern Sag of Liaohe River. Northeast Petroleum University (2015)
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23. Shu, L.: Controlling factors of remaining oil distribution in Dongying formation of block Ma 19. Petrol. Geol. Eng. 28(03), 78–81+84+148 (2014) 24. Wei, J.: Study on the Distribution Law of Remaining Oil in Shahejie Formation of Block Ma 19. Northeast Petroleum University (2014) 25. Bingbo, D., Riliang, N., Shumei, Z., Shiguang, L.: Research and application of reservoiroriented seismic data processing technology in Ma 19 well area of Liaohe Oilfield. China Petrol. Explor. 18(01), 49–53 (2013) 26. Dong, H.: Ma 19 Dongying Formation reservoir description and improvement development effect research. Liaoning Province, Liaohe Oilfield Company Exploration and Development Research Institute, October 14 (2005)
Influence of Aquifer Size and Gas Production Rate on Gas-Condensate Reservoir Performance Yi-fang Wu1(B) , Wei-hong Na1(B) , Ben Wang2 , Yan Li1 , Xin-xin Zhong1 , and Li Ma1 1 Sinopec International Petroleum Exploration and Production Corporation, Beijing, China
{yfwu.sipc,whna.sipc}@sinopec.com 2 Independent Reservoir Engineering Consultant, Beijing, China
Abstract. The process of water influx can provide natural driving energy in the development of gas-condensate reservoirs, whereas it may also cause the abandonment of production wells by water breakthrough. Under specific reservoir conditions, water influx is controlled by the size and shape of the aquifer, aquifer permeability and viscosity, as well as gas production rate. Therefore, it is critical to clarify the correlation between different patterns of water influx and recovery efficiency. This research takes a deepwater turbidite sandstone reservoir as the object, the aquifer volume, and gas production rate are changed through numerical simulation to analyze the effect of water influx on recovery efficiency. It suggests that the medium to large aquifers result in higher reservoir abandonment pressures by early water breakthrough, and lower gas recovery efficiencies. The gas and condensate recoveries of the weak aquifer case are slightly higher than the depletion case since it provides additional influx energy to the depletion reservoir. Moreover, the condensate-gas ratio of the higher abandonment pressure cases is much higher than depletion cases, which greatly improves condensate recovery. Gas recovery efficiencies of medium and strong aquifers are greatly improved by higher gas rates since the fast gas rate can outrun the water influx movement, however, the depletion and weak aquifer cases, have almost no impact. On the contrary, the higher gas rate results in lower condensate recovery efficiency for all aquifer cases. It may be contributed to higher gas rate will yield (1) lower condensate gas ratio due to lower abandonment pressure and (2) larger pressure drawdown from the wellbore, which will trap more condensate dropout in the reservoir. These conclusions show an important guiding significance for the in-depth understanding of the driving effect in gas-condensate reservoirs and optimizing gas production rate to enhance recovery efficiency. Keywords: Gas-condensate Reservoir · Water Influx · Aquifer Volume · Gas Production Rate · Numerical Simulation
1 Introduction In the development of gas-condensate reservoirs, retrograde condensation will happen once the reservoir pressure drops below the dew point [1, 2]. Heavy components start to drop out and block the hydrocarbon flowing path, resulting in a decrease in fluid © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 39–49, 2023. https://doi.org/10.1007/978-981-99-2649-7_4
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Y. Wu et al.
seepage capacity and loss in condensate yield [2–4]. Therefore, it is critical to reducing the dropout of condensate underground caused by pressure loss to enhance its recovery efficiency. To do this, common methods such as water and gas injection, chemical flood, and fracture technology are used to compensate for the reservoir pressure [2–7]. However, stimulations like these normally require a large number of investments for equipment and operation, especially for deep and offshore reservoirs, which may not be economical. Nearly half of the domestic gas reservoirs are water-driven by active natural aquifers [7, 8]. Most of them share the features of low production rate, rapid decline in production capacity, a fast increase in the water-gas ratio, and low recovery efficiency [7]. The process of water influx can help remain the formation pressure, whereas it may also cause the abandonment of production wells due to water breakthrough [4]. Waterproofing and water control, therefore, must be considered during the water-driving development of gas-condensate reservoirs [5]. Under specific reservoir conditions, the process of water influx is dominated by the thickness of the reservoir, the size, and shape of the aquifer, as well as the gas production rate [10, 11]. Each possible parameter should be investigated throughout sensitivity analysis to clarify its impact. Numerical simulation is an effective approach widely applied for many years in the studies of enhancing the recovery efficiency of gas-condensate reservoirs [9–14]. It is a fast and low-cost method able to reconstruct the complex conditions of a real-world reservoir at the very highest level [14]. Theoretically, the condensate yield is associated with the gas extraction and condensate-gas ratio [4] (see Fig. 1). No condensate drops out in the reservoir condition above the dew point (assumed as 4000 psia). The condensate-gas ratio remains constant at 180 stb/mmscf. The reservoir pressure keeps decreasing below the dew point with the development of the gas field. The condensate starts to drop out in the pores, which can no longer be extracted. As a result, reservoir hydrocarbon liquid dropout and condensate yield exhibit opposite trends until a certain pressure lower limit is touched. After that, the condensate-gas ratio begins to increase again, with a corresponding reduction in the underground hydrocarbon liquid dropout. This adverse stage, though, barely happens in real cases for the production is probably ceased before reaching the turning point.
Fig. 1. Condensate yield and liquid dropout with change in reservoir pressure in gas-condensate reservoirs.
Influence of Aquifer Size and Gas Production Rate
41
This research takes a deepwater turbidite sandstone reservoir as the object. The gas field is located in Kurt Basin east of Kalimantan Island with an area of 1027 km2 . The water depth is from 3000 to 3600 ft and the reservoir is buried 8000 to 9600 ft deep. The sedimentary environment belongs to the turbidity channel and turbidite fan in the upper Miocene deepwater restricted slope. Minor faults are seen, though they play an insignificant role in hydrocarbon accumulation. The reservoir is lithology-controlled with high porosity and permeability. Only one production well is drilled, located in the high part of the structure. Specific reservoir and fluid properties see Table 1. The reservoir pressure dropped below the dew point not long after the well was brought into production. Table 1. Reservoir and fluid properties. Property
Unit
Value
Average Initial Reservoir Pressure
psia
4884
Gas-Water Contact
ft-TVDSS
−8940
Reservoir Temperature
F
170
Average Reservoir Horizontal Permeability
mD
119
Average Reservoir Vertical Permeability
mD
14
Average NTG
fraction
0.8615
Average Reservoir Porosity
%
22.3
Average Netpay thickness
ft
67.5
Average Reservoir Swi
%
31.5
Average Reservoir Sgi
%
68.5
Dew point
psia
4500
Average Initial Condensate Gas Ratio CGR
bbl/mmscf
55
Average Initial Gas Formation Volume Factor
Rb/mscf
0.647
Average Initial Water Formation Volume Factor
Res.ft3/ft3
1.02
Residual Gas Saturation to Water
%
30
2 Methods Simulation codes are written in Eclipse and Petrel. The simulator is selected as Eclipse black oil model considering the data available and operation time. The black-oil model can be used for all depletion cases if the black-oil PVT data are generated properly [15]. The number of grids is 161 × 94 × 140. The size of each is 200 ft in the x-direction, 203 ft in the y-direction, and 0.61–5.47 ft in the z-direction. Historical simulation is applied for the production history. The result shows a good match of the bottom hole pressure and tubing head pressure. On this basis, a development strategy of 30 years given certain initial gas production rates is set for the predictions.
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The process of water influx is indirectly modeled by inputting different sizes of aquifer and gas production rates. Aquifer volumes are set from very small (VA /VR = 0 or 1) to medium (VA /VR = 10 or 30) and to large (VA /VR = 50) (see Table 2). According to previous studies, the production rate of gas-condensate reservoirs is mostly around 3% to 5% to reduce retrograde condensation and pressure-sensitive damage [16]. In this research, gas production rates are assumed from low to high (3%, 7%, 10%) for simulation (see Table 2). The volume of the reservoir is calculated via formula (1), and that of the aquifer by formula (2), gas production rate herein refers to the initial annual production rate of original gas in place, shown as (3). Lastly, gas and condensate recovery efficiency (4) and water influx (5) are calculated in Petrel. VR = OGIP ×
Bg Sgi
(1)
VA = OWIP × Bw − VR × Swi Rg =
(2)
daily production rate × days of the year × 100% OGIP
(3)
Cumulative production × 100% OGIP
(4)
Recovery efficiency =
Water influx = CWIR − OWIR
(5)
VR -reservoir volume, mmb, VA -aquifer volume, mmb, OGIP-Original gas in place, bcf, OWIP-Original water in place, mmstb, CWIR-Current water in reservoir, mmstb, OWIR-Original water in reservoir, mmstb, Rg -gas annual production rate, %, Bg -gas formation volume factor, rb/mscf, Bw -water formation volume factor, Res.ft3 /ft3 , Sgi Initial gas saturation, %, Swi -Initial water saturation, %. Since actually VA /VR = 1, the easiest way to make the no-aquifer case is to simply multiply the porosity of the grids that Swi = 1 with 0. To increase the size of the aquifer, the porosity of grids located near the edge of the aquifer away from the reservoir is multiplied. Note that when VA /VR ≥ 10, an extra imbibition curve is applied to the computation other than the original drainage curve, considering the residual gas trapped in the pores by water influx [1]. Scenarios with each sized aquifer are run under three gas production rates, overall, 15 cases are modeled. Constrain and cutoffs are listed in Table 2. Table 2. Parameters applied in simulations. Category
Parameter (unit)
Value
Variable
Rg (%)
3, 7, 10
VA /VR (multiple)
0, 1, 10, 30, 50
Constrain
Tubing head pressure (psi)
300
Cutoff
Minimum daily gas production rate (Mscf/d)
1000
Maximum water-gas ratio (stb/Mscf)
0.05
Influence of Aquifer Size and Gas Production Rate
43
3 Results 3.1 Impact of Aquifer Volume on Recovery Efficiency As shown by the results, the producing life expectancy decreases with the increase in the aquifer size (see Fig. 2A, 2B). Water influx takes place sooner as the aquifer expands (see Fig. 2C). The production well is shut due to water-gas ratio constrain under VA /VR from 10 to 50, whereas for VA /VR = 0 and 1 it is limited by the lowest gas production rate (see Fig. 2D). The hydrocarbon pore volume-weighted average pressure remains higher to the end of the production lifetime because of the energy supplement by water influx (see Fig. 2E). Moreover, the slopes of the pressure gradient appear to be tender, and the condensate-gas ratio slightly increases under larger aquifer cases (see Fig. 2F). Gas recovery efficiency reaches the peak when VA /VR =1, then it gradually decreases due to the early shut-in of the well by water breakthrough as the aquifer continues to expand, resulting in higher abandonment pressure. The maximum condensate recovery efficiency happens when VA /VR = 10, it is generally higher when the pressure is maintained at a higher level by water influx throughout the entire product lifetime. It is observed that the gas yield corresponds with the time of abandonment of the well, the sooner water breakthrough happens, the less amount of gas is produced. However, the total condensate production seems not to be closely related to the producing time ranges. It is impeded either the abandonment pressure is too low, or the well is shut too early. More condensate is produced under moderate hydrocarbon pore volume-weighted average pressure and producing time. A) Change in gas recovery efficiency with time; B) Change in condensate recovery efficiency with time; C) Change in hydrocarbon pore weighted average pressure with time; D) Change in water influx with time; E) Change in condensate-gas ratio with time; F) Change in water production cumulative with time. Since the production of condensate yield is not simply related to the life expectancy of producing well, the impact of pressure control is further demonstrated. When the hydrocarbon pore volume-weighted average pressure is above the dew point, the condensate yield is limited by the initial condensate-gas ratio. As a result, the recovery efficiencies of both gas and condensate are equivalent regardless of the existence of aquifers (see Fig. 3, pressure above 4500 psia). Subsequently, they start to decline separately below the dewpoint pressure. For the depletion case, the abandonment pressure decreases to about 1829 psia with an ultimate condensate recovery efficiency of 32.9%. For the water out case in which VA /VR = 50, the abandonment pressure is much higher at approximately 3788 psia due to water influx, ending with a condensate recovery efficiency of around 34.3%. The comparison reveals a positive correlation between the abandonment pressure and condensate recovery efficiency and a reverse relationship with gas recovery efficiency. Moreover, the percentage gap between the gas and condensate recovery efficiency becomes narrower for the water out cases. It suggests that even though higher abandonment pressure corresponds with less gas yield, the increased condensate-gas ratio successfully compensates for the condensate yield, resulting in higher condensate recovery efficiency.
A
100
B
80 60
VA/VR = 0 VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
40 20 0 0
5
10
15
20
25
30
Condensate Recovery Efficiency, %
Y. Wu et al. Gas Recovery Efficiency, %
44
35 30 25 20
VA/VR = 0 VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
15 10 5 0 0
5
10
15
2.E+07 Water influx, stb
C
D
VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
2.E+07 1.E+07 5.E+06 0.E+00 0
5
10
15
20
25
30
30
VA/VR = 0 VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
2.E+05 1.E+05 5.E+04 0.E+00 0
5
10
15
20
25
30
Time, years
5000
F
VA/VR = 0 VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
4500 4000 3500
0.07 Condensate-gas ra o
Hydrocarbon pore volume weighted average pressure, psia
25
2.E+05
Time, years
E
20
Time, years
Water produc on cumula ve, stb
Time, years
3000 2500 2000 1500
VA/VR = 0 VA/VR = 1 VA/VR = 10 VA/VR = 30 VA/VR = 50
0.06 0.05 0.04 0.03 0.02 0.01 0
0
5
10
15 Time, years
20
25
30
0
5
10
15
20
25
30
Time, years
Fig. 2. Simulation results of different aquifer volumes, Rg = 10%.
Fig. 3. Correlations between pressure and condensate recovery efficiency. VA /VR = 0 and 50. Rg = 10%.
3.2 Impact of Gas Production Rate on Recovery Efficiency When VA /VR = 1, the changes in gas recovery efficiency are hardly affected by gas production rate, while higher rates cause a minute decrease in the final gas recovery efficiency and abandonment pressure (see Fig. 4A). Condensate recovery efficiency, however, decreases separately following a larger pressure gradient with the increase in
Influence of Aquifer Size and Gas Production Rate
45
gas production rate (see Fig. 4B). These correlations begin to change as the aquifer volume continues to expand. When VA /VR ≥ 10, gas recovery efficiency increases obviously with the increase in gas production rate (see Fig. 4C, E), while the trend for condensate recovery efficiency is just the other way round (see Fig. 4D, F). A larger pressure drawdown is required to generate the equivalent amount of yield under faster production rates, resulting in lower abandonment pressure. It is further proved that condensate recovery efficiency is positively correlated with the abandonment pressure for reservoirs with medium-large sized aquifers.
Fig. 4. Correlations between hydrocarbon pore volume-weighted average pressure and recovery efficiency.
A) Change in gas recovery efficiency with pressure, VA /VR = 0; B) Change in condensate recovery efficiency with pressure, VA /VR = 0; C) Change in gas recovery efficiency with pressure, VA /VR = 10; D) Change in condensate recovery efficiency with pressure, VA /VR = 10; E) Change in gas recovery efficiency with pressure, VA /VR = 50; F) Change in condensate recovery efficiency with pressure, VA /VR = 50. The process of water influx is almost rate-independent when the aquifer is quite small (see Fig. 5). Eventually, the pressure remained in the reservoir is much the same since it experienced similar loss by gas production and compensation by water influx.
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However, the amount of water intruded into the reservoir is dominated by gas production rates for the water out cases. Less water is intruded into the reservoir to obtain the same gas yield as the gas production rate accelerates. In other words, the gas rates outrun the speed of water influx, resulting in higher gas recovery efficiency.
Fig. 5. Correlation between gas recovery efficiency and water influx under different gas production rates. Rg = 3%, 7%, 10%. VA /VR = 1 and 50.
4 Discussion 4.1 Controlling Factors on Gas and Condensate Production The recovery efficiency of gas-condensate reservoirs could be affected by the abandonment pressure, energy supply, aquifer volume, water influx, etc. [9, 11]. A small amount of aquifer can effectively supply the formation energy, narrowing the pressure gradient and therefore enhancing gas recovery efficiency. A medium-large aquifer would accelerate the process of water influx, leading to an early water breakthrough and reducing gas recovery efficiency. The curvatures of gas recovery efficiency for cases without aquifers are almost the same regardless of gas production rate. This is probably because no extra energy is supplied from the surroundings, which means the final pressure loss is almost equal. Interestingly, the amount of water influx decreases to obtain the same gas yield with the increase in gas production rate. It is then implied that the speed of water influx is slower than gas extraction, leaving more transition space between the gas and aquifer. Condensate recovery efficiency is a competing result of both gas extraction and condensate-gas ratio. Below the dew point, higher abandonment pressure will result in a higher condensate-gas ratio and higher condensate recovery efficiency for no-weak aquifer cases. As the aquifer expands, however, it may reduce due to the early shut-in of the production well since the overall gas extraction is insufficient to be overcome by the higher condensate-gas ratio. Nonetheless, condensate recovery efficiencies vary following distinct trends even when VA /VR = 0 and 1. This is probably because condensate dropouts sooner in the reservoir under a faster production rate, more effective pore volumes are then occupied, impeding the fluidity of gas [17, 18]. A larger pressure difference is then required for the same amount of production, consistent with the simulation results. This may explain the fact that faster production rates contribute to less cumulative condensate and gas production.
Influence of Aquifer Size and Gas Production Rate
47
4.2 Suggestions for Development Optimization Since the sale price of condensate is generally higher than gas, a lower gas production rate could be suggested under the condition of little or no aquifer to enhance condensate recovery efficiency. The cost and investment for longer production duration should also be examined for the increase in cumulative condensate production may not be significant. When it comes to reservoirs with a medium-large sized aquifer, the condensate-gas ratio should be taken into consideration. As condensate recovery efficiency would not differ greatly with the change in gas production rate under a relatively low condensate-gas ratio, the rate should be accelerated to improve cumulative gas yield and save the cost. Whereas for those with a higher condensate-gas ratio, condensate recovery efficiency would be dramatically impacted by the gas production rate, and so does the overall economic value of the project. It is, therefore, better to slow down the production rate to generate more condensate. Simultaneously, note that the gas production rates for condensate and gas to reach the maximum yield could be different. Economic evaluation based on comprehensive analysis including initial condensate-gas ratio, gas and condensate production, sale prices, cost, investment, and other constraints is necessary for different predicted production profiles to optimize the development plan and maximize the profit [19, 20].
5 Conclusion Water influx has a very strong impact on gas-condensate reservoir performance, and the influx strength depends on aquifer size, shape, and aquifer properties including permeability, viscosity, etc. In this paper, the numerical simulation runs with various aquifer sizes from VA /VR = 0, 1, 10, 30, 50 were made to investigate gas and condensate recovery efficiency impacts. It is found that the medium (VA /VR = 10) to large aquifers (VA /VR = 30, 50) result in higher reservoir abandonment pressures by early water breakthrough and lower gas recovery efficiencies. The gas and condensate recoveries of the weak aquifer (VA /VR = 1) case is slightly higher than the depletion (VA /VR = 0) case since it provides additional influx energy to the depletion reservoir. On the other hand, even though the higher abandonment pressure cases produce less gas, their producing condensate-gas ratio is much higher than depletion cases, which greatly improve condensate recovery. The results show medium and strong aquifers produce slightly more condensate than the depletion and weak aquifer cases. Increasing gas production rates may greatly enhance the gas recovery efficiency of water-driven gas reservoirs by reducing reservoir abandonment pressure. This is because the fast gas rate can outrun the water influx movement which depends on aquifer size and permeability. Gas recovery efficiencies of medium and strong aquifers are greatly improved by higher gas rates, however, in the depletion and weak aquifer cases, the gas recovery efficiencies have almost no impact. The study also shows the gas rate has an inverse impact on condensate recovery efficiency, e.g., the higher gas rate results in lower condensate recovery efficiency for all aquifer cases. It may be contributed to higher gas rate will yield (1) lower condensate gas ratio due to lower abandonment pressure and (2) larger pressure drawdown from the wellbore, which will trap more condensate dropout in the reservoir.
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Acknowledgments. The project is supported by Reserves & Economic Evaluation Unit of SIPC Technical Support Center. The paper is elected by IPPTC Organizing Committee to presented at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022.
References 1. Yang, S.L., Wei, J. Z.: Reservoir Physics, 1st edn. Petroleum Industry Press, Beijing (2004) 2. Coats, K.H.: Simulation of gas condensate reservoir performance. J. Pet. Technol. 37, 1870– 1886 (1985) 3. Raghavan, R., Jones, J.R.: Depletion performance of gas-condensate reservoirs. J. Pet. Technol 48, 725–731 (1996) 4. Guo, P., Wang, Z.H., Zhu, Z.Q., et al.: Technology for Enhancing Gas-Condensate Reservoir Recovery Efficiency and Case Studies. 1st edn. Petroleum Industry Press, Beijing (2015) 5. Shi-lun, L., Yi, P., Lei, S.: A new idea on enhancing the recovery rate of condensate gas reservoirs. Nat. Gas Ind. 28 (9), 1–5 (2008) 6. Tong-wen, J., Zhu, Z.Q., Xiong, Y., et al.: Dynamic Analysis Method and Practice of Circulating Gas Injection Development for Condensate Gas Reservoir. 1st edn. Petroleum Industry Press, Beijing (2013) 7. Guo, P., Jing, S.S., Peng, C.Z.: Technology and countermeasures for gas recovery enhancement. Nat. Gas Ind. 34(2), 48–55 (2014) 8. Song, D.S.: Research on Dynamic Characteristics and Analysis Method of Water-Drive Gas Reservoirs. Southwest Petroleum University, Sichuan (2012) 9. Izuwa, N.C., Nwosu, C.N.: Influence of aquifer support on gas condensate reservoir performance. In: Paper presented at the SPE Nigeria Annual International Conference and Exhibition, Lagos, Nigeria, August 2014 (2014) 10. Cui, C.Z., Wu, Z.X., Yang, Y., et al.: Prediction of water breakthrough time of vertical wells for bottom water condensate gas reservoirs considering dynamic gas-water interface. Fault-block Oil Gas Field 26(1), 58–61 (2019) 11. Tran, T.V., Truong, T.A., Ngo, A.T., Hoang, S.K., Trinh, V.X.: A case study of gas-condensate reservoir performance under bottom water drive mechanism. J. Petrol. Explor. Product. Technol. 9(1), 525–541 (2018). https://doi.org/10.1007/s13202-018-0487-7 12. Wang, B., Teasdale, T.S.: GASWAT-PC: a microcomputer program for gas material balance with water influx. In: Petroleum Industry Applications of Microcomputers, pp. 25–42. Society of Petroleum Engineers, Texas (1987) 13. Liang, B., et al.: In: IFEDC, pp 1-8. China Academic Journal Electronic Publishing House, Beijing (2020) 14. Zhang, L.H., Guo, J.J.: Basic Principles of Reservoir Numerical Simulation. 2nd edn. Petroleum Industry Press, Beijing (2014) 15. Fevang, Ø., Singh, K., Whitson, C.H.: Guidelines for choosing compositional and black-oil models for volatile oil and gas-condensate reservoirs. In: Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas (2000) 16. Xu, F.Z: Research on dissection of gas reservoirs in Longfengshan gas field and development optimization. Chem. Enterp. Manag. 3, 209–211 (2019) 17. Kalaydjian, F.J-M., Bourbiaux, B.J., Lombard, J-M.: Predicting gas-condensate reservoir performance: how flow parameters are altered when approaching production wells. In: Paper Presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado (1996)
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18. Barnum, R.S., Brinkman, F.P., Richardson, T.W., Spillette A.G.: Gas condensate reservoir behaviour: productivity and recovery reduction due to condensation. In: Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, October 1995 (1995) 19. Luo, M., Yang, J.F., Fu, Q.F., et al.: Sensitivity analysis research and application of condensate gas reservoir development plan. Contemp. Chem. Ind. 43(8), 58−62 (2014) 20. Fawzy, F.: Investigation of the optimum production strategies for the economic recovery of gas condensate reservoirs with different aquifer strength. In: Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA (2017)
Standards of Well Fracturing Measures in Class II Grade B Reservoirs in Water Cut Period Yao-Zhou(B) Daqing Oilfield Limited Liability Company, Daqing, China [email protected]
Abstract. The practice of polymer flooding development of Lamadian oilfield in extra high water cut period shows that the initial effects of well fracturing in class II grade A reservoirs is much better than that of class II grade B reservoirs, which means there is a big difference of the fracturing effect between two types of oil layers. Only a few wells of class II grade B reservoirs obtain better fracturing effect. To further improve the development effect of class II grade B reservoirs, the standards of well fracturing measures of such reservoirs in water cut period should be pinpointed. This paper compared the data of 48 fracturing wells of class II grade B reservoirs such as the dynamic production data, well pattern, scale of fracturing, fracturing layers and compound mode before and after fracturing in water cut period. Through analyzing differentiation characteristic of fracturing in different types of oil layers, this paper pinpointed the technology boundary of selection of fracturing wells and selection of fracturing layers of different oil layers in class II grade B reservoirs P II 7-G I 4 + 5 oil layer in water cut period. Refining of the fracturing standards of wells in water cut period provided effective reference and basis for the well-selecting and layer-selecting in class II grade B reservoirs in water cut period, which validly improve the development effect of the wells in class II grade B reservoirs. Keywords: class II grade B reservoirs · well fracturing measures · technical standards
Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been re-viewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 50–59, 2023. https://doi.org/10.1007/978-981-99-2649-7_5
Standards of Well Fracturing Measures
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1 Introduction After responding time, polymer flooding in class II grade B reservoirs of Lamadian oilfield has turned into water cut period, which has the characteristics, such as increased filtrational resistance, large descend range of liquid production capacity. It impacted the effects of polymer flooding. Fracturing is the main adjustment method to enhance production of oil of such reservoir and improve development effect [1]. According to the development practice of polymer flooding in ultra-high water-cut stage of Lamadian oilfield, prepared with the wells of class II grade A reservoirs which had 6.0 t increased oil production per day after fracturing, the wells of class II grade B reservoirs PII7-G I 4 + 5 oil layer in water cut period was only average 3.0t increased oil production per day. However, nearly one fifth of these wells of class II grade B reservoirs had above 4.5 t increased oil production per day, which was close to the level of class II grade A reservoirs [2]. For one thing, the reason is due to high pay-gross thickness ratio and relatively less remaining oil, for the other hand, it is related to the well-selecting, layselecting and the fracturing method, which means that the fracturing measure of polymer flooding needs technical standard of class II grade B reservoirs PII 7-G I 4 + 5 oil layer in water cut period to improve development effect [3]. This paper took 66 fracturing wells of class II grade B reservoirs P II 7-G I 4 + 5 oil layer in water cut period for example, found out the main factors that influenced the effect of fracturing, and summarized the standards of well-selecting and layer-selecting of class II grade B reservoirs P II 7-G I 4 + 5 oil layer, which provided basis for later exploration [4].
2 Analysis of Fracturing Effect In terms of fracturing effect of responding wells (Table 1), selected the fracturing well groups, which had enough producing energy and good injectivity behavior to analyze. The result was that in initial stage of measure, the average increased liquid production per day was 28 t, and increased oil production was 3.0 t. Among these wells, about 39 oil wells have less than 3.0 t increased oil production. The average increased oil production of 39 wells is 1.4 t per well per day. The proportion is 59.1%; about 18 oil wells have increased oil production that is between 3.0 t and 5.0 t. The average increased oil production of 18 wells is 4.1 t per well per day. The proportion is 27.3%; about 9 oil wells have above 5.0 t increased oil production. The average increased oil production of 9 wells is 7.8 t per well per day. The proportion is 13.6%. The result shows that the wells located on the oil well row of the basic well pattern have better fracturing effect and the average increased oil production per day is 4.0 t; the wells located on the diverting stream line of injection-production take second place, and the average increased oil production per day is 2.3 t; the wells located on the injection well row of the basic well pattern and wells located on the main stream line have the worst effect, and the average increased oil production per day is only 1.7 t, which is consistent with responding characteristics and residual oil distribution law of class II grade B reservoirs. Therefore, the wells located on the oil well row of the basic well pattern should precedence to be selected as fracturing wells.
39
18
9
66
5
total
100
13.6
27.3
59.1
28
44
33
23
3
7.8
4.1
1.4
Increased Number Proportion Increased Increased oil (%) liquid oil production (t/d) production scale (t/d) (t/d)
34
8
12
14
27
40
32
15
4
8
4.1
1.4
17
5
12
29
32
28
Increased liquid (t/d)
2.3
4.1
1.5
15
2
13
31
44
26
Increased Number Increased oil liquid production (t/d) (t/d)
Diverting stream line Injection well row of the basic well of injection-production pattern/main stream line
Number Increased Increased Number liquid oil (t/d) production (t/d)
Oil well row of the basic well pattern
Different well patterns position
Table 1. Fracturing effect of wells at different location in initial stage of fracturing measures
1.7
4
1.3
Increased oil production (t/d)
52 Yao-Zhou
Standards of Well Fracturing Measures
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Meanwhile, fracturing effect of these wells has a big difference. As a result, under the premise of enough producing energy, the proportion of sand connecting is above 50.0%, and good injectivity behavior, analyze the factors influencing the fracturing effect of three position types to summarize the difference characteristics of fracturing wells of class II grade B reservoirs P II 7-G I 4 + 5 oil layer in water cut period. 2.1 Analysis of Technical Standards of Well-Selecting According to the principle and characteristics of responding of polymer flooding, under the premise of enough producing energy [5], the fracturing standards of well-selecting of class II grade B reservoirs should be judged according to the descend range of liquid production capacity and water cut. The average fracturing thickness per well is 8.6 m, while average increased oil production per day in initial stage of fracturing is 3.0 t, so choose increased oil production per day per fracturing thickness 0.4 t/m as the standards. From correlation curve (Fig. 1) of increased oil production per day per fracturing thickness and the descend range of liquid production capacity of 66 wells of the block, there is obvious positive correlation between them. Overall speaking, the greater the descend range of liquid production capacity, the better the increased oil production effect, although, the wells at different location have differences [6]. The result shows that among the wells located on the oil well row of the basic well pattern, the descend range of liquid production capacity of the wells which is above 30% have better fracturing effect; among the wells located on the diverting stream line of injection-production, the descend range of liquid production capacity of the wells which is above 40% have better fracturing effect [7]; among the wells located on the injection well row of the basic well pattern and wells located on the main stream line, the descend range of liquid production capacity of the wells which is above 45% have better fracturing effect.
Fig. 1. The correlation curve of increased oil production per day per fracturing thickness and the descend range of liquid production capacity.
From correlation curve (Fig. 1) of increased oil production per day per fracturing thickness and the descend range of water cut of 66 wells of the block, there is obvious
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positive correlation between them [8]. The greater the descend range of water cut, the greater increased oil production per day, although, the wells at different location have differences. In terms of the wells located on the oil well row of the basic well pattern, the greater the descend range of water cut, the greater increased oil production per day, the better fracturing effect. The best way is to select the wells which the descend range of water cut is above 8.0% to fracture; while, due to the remaining oil, the descend range of water cut of the wells located on the diverting stream line of injection-production and the wells located on the injection well row of the basic well pattern and the wells located on the main stream line, the descend range of water cut couldn’t reach the enough level, so only the wells which the descend range of water cut is above 6.0% and 4.0% could be selected to fracture to meet the standards of increased oil production per day per fracturing thickness 0.4 t/m to improve the development effect. 2.2 Analysis of Technical Standards of Layer-Selecting Under the premise of good injectivity behavior, analyze water logging and permeability of the fracturing layers to define the standards of layer-selecting [9]. From correlation curve (Fig. 2) of increased oil production per day per fracturing thickness and high water logging thickness of fracturing layers, among the wells located on the oil well row of the basic well pattern, the layers which high water logging thickness is less than 40% have better effect; among the wells located on the diverting stream line of injection-production, the layers which the water logging thickness is less than 50% have better fracturing effect; due to the water logging of the wells located on the injection well row of the basic well pattern and wells located on the main stream line is very serious, select the layers which the water logging thickness is less than 60%.
Fig. 2. Correlation curve of increased oil production per day per fracturing thickness and high water logging thickness of fracturing layers
Standards of Well Fracturing Measures
55
From the fracturing effect scale of different permeability layers of 66 wells of class II grade B reservoirs (Table 2), the characteristics of fracturing effect of class II grade B reservoirs is relatively conform to that of class II grade A reservoirs, that is, during the water cut period, the middle-high permeability layers (0.4 µm2 −0.8 µm2 ) respond earlier. So selecting these layers as fracturing layers could gain better increased oil production effect [10]. However, the effect also differs greater among different well positions. In terms of the wells located on the oil well row of the basic well pattern, fracturing layers which permeability is between 0.6 µm2 and 0.8 µm2 have better effect, increased oil production per day is up to 4.5 t and increased oil production per day per fracturing thickness could up to 0.6 t/m. Increased oil production per day per fracturing thickness of the low-middle permeability fracturing layers which permeability is 0.2 µm2 − 0.4 µm2 and 0.4 µm2 −0.6 µm2 could also up to 0.4 t/m. Therefore, all layers of the wells should be taken into account when fracturing. Then combine with dynamic data and water absorption to select the fracturing layer and scale [11]. The fracturing effect of middle-high permeability layers of wells located on the diverting stream line of injection-production is obvious better than that of low permeability, it is better to select the layers which is middle-high permeability [12]. In terms of wells located on the injection well row of the basic well pattern and main stream line, the fracturing effect of layers which permeability is 0.2 µm2 −0.4 µm2 is better, increased oil production per day is high up to 2.8 t and increased oil production per day per fracturing thickness is up to 0.3t/m. 2.3 Design Analysis of Technological Parameter of Fracturing During polymer flooding, adsorption trapping of polymer causes filtration capacity getting worse, and the injection system is maladjusted to the poor and thin reservoir, which makes layers blocked, which causes liquid capacity declining [13]. Therefore, the presupposition of better fracturing effect is to ensure particular fracturing scale [14]. Increased oil production of initial fracturing measures of class II grade B reservoirs in water cut period is 28 t, which means better fracturing effect. Take increased oil production per day per fracturing thickness 3.0 t/m as qualified standard. From correlation curve of increased oil production per day per fracturing thickness and quantity of sand fracturing per fracturing thickness (Fig. 3), before quantity of sand fracturing per fracturing thickness of three position types of wells is up to 8.0 m3 /m, increased oil production per day per fracturing thickness is obviously increased as quantity of sand fracturing is increasing, and after it is above 8.0 m3 /m, it tend to gently. Almost the wells that quantity of sand fracturing is above 6.0 m3 /m could reach the standard, and increased oil production per day per fracturing thickness is 5.1 t/m. While that of quantity of sand fracturing is less than 6.0 m3 /m is less than 3.0 t/m. Therefore, the quantity of sand fracturing should be controlled at the range of 6.0 m3 /m−8.0 m3 /m. 2.4 Multi Linear Regression Forecast Mode By analyzing the factors which influence the fracturing effect of class ii grade B reservoirs, such as the descend range of liquid capacity, water cut, the proportion of high water logging and permeability, applying SPSS software, taking enhanced production
25
28
28
0.4− 0.6
0.6−0.8
total
3
3.9
2.6
0.4
0.5
0.3
0.3
33
0.2− 0.4
2.4
Increased oil production per fracturing thickness (t/m)
permeability Increased Increased scale of liquid oil fracturing (t/d) production layers (t/d) (µm2 )
27
28
32
22
3.9
4.5
3.9
3.2
Increased Increased liquid(t/d) oil production (t/d)
0.5
0.6
0.4
0.4
29
25
33
25
2.3
3.6
2.2
1.3
Increased oil production (t/d)
diverting stream line of injection-production
Increased Increased oil liquid(t/d) production per fracturing thickness (t/m)
oil well row of the basic well pattern
Different well patterns position
0.3
0.5
0.3
0.2
31
31
22
43
1.8
1.5
1.2
2.8
Increased oil production (t/d)
0.2
0.2
0.1
0.3
Increased oil production per fracturing thickness (t/m)
injection well row of the basic well pattern/main stream line Increased Increased oil liquid(t/d) production per fracturing thickness (t/m)
Table 2. Fracturing effect of different permeability layers scale
56 Yao-Zhou
Standards of Well Fracturing Measures
57
Table 3. Standards of well-selecting and layer-selecting of PII7-GI4 + 5 oil layer Position of wells
oil well row of the basic well pattern
diverting stream line of injection-production
injection well row of the basic well pattern/main stream line
Principle of well-selecting
1. The descend range of liquid capacity ≥ 30% 2. The descend range of water cut ≥ 8.0 % 3. Formation pressure is higher than initial formation pressure
1. The descend range of liquid capacity ≥ 40% 2. The descend range of water cut ≥ 6.0 percent 3. Formation pressure is higher than initial formation pressure
1. The descend range of liquid capacity ≥ 45% 2. The descend range of water cut ≥ 4.0 % 3. Formation pressure is higher than initial formation pressure
Principle of layer-selecting
1. Middle-high permeability layers 2. High water logging thickness 1.0
0.5–1.0 Ratio
Number
Ratio
Number
Ratio
2010
4716
335
7.1%
570
12.1%
546
11.6%
1382
29.3%
1883
39.9%
2011
5765
540
9.4%
742
12.9%
788
13.7%
1579
27.4%
2116
36.7%
2012
7082
733
10.4%
1185
16.7%
987
13.9%
1675
23.7%
2502
35.3%
2013
8381
1026
12.2%
1478
17.6%
1195
14.3%
1850
22.1%
2832
33.8%
2014
9667
1314
13.6%
1896
19.6%
1333
13.8%
2068
21.4%
3056
31.6%
2015
10445
1822
17.4%
2059
19.7%
1474
14.1%
2104
20.1%
2986
28.6%
2016
11481
2204
19.2%
2355
20.5%
1669
14.5%
2214
19.3%
3039
26.5%
2017
13054
2702
20.7%
2731
20.9%
1761
13.5%
2612
20.0%
3248
24.9%
2018
15881
3257
20.5%
3315
20.9%
2409
15.2%
3330
20.9%
3520
22.5%
2019
18567
3993
21.5%
3929
21.2%
2844
15.3%
3904
21.1%
3897
20.9%
2020
20966
4948
23.6%
4701
22.4%
3146
15.0%
4227
20.2%
3944
18.8%
2.2 Deficient Gas Wells In Changqing gas area, a growing number of wells slide to be less than 0.1 × 104 m3 /d in daily output. In 2010 there were 4716 gas wells, 7.1% of which were low production wells. Ten years later, the percentage rise to 23.6% in 2020 when there were 20966 gas wells. And the proportion is much likely to rise with the join of new wells in the coming years. The top two gas fields of having the biggest number of low production wells are Sulige and Jingbian, the ratio of which are 27% and 20.1% respectively (see Fig. 1).
Study and Application on Highly Effective Development Technology
The ratio of low production wells
The total number of wells
20000
19.2 17.4
15000
15881
12.2 9.4
10.4
7.1 5000
4716
0
2010 (a)
5765
7082
2012
8381
9667
20
15
13054 11481 10445
10
5
2014
2016
2018
Time
(a) Historical data
2020
30 The total number of wells
27
18567
13.6
10000
20966
18000
25
21.5
20.7 20.5
0
The ratio of low production wells
15000
20.1
12000
20
9000
15
10.1
6000
8.8
3000
0
25
10
2.5 1922
16223
Jingbian Gasfield Sulige Gasfield
465 Zi-Mi Gasfield
397
1790
Yulin Gasfield Shenmu Gasfield
5
The ratio of low production wells (%)
23.6
The total number of wells
The ratio of low production wells (%) The total number of wells
25000
63
0
(b)
(b) Gas data of five gas fields
Fig. 1. Distribution of low production wells in Changqing gas area.
2.3 Causes for Low Production When it comes to the core factors of low production gas wells, there are five types: depleted formation energy, bad reservoir quality, water flooding, wellbore malfunction, and unfitting production system. Depleted Formation Energy. The formation energy is nearly depleted when there is little supply of gas or liquid. For low production wells of this kind, the flowability is much weak in formation, wellbore and gathering. There are about 628 wells, mainly in Jingbian gas field which undergoes long-term production, accounting for around 12.8% of all low production wells. Worse Reservoir Physical Properties. The reservoir quality typically is reflected by porosity and permeability. When it is in the margin of river channels, the reservoir is far away from high quality for there is little possibility of containing large volume of natural gas. Shenmu is the major gas field of having the largest number of low production wells caused by bad reservoir quality, the number of which is about 1411 accounting for 28.8%. Serious Water Flooding. Serious water flooding often causes the stoppage of gas wells. In the very beginning, there is little formation water left underground for most of it can be lifted out to surface by natural gas. With the drop of pressure, more water starts to stay in the bottom of wellbore, leading to the increase of water volume in the surround area [7]. The permeability of gas is to decreases with the increase of water saturation. The more water left, the lower gas production. Some of them are forced to cease breathing. In Changqing gas area, there are 2368 wells resulting from serious water flooding, 43.4% contribution to all low production wells. They are scattered in the western Sulige, which is notorious for widespread water flooding. Wellbore Malfunction. When malfunctions takes place at casing, tubing, or any other wellbore components, gas wells will work abnormally or be halted. Wellbore malfunctions have several types such as tubing corrosion, scaling, sand-blocking. 284 lowproduction wells are caused by wellbore malfunctions. Malfunctions like corrosion and
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scaling, taking a long time, mainly exist in Jingbian. Others like sand blocking and restrictor failure, relating to wellbore types, often come into being in Sulige. Unfitting Production System. H2 S is extremely harmful to human beings, animals and others on Earth, mainly existing in the gas reservoir of lower Paleozoic while not in upper Paleozoic. As for upper Paleozoic reservoirs, the development technologies are unfitted with gas wells containing H2 S. Thus for gas fields like Sulige, gas wells after opening up lower Paleozoic reservoir are surely to be closed. There are 207 closed wells caused by unexpected H2 S, accounting for 4.2% of all low production wells.
3 Stimulating Technologies For old gas fields where low-production and closed wells are posing a growing effect in a negative way, stimulating technologies for old wells play a significant role in their highly effective development. The common technologies usually include sidetracking, reconstruction, drainage and so on [4]. Corresponding to five causes mentioned above, diverse methods are put forth covering reservoir, wellbore, and production process. After three years of in-site practice, technologies with the core of reservoir stimulating and auxiliary of wellbore treatment and updating production process matures (see Fig. 2). Stimulating Technologies for Old Depleted formation
Worse physical properties
Serious water flooding
Wellbore malfunction
Wellbore Treatment
Reservoir Stimulating
Unfitting production
Surface Updating
Comprehensive Treatment of Well Group
Desulfurization at Wellhead
Difficult Throttle Fishing and Processing
Reproduction of Water Flooded Wells
Wellbore Chemical Descaling
Optimizing pipe column reproduction
Workover
Coiled Tubing Sand Flushing
Reservoir Dredging and Unblocking
Fishing and Dropping Plugs
Sidetracking Horizontal Wells.
Stimulating Untapped Reservoir
Fig. 2. Stimulating Technologies for Old Wells in Low-Permeability and Tight Gas Reservoirs
Study and Application on Highly Effective Development Technology
65
3.1 Reservoir Stimulating Before planning stimulating, reservoir features and problems should are clearly understood in the first place by making an accurate review of old wells through data such as logging, testing, production. Then specific contradiction can be solved effectively by the following methods. Stimulating Untapped Reservoir. In Ordos basin, there are two kinds of gas reservoir in geology: upper Paleozoic and lower Paleozoic. The former develops mainly in Ma5 member of Majiagou formation of Ordovician. The latter consists of five gas formations of Permian: Shiqianfeng, Shihezi, Shanxi, Taiyuan and Benxi. The earlier development scheme has some shortcomings due to insufficient understandings. For example, the gas reservoir of the upper Paleozoic in Jingbian gas field is barely developed for its reservoir was not deemed feasible to be developed economically and technically at that time [8]. Main development formations belong to upper Paleozoic in Sulige gas field, left gas reservoirs of lower Paleozoic untapped. The construction of Yulin gas field largely comes from Shan2 formation of upper Paleozoic, seldom from other gas formations. Along with the successful development of those gas fields are the updating of geological understandings and developing technologies. Gradually, the focus of development starts shifting to those ignored gas reservoirs. One method of stimulating production is to develop untapped reservoir by implementing perforation and fracturing [9, 10]. The key issue lies in picking up the most potential layer from seemingly useless and similar reservoirs. Based on diverse gas well data such as logging, testing, production, porosity overlapping is newly put forth to interpret gas saturation and has been proved accurate and effective. Moreover, the low limit standard of resistivity for effective reservoir is recalibrated to make the calculation of its thickness more reasonable and trustworthy. In the premise of maturity, safety, economy and influence, there form four types of stimulating untapped reservoir: sealing upper and producing lower, sealing lower and producing upper, sealing middle and producing upper-lower, sealing upper-lower and producing middle (see Table 2). The implementation is organized uniformly by special project group and supported by scientific research units. And for each well, it is also optimized from geology and engineering through discussion. After implementation, the effect is evaluated to provide upgrading suggestions to other wells. During three-year practice, there are 104 old wells in total receiving stimulating, with 11 thousand m3 /d increase for each well. By now, the adding volume of natural gas is about beyond 450 million m3 with the input-output ratio of 1:1.9, and expected to be 930 million m3 in the end. Sidetracking Horizontal Wells. Sidetracking horizontal wells consists of windowopening, sidetracking and directional deviation. It has several merits. Firstly, it is not only relatively lower in cost but also environment-friendly. Many devices of old wells such as wellbore, surface equipment and well site can continue to work in service. Due to the smaller size of wellbore, the amount of mud and cuttings which are harmful to environment is less than that of vertical or directional wells. Secondly, the implementation of sidetracking horizontal wells can further improve the existing well pattern, which is
66
P. Zhang et al. Table 2. Four types of Stimulating Untapped Reservoir.
Type
Sealing method
Production
Sealing lower and producing upper
Block the lower layer by squeezing cement or dropping plugs
Producing upper
Block the lower layer with multi-layer packers
Producing multi layers
Block the upper layer by filling sand and squeezing cement
Producing lower
Block the upper layer with multi-layer packers
Producing multi layers
Sealing middle and producing upper-lower
Block the middle layer by squeezing cement
Producing upper and lower
Sealing upper-lower and producing middle
Block the lower layer by Producing middle squeezing cement or dropping plugs, block the upper layer by filling sand and squeezing cement
Sealing upper and producing lower
conducive to the best utilization of remaining reserves. Its implementation has a reliable support from geology data such as regional sand body development, reservoir distribution and production [11, 12]. From early trial to now wide application, the sidetracking horizontal well has comprehensively grown in many aspects. In drilling technologies, opening window and speeding up for the small size wellbore have been mastered as well as trajectory controlling and functional mud. Technologies of geo-steering and geological deployment have also been maturing. Benefiting from merits above, the sidetracking horizontal well have dominated major measures of stimulating production and recovery improvement. Amid 2018, two sidetracking horizontal wells were finished with the accumulated output of 20 million m3 , about 17 thousand m3 /d added averagely. The input-output ratio is about 1:0.9. Fishing and Dropping Plugs. In bid to value the productivity of each layer, well testing is carried out on each layer from bottom to top in the exploration stages [13]. For some wells with more than one production layer, the most favorite layer has the priority of being developed while other layers are temperately isolated by plugs and then put into production by fishing in the later. For others with more than one layer opening together, the first thing is to figure out which layer the formation water comes from if large volume of formation water results in the closure of wells. Then dropping plugs to isolate the water layer can let the other layers produce normally. There are two kinds of plugs: removable and permanent. At present, the former, used in gas exploration wells, is mainly composed of anchoring mechanism, unsealing mechanism and sealing mechanism. And it can be drillable or fishable according to the unsealing method [14, 15]. The drillable plug is usually used to block the bottom production layer. Its unsealing can be easily realized through drilling or grinding plug by
Study and Application on Highly Effective Development Technology
67
screw grinding shoe or sleeve milling tools which are connected with oil pipe. However, the fishable plug, steel-made, is different in unsealing. It must be grasped and then lifted out of well by a special tool cutting off unsealing shear nail or unlocking the lock block. The operation has more difficulties which lead to problems such as time-consuming and low success rate. To tackle them, some process such as sand flushing and scraping are added to prevent plug from being stuck. In three years, there are 50 wells having seen their plugs fished or dropped. By now, about 268 million m3 gas has been harvested with daily output of 11 thousand m3 for each one. And its input-output ratio is about 1:4.2. The cumulative amount of natural gas will be expected to reach up to about 430 million m3 . Reservoir Dredging and Unblocking. The goal of reservoir dredging and unblocking is to solve the problem of reservoir seepage channel blockage. In the middle or late stage of gas wells, the reservoir is prone to be damaged by scaling and water, which resulting in the rapid decline or even shutdown of gas wells. The analysis shows that the reservoir damage feature of upper Paleozoic is different from that of lower Paleozoic. In order to revive gas wells, two different methods of reservoir dredging and unblocking are formed. For the water blocking in sandstone of upper Paleozoic, the damage can be canceled out by dredging and unlocking formation water near well zone. The carbonate reservoir of lower Paleozoic is prone to be blocked because its high-salinity formation water and high-content sulfide gas can result in scaling and corrosion easily. Its reservoir blockage can be removed by deep acid fracturing. For the tight sandstone reservoir of upper Paleozoic, its gas well production is negatively affected by many factors such as capillary force, interfacial tension. Those can make seepage channel in well zone occupied by formation water, resulting in the reduction of gaseous permeability. To evaluate water blocking on sandstone gas reservoir, comprehensive analysis on production and parameters is made as well as indoor simulating experiment. Then the standard for evaluating reservoir blocking damage is built through the APTi index model [16, 17]. The technology of reservoir water-locking relieve can be realized through a pump which injects surfactant into wellbore to reduce the water surface tension. As the injected surfactant decrease the minimum flow differential pressure and activation differential pressure, formation water near the well area will be discharged more easily, improving the seepage of reservoir and restoring the production of gas wells. After three years’ practice, 331 wells are successfully revived and the average daily output increases by 6 thousand m3 . The effect usually has a validation of from 3 to 6 months. In present the input-output ratio is 1:14.7 with the accumulative 326 million m3 increase. For wells of carbonate gas reservoir of lower Paleozoic, products of corrosion and scaling such as inorganic salt are readily formed and deposited within reservoir pores in the late stage of production. With these deposits blocking seepage channel, the production declines rapidly or even worse to zero, with casing pressure dropping suddenly. It is fundamental to make an all-round analysis on geological feature, reservoir sensitivity and plugging mechanism. In three years, the deep acid fracturing has been put into effect at 37 wells with 13 thousand m3 daily output increased averagely. The accumulative gas production has been up to 202 million m3 currently with 1:8 of the input-output ratio and will be expected to be 390 million m3 at last.
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P. Zhang et al.
3.2 Other Methods Besides reservoir stimulating methods above, there are other two methods: wellbore treatment and surface process updating (see Table 3). The former mainly solves wellbore problems such as sand depositing, casing corrosion, throttle failure. All of them can force gas wells to be closed [18, 19]. The latter includes two kinds of updating methods. When the closure of gas wells is caused by high content of hydrogen sulfide in natural gas, the normal production can be restored by installing desulfurization equipment at wellhead can eliminate or reduce the content of hydrogen sulfide [20]. For gas wells whose closure is brought about by unfitted process of the gas gathering station, it is common to updating the unfitted process from surface pipes to gas gathering station. Table 3. Principles of Wellbore Treatment and Surface Updating. Types
Problems
Stimulating Technology
Principles
wellbore treatment
sand depositing, wellbore effusion and blocking
coiled tubing sand flushing
using coiled tubing sand punching, gas lift, fishing and other processes to effectively eliminate wellbore faults
wellbore malfunction such as blocking, throttle failure of unable to salvage
workover
using workover with pressure or common workover of gas well overhaul to eliminate wellbore faults
unfitting production pipe column
optimized pipe column reproduction
take downhole operation to replace or optimize pipe column for unifying the diameter, and carry out drainage gas recovery such as plunger or speed pipe column
casing corrosion and scaling
wellbore chemical descaling
chemical descaling agent is used to react with dirt, and the gas-liquid are stirred to bring the scale out of wellbore
serious water flooding
reproduction of water flooded wells
using intermittent continuous gas lifting and auxiliary bubble drainage process with natural gas and nitrogen
throttle failure
difficult throttle fishing and processing
using heavy steel wire and special tools, or added flow channel through the pipeline, milling of coiled tubing
upper Paleozoic gas reservoir wells is caused by high content of hydrogen
desulfurization at wellhead
installing desulfurization equipment at wellhead can eliminate or reduce the content of hydrogen sulfide within a safe range
gas wells whose closure is brought about by unfitted process of the gas gathering station
comprehensive treatment of well group
updating the unfitted process from surface pipes to station
surface updating
Study and Application on Highly Effective Development Technology
69
4 Implementation Results 4.1 Overall Results In Changqing gas area, the technology of stimulating old wells has been widely applied to revive the production of 1197 wells from 2018 to 2020 (see Fig. 3). Until now, the total increased natural gas has been up to 4.5 billion m3 , equivalent to more than 3.6 million tons of petroleum. The increased daily output of natural gas is more than 6 million m3 . The whole decline rate of Changqing gas area has been reduced by more than 2% and its recovery rate has been improved by about 3–6%. The total investment during three years amounts to about RMB 610 million. So far the whole input-output ratio is 1:7.7. Thus the economic benefits are outstanding.
Fig. 3. Daily output of each year’s stimulated gas well since 2018.
The overall effect has increased steadily, and the economic benefits have improved year by year. From 2018 to 2020, the number of gas wells undertaking treatment is 310, 513, 376 respectively, which had produced 384 million m3 , 515 million m3 , and 452 million m3 natural gas in same year. The average daily output for each well increased from 7.8 thousand m3 in 2018 to 9 thousand m3 in 2020. The top daily production rose from 2.76 million m3 in 2018 to 3.26 million m3 in 2020. The input-output ratio of the same year climbed from 2.4 to 2.6 (see Fig. 4).
300
310
200
100
0
2018
2019
Time
2020
4.52 4
3.84
3
2
1
0
2018
2019
Time
2020
304
3.0
276
240
180
120
60
0
2018
0.9 4
300
The first year input-output ratio
1.0
326 3
3
8
376
5
The average daily gas increase in wells
360
2019
Time
2020
0.8
2.59
0.78
The first year input-output ratio
Number of wells
400
The maximum daily gas increase production
4
3
The first year cumulative gas production (10 m )
500
5.15
The average daily gas increase in wells (10 m )
The first year cumulative gas production 6
513
The maximum daily gas increase production (10 m )
The number of treatment wells 600
0.66 0.6
0.4
0.2
0.0
2018
2019
Time
2020
2.5
2.46
2.35
2.0
1.5
1.0
2018
2019
2020
Time
Fig. 4. Production indicators of gas wells with recovery measures from 2018 to 2020.
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P. Zhang et al.
4.2 Specific Result for Each Methods Among three stimulating technologies, wellbore treatment and reservoir stimulating have a great achievement in old wells. The former’s cumulative increased gas production has added up to 2.2 billion m3 , with the average daily production of each well increasing to 11 thousand m3 and its input-output ratio is 1:13.1. The latter’s cumulative increased gas production has added up to 2 billion m3 , with the average daily production of one well increasing to 8 thousand m3 and its input-output ratio is 1:5.6. However, the surface process updating performs worst. Its cumulative increased gas production has added up to 0.2 billion m3 , with the average daily production of one well increasing to 2 thousand m3 and its input-output ratio is 1:3.5 (see Fig. 5). Noticeably, every method has its own merits and faults. Reservoir stimulating benefits little in the first year with the input-output ratio is 1:1.5 due to its expensive and timeconsuming technologies such as stimulating untapped reservoir and fishing-dropping plugs, although it has increased as much as 580 million m3 gas. Wellbore treatment, increasing 640 million m3 gas and having the input-output ratio of 1:3.6 in the first year, is best in effect and benefits in a short period. Its main shortcoming is high frequent malfunction. With small investment and short implementation period, surface process updating has input-output ratio of 1:2.1, even if it has increased 120 million m3 gas.
1200
number of wells
20
The number of treatment wells The first year input-output ratio The current input-output ratio The predicted input-output ratio
16
14.9
13.1 900
12
8.6 600
5.6
4.2
3.6
300
524
455
Reservoir Stimulating Wellbore Treatment
4.2 4
3.5 2.1
1.5 0
8
7.7
6.5
input-output ratio
1500
218
1197
0
Surface Updating Stimulating for Old Wells
(a)
(a) Amount of treatment wells and input-output ratio 50.5 44.9
1.2
4
1.13 40
0.9
0.82
0.8
30
19.9
20
22.7
22.8
25.9 0.6
13.4 10
0
5.8
6.4
Reservoir Stimulating Wellbore Treatment
3
50
average daily gas increase (10 m /d)
1.5
The first year cumulative gas production The current cumulative gas production The predicted cumulative gas production The average daily gas increase in wells
8
3
cumulative gas production (10 m )
60
0.2 1.2 2.0 2.3
0.3
0.0
Surface Updating Stimulating for Old Wells
(b)
(b) Cumulative increased gas production and daily output
Fig. 5. Effect of four different measures.
Study and Application on Highly Effective Development Technology
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5 Conclusions and Suggestions Low-production wells have many causes involving reservoir quality, wellbore, and surface process. They can be classified into five groups: depleted formation energy, worse physical properties of reservoir, serious water flooding, wellbore malfunction, and unfitting production system. To revive normal production of those low-permeability gas wells, three kinds of stimulating and reviving technologies are put forth covering reservoir, wellbore, and surface production process. After three years of research and practice, three technologies has been used successfully in 1197 old wells. Until now, more than 4.5 billion m3 of natural gas has been obtained, equivalent to 360 million tons of oil. The input-output ratio is 1:7.7 with RMB 0.61 billion being invested. Each gas well has harvested more than 3.7 million m3 in total. The daily output of all gas wells amounts to more than 6 million m3. The whole decline rate of Changqing gas area has been reduced by more than 2% and its recovery rate has been improved by about 3–6%. The outstanding effects and benefits provide strong support to the effective and stable development of Changqing gas area. Acknowledgments. The project is supported by National Science and Technology Major Project “Demonstration Project for Development of Large-scale Low Permeability Lithological Reservoir in Ordos Basin” (Number 2016ZX005050).
References 1. Zhang, M., Wu, Z., Fan, Y., et al.: Development Technology and development prospect of low permeability gas reservoirs in Ordos Basin. Nat. Gas Ind. 31(7), 1–4 (2011) 2. He, J., Yu, H., He, G., et al.: Natural gas development prospect in Changqing gas province of the Ordos Basin. Nat. Gas Ind. 41(8), 23–33 (2021) 3. Ji, G., Jia, A., Meng, D., et al.: Technic strategies for effective development and gas recovery enhancement of a large tight gas field: a case study of Sulige gas field, Ordos Basin, NW China. Petrol. Explor. Dev. 46(3), 602–612 (2019) 4. Zhao, W., Jia, A., Wang, K., et al.: Theoretical and technological progress and development prospect of China’s natural gas exploration and development in the 13th five-year plan period. Petrol. Sci. Technol. Forum 40(3), 11–23 (2021) 5. Lu, T., Liu, Y., Wu, L., et al.: Difficulties and countermeasures for stable production of tight sandstone gas reservoirs in Sulige gas field, Ordos Basin. Nat. Gas Ind. 35(6), 43–52 (2015) 6. Feng, Q., Li, J., Wei, M., et al.: Differentiated management strategies on low-yield and lowefficiency wells in the Sulige Gas Field, Ordos Basin. Nat. Gas Ind. 36(11), 28–36 (2016) 7. Zhao, Y.: Analysis of wellbore liquid accumulation in low production and low-pressure gas wells. Nei Jiang Ke Ji 39(5), 74–75 (2018) 8. Zhang, Q., Wang, J., Wang, X., et al.: Research checking layer and patching perforation technology in Neopaleozoic reservoir of Jingbian gas field. Petrochem. Ind. Appl. 31(8), 74–86 (2012) 9. Yang, S., Liu, Q., Yang, F., et al.: Research and application of stimulation technology with offensive measures for low-yield gas wells in the Sulige Gas Field. Inner Mongolia Peterochem. 12, 101–102 (2018) 10. Huang, Y., Jiang, C., Wang, S., et al.: Impact of crossflow to replenished fractures in wells with depleted fractures and remedial measures. Petrochem. Ind. Appl. 39(8), 68–72 (2020)
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11. Zhang, J., Wang, G., He, K., et al.: Practice and understanding of sidetracking horizontal drilling technology in old wells in Sulige Gas Field. Petrol. Explor. Dev. 46(2), 370–377 (2019) 12. Sun, N.: Sidetracking horizontal well to become important technological scheme for stimulation of low-yield oil and gas wells in old areas. Petrol. Sci. Technol. Forum 2, 28–35 (2018) 13. Wang, S., Huang, Y., Hu, D.: Study and application on the fishing and milling technology of layer-sealing bridge plugs in gas exploration wells. China Petrol. Mach. 49(1), 41–46, 52 (2021) 14. Xu, J.: Development and application of retrievable bridge plugs. Oil Drill. Prod. Technol. 31(3), 114–118 (2009) 15. Fu, G., Zhang, S., Xu, Y., et al.: Separate layer fracturing technology testing with retrievable bridge plug. Drill. Prod. Technol. 25(5), 44–46 (2002) 16. Yang, Y.: Study of water locking damage mechanism and water unlocking of low permeability reservoir. J. Southw. Petrol. Univ. (Sci. Technol. Edn.) 35(3), 137–141 (2013) 17. Zhao, C., Li, W., Zhang, Y., et al.: Damage mechanism and prevention methods analysis of low permeability gas reservoir water blocking. Fault Block Oil Gas Field 11(3), 45–46 (2004) 18. Ye, X., Zhang, P., Wei, M., et al.: The research on descaling method and effect analysis of on-site testing in natural gas well. Petrochem. Ind. Appl. 38(6), 66–71 (2019) 19. Song, H., Feng, P., Xiang, M., et al.: Research on reasonable fishing time of downhole choke in Sulige gas field. In: 10th Ningxia Young Scientists Forum Proceedings on Proceedings, Yinchuan, pp. 207–213 (2014) 20. Zhang, Y., Zhu, L., Li, X., et al.: Research on triazine liquid desulfurization technology in natural-gas well. Petrochem. Ind. Appl. 38(5), 79–84 (2019)
The Downhole Wireless Monitoring in Well Testing Xiong Han(B) , Dong-xiao Pang, Zhi-lin Li, Hu Deng, and Qiu-yun He CCDC Drilling and Production Technology Research Institute, Guanghan, Sichuan, China [email protected]
Abstract. In order to improve the safety, precision and controllability of well testing in the complex deep wells and shale gas wells, The downhole Wireless monitoring platform, which is based on wireless transmission technology, sensor technology and expert system, is built to communicate the downhole and the surface. Specifically, the downhole well testing data are acquired through analysis by the expert system after the data are transmitted in form of wireless electricmagnetic waves from downhole transmitter to the receiving antenna on ground surface through composite downhole media. In the well testing period, on the one hand it can real-time get the temperature and pressure data of the down hole and other data in order to grasp the downhole situation, on the other hand downward signals from surface can be used to control downhole devices, for example dynamically adjusting the operating procedures. So it can benefit for reducing security risks and improving the quality of well testing data acquired and others. The wireless transmission system adopts the mode of “One Signal-transmitter + N Signal-repeater” and Signal transmission frequency is below 50 Hz, with effective transmission distance of Signal Transmitter 2500–3500 m and SignalRepeater 1500–2000 m. The system technical capacity is that the theoretical transmission distance can reach 5000–7000 m (N equals 2 or 3), with data transmission rate of 12bit/s, temperature resistance of 177 °C, pressure resistance of 140 MPa and more than 30 days of sustainable work. The expert system is mainly composed of the Ground Antenna and the Analysis Platform, and the recognizable signal resolution of the expert system reaches 10−5 V by the suppression of “power frequency” interference on the ground. Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 73–81, 2023. https://doi.org/10.1007/978-981-99-2649-7_7
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X. Han et al. At present, the technology has been successfully applied for well testing more than 20 wells in Sichuan Province of China in the different conditions such as drifting, scraping, acidizing, flowback and, pressure-recovery and other operations to realize the data interconnection of the downhole and the surface. In Field application, the maximum well depth reaches 5050 m, the continuous working time is more than 478 h. It proved the feasibility and reliability of the technology, having a very good application prospects. Keywords: Downhole monitoring · Well Testing · Wireless
1 Introduction With the development of oil and gas exploration, complex deep reservoir and unconventional reservoir have become a focus. In the complex deep wells, For example, in Tarim and Sichuan areas, the depth of some wells can reach 8000 m, with the formation temperature over 210 °C, the formation pressure over 140 MPa, the downhole acidizing pressure close to 200 MPa, and the wellhead shut in pressure up to 110 MPa, which are a great challenge to the wellbore in well testing and completion operation. In shale gas wells, the fracturing is the scale of “thousands of tons of sand, thousands of cubic meters of liquid”, and the large amount of liquid is continuously returned in the later stage, with the serious wellbore environment. In order to ensure the smooth implementation of the wellbore operation, it is necessary to establish a digital wellbore based on real-time monitoring of wellbore conditions. It is an information platform for communication between the underground and the ground through wireless ways during well testing, providing a pair of eyes for engineers to see the underground situation [1–4]. Firstly, it can monitor the downhole construction process in real time (such as perforating, acid fracturing, drainage operation, etc.) and feed back the real situation at the bottom of the well, so as to ensure the accuracy and effectiveness of on-site operation decision-making. Secondly, the pressure recovery data and other data during the test can be obtained in advance, greatly improving the efficiency of oil test. Lastly, when the downhole is complex and the stored downhole pressure gauge can’t get out of the ground, it can ensure the normal acquisition of the well testing data, avoiding the secondary well testing operation and saving the cost. The challenge of the application of digital wellbore technology in Tarim and Sichuan areas lies in the following points. Firstly, ultra deep wellbore length, complex downhole media, irregular transmission framework, and high impedance environment in the confined space of tubing and casing cause sharp attenuation of wireless signal, which becomes the technical bottleneck of long-distance transmission of downhole signal. Secondly, It is difficult to work stably for a long time because of the huge influence of temperature about the performance of signal transmitting element. Thirdly, because Ground EMI is 1000 times the signal strength, how to suppress the influence of noise, and accurately extract useful signals is a great challenge. Therefore, it is necessary to make breakthroughs in the design of wireless transmission antenna, the design of high temperature resistant circuit board, and the development of ground receiving system, so that it can be reliably used in the field.
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2 The Components of the Digital Wellbore The digital wellbore of well testing combines wireless transmission system, sensor system, expert system and others, to build a information platform for downhole and surface communication (As shown in Fig. 1). The wireless transmission system consists of Signal-transmitter and Signal-repeater, the senor system consists of electronic pressure sensor and load sensor, etc., and the Expert system consists of the ground antenna and analysis platform. The data from electronic pressure sensor and load sensor is converted into electromagnetic wave signals, then are sent up the wellbore by the generator. At the same time, the generator receives the orders from the ground to adjust its working state. The Signal-repeater is mainly used to amplify the signal to extend the communication distance. The expert system is mainly used to analyze the downhole data and also send order to the downhole according to the needs of the operator, for example, opening the downhole valve. During well testing, Field Engineers can master the bottom of the well in real time, and realize dynamic adjustment of testing procedures, so as to improve the quality of test data acquisition and timely discover downhole abnormalities for reducing risks.
Fig. 1. The Schematic diagram of digital wellbore
2.1 Wireless Transmission System Based on the low-frequency electromagnetic wave transmission having the characteristics of slow attenuation, the underground low-frequency electromagnetic wave transmitting antenna is built with transmitter, tubing and casing and transition frequency is below 50 Hz [5–8]. As shown in Fig. 2, a is tubing, b is resistance, c is casing, d is formation and f is transmitter. In order to make the signal transmission more stable and reliable, a repeater is used in the system. Transmitter signal strength is 0.1 mv about at 3000 m and 0.01 mv about at 4500 m, therefore, the reliable transmission distance of
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the transmitter is 2500–3500 m. The reliable transmission distance of Signal-Repeater is 1500–2500 m. In order to improve the transmission distance, multiple repeater schemes are adopted. The system technical capacity is that the theoretical transmission distance can reach 5000–7000 m (using 2 or 3 repeaters), with data transmission rate of 12 bit/s.
Fig. 2. Wireless transmission model
Because the Repeater not only transmits data signals from the downhole, but also transmits order signals from the wellhead (Fig. 3). In order to prevent the errors in signal identification, it need to stipulate the transmission protocol for these signals. Specifically, Frequency-Division-Multiplexing is used between the data signals from the downhole and the order signals from the wellhead [9–12]. While Time-Tivision-Multiplexing is used between the repeater signal and transmitter signal, that means Repeater signal and transmitter work in different time periods to avoid interference of the same signal on two devices [13–15].
Fig. 3. The principle of wireless transmission technology
2.2 Downhole Sensor and Circuit The downhole sensor is the eye to identify the downhole working condition, and the downhole circuit board is the tool to convert the sensor signal [16]. In the deep well
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environment, the formation temperature can usually reach 177 °C [17]. The sensor and circuit board components are mostly semiconductor materials, and the performance is greatly affected by high temperature [18]. Based on the optimization of electronic components, the power-reduction design of system modules and the optimization of hot spot distribution are carried out to avoid the large temperature rise caused by the heat shielding of components. Based on the engineering requirements, the indicators of downhole sensor and circuit shall be at least that the temperature resistance is more than 177 °C (Fig. 4), quake resistance reaches 5G, stable working time is more than 720 h in order to match the well testing time, and accuracy of data acquired by sensors is more than 0.025% F.S in order to meet the data analysis requirements.
200 160 120 80 40 0 Simulated wellbore pressure
MPa
Simulated wellbore temperature
Fig. 4. Circuit board high temperature resistance test (177 °C)
2.3 The Expert System The ground receiving antenna is installed at the wellhead. When the signals are received, it is handed over to the ground analysis platform, and the weak signal is extracted by filtering technology, which can realize 10 uv level signal from Environmental EMI intensity of 100000 uv [19, 20]. The filtering technology is based on the method of power frequency interference parameter estimation. Firstly, the received signal is transformed in frequency domain, and the interference components of power frequency harmonics are searched in frequency domain. In other words, Calculating power frequency interference parameters near the frequency f = 50 kHz (n = 1, 2, 3…). Then, the power frequency interference is reconstructed according to these parameters, and the interference signal is subtracted from the received signal, As shown in Fig. 5. Then the signal are demodulated to the downhole actual data, displayed on screen. The ground visualization interface is shown as the Fig. 6 that the whole interface can be divided into nine areas, including receiving parameter setting, synchronization parameter setting, transmission parameter setting, control indication area, receiving parameter, parameter value display, waveform area, demodulation frame structure and error output area. After knowing the downhole situation, the Engineer shall timely adjust the parameters of well testing operation to ensure the safety and efficiency. Experiment.
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Fig. 5. Small signal recognition effects
Fig. 6. Visual expert interface
3 Field Experimentation Setup The field experiment of digital wellbore was carried out in Hechuan area of Sichuan Province (Fig. 7). The completed drilling depth of HT-X is about 5800 m, and the artificial bottom hole is about 5700 m. At the experimental site, the transmitter and one repeater are lowered into the wellbore along with the tubing. The transmitter is placed at a depth of 4200 m and the repeater is placed at a depth of 1800 m. At the beginning of tool entering the well, the engineer will use the data transmitted from the well to the surface to monitor the situation of the wellbore, for example acidizing, blowout and fluid discharge, the recovery of shut in pressure, for making favorable decisions in time, and improving the operation efficiency. In order to verify the accuracy of the data obtained by wireless, the engineer designed the following scheme: the underground electronic pressure gauge is installed near the transmitter, when the well testing operation is completed, all tools are lifted out of wellbore, it reads the data of the underground electronic pressure gauge, and compare with the data obtained by wireless.
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Well depth structure: 178 mm[0–5350 m] + 127 mm[5340–5800 m].
Fig. 7. HT-X well number wellbore test site
4 Results The communication depth of signal in HT-X actually reaches 4200 m, realizing the monitoring of drifting, scraping, acidizing, flowback and, pressure-recovery and other operations. The signal strength received on the ground is greater than 5 × 10−5 v. In addition, although the transmitter is deep, it can occasionally receive a small amount of signal on the ground, but the signal is extremely weak (Fig. 8). Monitoring data shows the downhole maximum temperature is 116.79 °C and the downhole maximum pressure is 108.82 MPa. The downhole data obtained by wireless transmission is consistent with the data of electronic pressure gauge, which shows the reliability of digital wellbore technology (Fig. 9). By now, 20 field applications have been carried out, for example M-X, HT-X and GS-X wells, eg. The maximum depth of signal transmission is 5050 m, the maximum application time is 478 h, and the maximum temperature is 149.48 °C.
Fig. 8. Relationship between signal strength and wellbore depth
Fig. 9. Read downhole working condition data in real
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5 Conclusions Combine sensor technology, wireless transmission technology, expert system and other technologies to build a digital wellbore information platform for downhole and surface communication. During well testing, the field engineer can master the downhole situation in real time, realize dynamic adjustment of the test procedure, improve the quality of test data acquisition and reduce the safety wind Risk. Using the underground string and transmitter to build the underground low-frequency electromagnetic wave transmitting antenna, and through the repeater, the difficulty of long-distance signal transmission is solved. Based on the system module power reduction design and hot spot distribution optimization, the problem of large temperature rise caused by the heat shielding of components is solved. The circuit board can meet the environment temperature below 177 °C, but the circuit board with temperature resistance over 177 °C still needs to be developed. For citations of references, we prefer the use of square brackets and consecutive numbers. Citations using labels or the author/year convention are also acceptable. The following bibliography provides a sample reference list with entries for journal articles [1], an LNCS chapter [2], a book [3], proceedings without editors [4], as well as a URL [5]. Acknowledgments. The project is supported by China Petroleum Science and Technology Project (Number 2018E-2104).
References 1. Lu, Q., Cai, J., Zhang, W.: Application of APR well test technology in exploration well of Sininan Dengying formation. Well Test. 25(6), 34–37 (2016) 2. Wen, J., Lin, Y., Pan, D.: Application of block-acidification-test-completion integrated pipe string in Double Exploration 2 Well. Well Test. 25(6), 46–48 (2016) 3. Liu, F., He, Q., Xiao, J.: Development situation of surface read-out technology of down-hole test data. Drill. Prod. Technol. 34(4), 48–51 (2013) 4. Han, X., Pang, D., Liu, F.: Research on direct reading technology of underground wireless data and its application. Well Test. 25(6), 61–63 (2016) 5. Vinegar, H.J., et al.: Permanent downhole, wireless, two-way telemetry backbone using redundant repeaters. U.S. Patent 6958704 B2, October 25 (2005) 6. Harrington, R.F.: Time-Harmonic Electromagnetic Fields. McGraw-Hill, New York (1961) 7. Vong, P.K., Rodger, D., Marshall, A.: Modeling an electromagnetic telemetry system for signal transmission in oil fields. IEEE Trans. Magnet. 41(5), 2008–2011 (2005) 8. Holloway, C., Hill, D., Dalke, R., Hufford, G.: Radio wave propagation characteristics in lossy circular waveguides such as tunnels, mine shafts, and boreholes. IEEE Trans. Antennas Propagation 48(9), 1354–1366 (2000) 9. Shao, Z., Wei, J., Pan, X., Cheng, X., Wang, Z., Li, L.: Application effect analysis of surface direct reading well testing technology in flowing wells and mechanical production wells in Linhe Oilfield. Well Test. (04) (2022) 10. Bai, H., Wang, C., Lin, Q., Zhang, L.: Study on acoustic attenuation characteristics of oil well remote wireless communication. J. Liaoning Univ. Petrochem. Technol. (03) (2022)
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11. Jiang, H., Li, D., Wang, B., Meng, L., Zhang, L.: Study on data transmission mechanism in water injection pipe of triangular monopole antenna. Petrol. Mach. (07) (2021) 12. Chen, Z., et al.: Application status and development prospect of intelligent separate injection technology in Bohai Oilfield. Liaoning Chem. Ind. Co. Ltd. (05) (2021) 13. Zhang, Y., Zhao, K., Wang, P., Sun, R., Ruan, X.: Application of low frequency electromagnetic wave wireless transmission testing technology in complex fault block reservoirs in Abei Sag. Petrol. Drill. Prod. Technol. (03) (2021) 14. Liu, B.: Daqing Oilfield cable direct reading technology under pressure. Well Test. (01) (2021) 15. Liu, C., Hu, H., Chen, Q., Li, H., Pang, D., Wang, Q.: Research on a new long-distance wireless two-way communication detection system. Electr. Meas. Instrum. (15) (2020) 16. Zheng, L., Wang, Z.: Simulation study on acoustic wireless communication technology under oil wells. Internet Things Technol. (12) (2019) 17. Lu, Z., Fan, B., Feng, W., Liu, J.: Development and application of underground short distance wireless data transmission system. Petrol. Drill. Prod. Technol. (S1) (2018) 18. Ruan, H.: Overview of intelligent water injection technology. Neijiang Sci. Technol. Co. Ltd. (11) (2018) 19. International Data Corporation (IDC) Horizontal Well Report - May 1999 (1999) 20. Saltuklaroglu, M.: Mobil’s SAGD experience at Celtic, Saskatchewan. In: Petroleum Society Paper CIM 99-25, Case Study No. 13, Presented at the 50th Annual Technical Meeting of the Petroleum Society, Calgary, AB, 14–18 June 1999 (1999)
Study on Slippage Effect and Stress Sensitivity of Tight Sandstone Heng-yang Wang(B) China University of Petroleum, Beijing, Beijing, China [email protected]
Abstract. In this paper, tight sandstone core obtained by closed coring in Shengli Oilfield was taken as the experimental sample, and the conventional core clamping system was used. In order to study slippage effect and stress sensitivity of tight sandstone, this paper changed the confining pressure applied to the core holder and the displacement pressure of the displacement pump, which had an impact on the flow of the flowmeter at the outlet, and calculated the gas permeability of the core under different pressures. The results showed that the relationship between the average gas pore pressure and gas permeability of tight sandstone was more in line with the quadratic curve equation, which could be corrected by the quadratic curve equation. The gas permeability decreased with the increase of effective stress, and the change trend was consistent with the change trend of power function. Keywords: Tight Sandstone · Gas Permeability · Slippage Effect · Stress Sensitivity
1 Introduction Tight sandstone gas reservoir is widely distributed and rich in resources, which is an important field of natural gas exploration and development [1–4]. However, due to the complex rock mineral composition and pore structure of tight reservoir, the slippage Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the 2022 International Petroleum and Petrochemical Technology Conference in Chengdu, China from 9 to 11 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submit-ted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 82–89, 2023. https://doi.org/10.1007/978-981-99-2649-7_8
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effect and stress sensitivity of reservoir permeability appear in the process of developing natural gas resources. So far, many researchers have studied the slippage effect and stress sensitivity of tight sandstone. Through a series of sandstone gas flow and permeability tests under confining pressure and pore pressure, Wang huanling et al. [5] proved that there is slippage effect in tight sandstone gas flow, and its seepage does not comply with Darcy’s law. Wang Yongzheng et al. [6] used equivalent fluid permeability as a parameter to evaluate the stress sensitivity of the reservoir, eliminating the influence of gas slippage effect on the experimental results, and analyzed the influence of stress sensitivity on productivity in combination with plane radial flow theory. Cao Qian et al. [7] used unsteady state method to measure helium permeability under three conditions of fixed confining pressure, internal pressure and effective stress. Based on the analysis of slippage effect and effective stress, the coupling control effect of them on the permeability change of fractured tight sandstone gas was discussed. Li Xiaoping et al. [8] verified the reliability of the established apparent permeability model based on experimental and LBM simulation data, and analyzed the influence of various factors on the apparent permeability of shale matrix. Liming et al. [9] deduced an improved power-law permeability model to evaluate the permeability stress sensitivity of tight sandstone reservoir, which is helpful to the improvement of reservoir simulator. In this paper, the tight sandstone core of Shengli Oilfield was used as experimental material to study the influence of gas slippage effect and stress sensitivity on gas logging permeability of tight sandstone core. The experimental results had guiding significance for the exploration and development of tight sandstone gas reservoir.
2 Experimental Scheme Taking the tight sandstone core obtained by closed coring in Shengli Oilfield as the sample, the core clamping replacement system was adopted, and the confining pressure was applied to simulate the formation overburden pressure. The experimental temperature was room temperature, and the experimental fluid was high-purity nitrogen. During the experiment, the nitrogen in the nitrogen cylinder was first delivered to the piston container for pressurization, and then controlled by the pressure regulating valve to make the inlet pressure range of the core between 0.01–5 MPa. The outlet pressure was atmospheric pressure. The experimental flow chart is shown in Fig. 1. During the experiment, the gas pore pressure was gradually increased for each stage of confining pressure, and the gas flow through the core was measured by flowmeter. When the reading of the flowmeter was stable, recorded the reading at this time and calculated the gas measurement permeability under the pore pressure. The calculation formula is: Kg =
2Q0 p0 μL × 100 A p12 − p22
(1)
where Kg is gas permeability, ×10−3 μm2 ; p0 is atmospheric pressure, MPa; A is core cross-sectional area, cm2 ; µ is gas viscosity, mPa * s; L is core length, cm; p1 and p2 are the absolute pressure on the inlet and outlet sections respectively, MPa (Table 1).
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Fig. 1. Experimental flow of core permeability test Table 1. Loading scheme of tight sandstone samples Experimental purpose
Pore pressure/MPa
Confining pressure/MPa
Study on slippage effect
0.5, 0.9, 1.3, 1.7, 2.1, 2.5, 2.9, 3.3
2, 4, 6, 8
Study on stress sensitivity
1.9
2, 4, 6, 8
3 Study on Gas Slippage Effect The existence of gas slippage effect makes the gas permeability greater than the liquid permeability. In 1941, Klinkenberg gave the mathematical expression of gas measurement permeability of gas slippage effect: b (2) Kg = K∞ 1 + pm where Kg is gas permeability; K∞ is absolute permeability; pm is average pressure at core inlet and outlet, pm = (p1 + p2 )/2; b is slippage factor. With the deepening of research, the researchers found that the flow of gas in tight rock core may not completely follow Klinkenberg’s linear equation, which can be described by higher-order equation, and gave the quadratic permeability correction equation [10]: b e (3) Kg = K∞ 1 + + 2 pm pm where e is quadratic slippage coefficient, which is related to temperature, gas type and pore structure of porous medium. According to the loading scheme of experimental samples, we got the gas permeability under different pore pressure, and got the relationship between gas permeability and
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the reciprocal of average pore pressure. Figure 2 and Fig. 3 are the fitting diagrams of the linear and quadratic equations of average gas pore pressure and permeability respectively; Table 2 and Table 3 show the fitting results of the linear and quadratic equations of average gas pore pressure and permeability.
Fig. 2. Linear equation fitting between average gas pore pressure and permeability
Table 2. Linear fitting results of sandstone Confining pressure/MPa
Fitting formula
2
Kg =
0.0964 1 + 0.9889 pm
Absolute permeability/× 103 µm2
Slippage factor/MPa
Correlation coefficient
0.0964
0.9889
0.979
4
Kg =
0.0561
0.1301
0.915
6
Kg =
0.0501
0.0738
0.817
8
Kg =
0.0453
0.0645
0.763
0.0561 1 + 0.1301 pm 0.0501 1 + 0.0738 pm 0.0453 1 + 0.0645 pm
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Fig. 3. Quadratic equation fitting between average gas pore pressure and permeability
Table 3. Quadratic fitting results of sandstone Confining pressure/MPa
Fitting formula
Absolute permeability/× 103 µm2
Slippage factor/MPa
Correlation coefficient
2
Kg =
0.0923
0.1679
0.994
0.0517
0.2650
0.922
0.0445
0.2674
0.973
0.0402
0.2587
0.954
0.0166 0.0923 1 + 0.1679 2 pm − pm
4
Kg =
0.0329 0.0517 1 + 0.2650 2 pm − pm
6
Kg =
0.0445 0.0445 1 + 0.2674 2 pm − pm
8
Kg =
0.0472 0.0402 1 + 0.2587 2 pm −
pm
Through the fitting of the two equations, the fitting degree of the linear equation was relatively low, and the average correlation coefficient was about 0.869. The fitting degree of quadratic equation was better, and the average correlation coefficient was about 0.961. Therefore, for tight sandstone, it is reasonable to use quadratic curve equation to correct gas logging permeability.
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4 Study on Stress Sensitivity Stress sensitivity refers to the increase of effective stress on rock, the deformation of rock skeleton particles and fracture end face, and then the change of permeability. The calculation formula of effective stress is: σe = pc − αpm
(4)
where σe is effective stress, MPa; pc is confining pressure, MPa; pm is average pore pressure, MPa; α is Biot coefficient, take 1 here. In order to study the stress sensitivity of tight sandstone, we tested the gas permeability of tight sandstone cores S-1, S-2 and S-3 under different effective stresses according to the experimental scheme. The parameters of tight sandstone core are shown in Table 4, and the experimental results are shown in Fig. 4. Table 4. Physical parameters of tight sandstone core Core sample
S-1
S-2
S-3
Length/mm
51.01
49.87
52.10
Diameter/mm
24.89
24.95
24.91
3.05
4.49
5.01
Porosity/%
Fig. 4. Stress sensitivity test results
It can be seen from Fig. 4 that the gas permeability decreased with the increase of effective stress, which was due to the increase of effective stress, the closure of micro fractures in tight sandstone core and the decrease of micropore volume.
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In order to further study the relationship between effective stress and permeability, we fit the gas measured permeability obtained from the experiment with power function, and the equation is as follows: Kg = MPc−N
(5)
where M and N are fitting constant. Table 5 shows the fitting results and fitting correlation coefficients of power function on gas measurement permeability. We found that the fitting correlation coefficients of power function on gas permeability were greater than 0.98, and the fitting effect was good, indicating that the change trend of gas measurement permeability was consistent with that of power function. Table 5. Permeability fitting results of power function Core sample M
N
Correlation coefficient
S-1
0.0639 0.359 0.988
S-2
0.0828 0.339 0.995
S-3
0.1141 0.401 0.993
5 Conclusion (1) The relationship between average gas pore pressure and gas logging permeability of tight sandstone was more in line with the quadratic curve equation. In order to eliminate the influence of slippage, the quadratic curve equation could be used for correction. (2) The gas permeability decreased with the increase of effective stress, and the change trend was consistent with the change trend of power function.
References 1. Zhao, J., Liu, J., Zhang, Q., Qu, X.: Review of geophysical exploration methods and technologies for tight sandstone gas reservoirs. Adv. Geophys. 32(02), 840–848 (2017) 2. Li, Y., et al.: Statistical analysis of parameters of global tight sandstone gas basins. Nat. Gas Geosci. 28(06), 952–964 (2017) 3. Jia, C., Zheng, M., Zhang, Y.: Unconventional hydrocar-bon resources in China and the prospect of exploration and development. Petrol. Explor. Dev. 39(2), 129–136 (2012) 4. Li, H.: Enlightenment of unconventional oil and gas exploration at home and abroad to peripheral basins of Daqing. Zhejiang University (2012) 5. Wang, H., Xu, W., Chao, Z., Kong, Q.: Experimental study on slippage effects of gas flow in compact rock. Chin. J. Geotech. Eng. 38(05), 777–785 (2016) 6. Wang, Y., Zhang, R., Song, F.: Stress sensitivity evaluation of tight sandstone reservoir to eliminate slippage effect. Sci. Technol. Eng. 17(17), 221–226 (2017)
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7. Cao, Q., Gong, Y., Fan, T.: The effect of pressure variation on gas permeability in fractured tight sandstone reservoir. Sci. Technol. Eng. 18(26), 60–67 (2018) 8. Li, X., Liu, S., Li, J., et al.: Apparent gas permeability model of shale matrix coupling stress sensitivity and water saturation. Nat. Gas Geosci. 32(6), 861–870 (2021) 9. Li, M., Ou, F., Ian, Y., Li, M., Wang, J.: Establishment and verification of stress-sensitive model for tight sandstone reservoirs. Oil Gas Explor. Dev. 39(06), 75–81 (2021) 10. Tang, G.H., Tao, W.Q., He, Y.L.: Gas slippage effect on microscale porous flow using the lattice Boltzmann method. Phys. Rev. E 72, 056301–056308 (2005)
Study on Ground Simulation Test Design Method for Multi-pulse Fracturing of Coal-Bed Methane Jin-jun Wu1,2(B) , Jing Liu1 , Jun-rui Duan1,2 , Ren-jie Zhang1 , and Kai Wang1 1 Xi’an Shiyou University, Xi’an, China
[email protected] 2 High Energy Gas Fracturing Sub-room, Key Laboratory of Oil and Gas Reservoir
Reconstruction, CNPC, Beijing, China
Abstract. The mechanical properties of conventional simulated cement target is very different from coal-bed methane. However, if large size coal rock is directly used for the ground test of multi-pulse fracturing, the coal rock will be completely broken and the formation state of multiple fractures cannot be observed. We studied and designed the simulation test method of CBM coal rock coated with cement target. It mainly includes coal rock coal sample, coated cement layer, multi-pulse test device and test system, etc. The formation state of multiple cracks in coal rock can be obviously observed by firing range test, and P-T curve can be measured. It provides a new experimental method for the study of multi-pulse fracturing mechanism of low permeability coal-bed methane. Keywords: Coal-bed methane · Multi-pulse fracturing · Simulation test · Design method
1 Introduction Cement target or rock test is generally used in ground simulation test of high-energy gas fracturing [1, 2]. Due to the different mechanical and geological characteristics between Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 90–95, 2023. https://doi.org/10.1007/978-981-99-2649-7_9
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cement target and underground reservoir, the experimental results are different from the fracturing results in real reservoir environment [3, 4]. In particular, the difference is greater in the similar test of multi-pulse fracturing of coal-bed methane [5]. However, ground tests of multi-pulse fracturing with large size coal and rock without sealing and confining pressure will lead to complete fracture of coal and rock, and the formation state of multi-fractures cannot be observed [6, 7]. Therefore, we studied and designed a simulation target test method of CBM coal rock coated in cement target. The formation state of multiple cracks can be obviously observed through the range test, and the complete P-T curve can be tested. It provides a new experimental design method for the study of multi-pulse fracturing mechanism of low permeability coal-bed methane.
2 Test Purpose and Design Principle The purpose of this experiment is to study and explore the mechanism of multi-fractures in coal-bed methane fracturing caused by multi-pulse high-energy gas fracturing [8, 9]. It provides a new technical approach and research direction for CBM fracturing development [10–12]. Design principle: A simulation test target of large size coal - rock cladding embedded in cement target was designed. Such as Fig. 1. It mainly includes coal rock coal sample, coated cement layer, multi-pulse test device and test system, etc. By screening CBM coal samples and combining with the lithology of coal seam strata, the coated cement target is designed, and the multi-pulse fracturing charging structure and P-T test system matching its parameters are designed. The ground simulation test system was formed in the shooting range to complete the general test. The generation and formation process of multiple cracks and test analysis of observation test target were studied. This paper analyzes the mechanism of multi-pulse fracturing of coal-bed
Fig. 1. Multi-pulse fracturing simulation test of coal-bed methane
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methane and develops new techniques and theoretical methods suitable for fracturing development of coal-bed methane [13–15].
3 Design of Test Scheme 3.1 Test Main Material Coated cement target: The coated cement target layer is made according to the specification for making concrete target for perforating detection in oil and gas Wells in “SY/5891.1-1999”. Curing 28 days, meet the test requirements. Multi-pulse gas fracturing structure [16, 17]: Design machining center pipes, fracturing drugs, auxiliary drugs, etc. Test system: Pressure sensor, portable computer, temperature test block. Preparation of auxiliary materials: Detonating instrument, detonating wire, sealing ring and tools [18]. 3.2 Cement Target Design and Production Multi - pulse fracturing test was carried out by using cement - coated coal sample. The production of cement target layer is in accordance with “SY/5891.1-1999” concrete target production specifications. Coal-bed methane samples from Jincheng were used: test A: 450 × 240 × 200 mm; test B: 430 × 130 × 220 mm. Determine the coal sample of CBM. Generally, the size of coal sample is not less than 300 × 100 × 200 mm. Screening the material ratio composition of coated cement target. Cement used for targets: The dry river sand: The water mass ratio is 0.8–1.5:1.5–2.5:0.4–0.6. The target thickness of coal sample coated cement is 300–600 mm. During the simulation target pouring, CBM coal samples are coated and embedded in large cement simulation target. Mark the threedimensional position of coal sample in cement target. Cement target pouring molding after curing 28 days. 3.3 Test Propellant Design According to the above calculation and experience, ϕ6 × 242 mm compound propellant was adopted. The high burning rate compound propellant can react quickly to form high temperature and high pressure gas in the steel tube cavity, which is released to the cement target coal rock and coal sample target from the pre-designed reserved hole, first to the coal rock and then to the cement target, forming cracks [19, 20]. 3.4 Test Method The multi-pulse fracturing unit is placed in the concrete target. After centering, add sealant to annulus at both ends for sealing [21]. Then the concrete target and fracturing device are lowered into the foundation pit used in the test. After connecting the foot line, tighten the upper end cover. After evacuating, detonate and observe.
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4 Test Steps This final assembly test includes coal rock coal sample coated cement target, multi-pulse test device, test device system and other parts of the design. The preparation of the test process is more complicated. After completing the machining design test of each part of the test respectively. Determine the division of labor, prepare the test site and time of the range. Complete the whole test work after the general assembly and debugging in the test range. The detailed test procedure is not described here.
5 Test Results and Analysis After initiation, cement target cracking was observed to basically form 3–5 cracks. The crack trend basically extends along the reserved channel direction and other directions. P-t curve measured by test system device (Fig. 2): The peak pressure is 30 MPa and the acting time is 60 ms. It completely reflects the generation and fracture formation process of multi-pulse fracturing of coal samples. To provide strong experimental support for further research on the mechanism of action.
Fig. 2. Multi-pulse fracturing p-T test curve of coal samples
3–5 cracks are clear and regular after the coated cement target test. The coated coal rock is not broken. Fracture interface reflection is very clear (Fig. 3). The complete P-T curve reflects the dynamic action process of pressure with time. The experimental design method proves that multi-pulse fracturing can produce fractures in coal rock. It also shows that multiple fractures can be randomly generated in coal seam by multi-pulse fracturing of high energy gas in coal-bed methane well. It creates favorable conditions for the desorption of natural gas in coal reservoir.
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Fig. 3. Spot effects
Using CBM coal-rock cladding type simulated cement target can also replace infinite CBM coal-rock to form multiple fractures (High Cost). Simulate a more realistic reservoir environment. This test method has important guiding significance for the study of formation and propagation of multi-fracture produced by multi-pulse fracturing of coal-bed methane.
References 1. Wu, J., Wu, J., Zhou, P., Li, X.-X.: Multiple pulse fracturing for low permeability coal seam development feasibility analysis. J. Coal Technol. 4(12), 135–138 (2017). https://doi.org/10. 13301/j.carolcarrollnki.Ct.2017.12.052 2. Wu, J., Wu, J., Xu, D., Lv, Y.: Strong shallow coal-bed gas pulse perforation fracturing process experimental study. J. Coal Technol. 35(1), 10–12 (2016). https://doi.org/10.13301/j.carolc arrollnki.Ct.2016.10.005 3. Zhang, S.: Fracturing technology and application of deep coalbed methane. Petrochem. Technol. 222,29(05), 156–158 4. He, T., Jing, Y., Ke, Y., Liu, W.: Research status and prospect of anhydrous fracturing fluid technology. Adv. Fine Petrochem. Ind. 20(02), 24–28+32 (2019). https://doi.org/10.13534/j. cnki.32-1601/te.2019.02.008 5. Zhang, X., Zhang, S., Yao, B.: Research status of pulse fracturing technology for coalbed methane Wells. Oil Field Equip. 48(05), 79–83 (2019) 6. Wang, J., Qi, L., Long, Y.: Research status and development trend of anhydrous fracturing technology. Petrochem. Technol. 23(12), 217–218 (2016) 7. Blowing. Coalbed methane well fracturing technology research and application. J. Inner Mongolia Coal Econ. 2021(22), 148–150 (2021). https://doi.org/10.13487/j.carolcarrollnki imce.021380 8. Du, X., Zhang, X., Tang, M., Huang, P.-G.: Research on fixed point multi-stage pulse fracturing technology of thin interlayer. Drill. Prod. Technol. 41(01), 65–68+5–6 (2018) 9. Wu, F., Xu, S., Liu, J., Yu, X., Pu, C., Ren, Y.: Coupling simulation of combined pulse fracturing loading process and sensitivity analysis of influence of powder ratio. Explos. Shock Waves 38(03), 683–687 (2018)
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10. Pu, J., Yang, Y., Pu, C., Zou, H.: On some studies about the dynamic mechanisms of carbon monoxide flow and diffusion during high energy gas fracturing. Saf. Sci. 50(4), 903–908 (2012) 11. Wu, J.J., Liu, L.C., Zhao, G.H., Chu, X.S.: Research and exploration of high energy gas fracturing stimulation integrated technology in Chinese shale gas reservoir. Adv. Mater. Res. 1792, 524–527 (2012) 12. West Virginia High Technology Consortium Foundation; Researchers Submit Patent Application. Pulsed Fracturing Method and Apparatus, for Approval. J. Eng. (2015) 13. Baker Hughes Incorporated; Patent Issued for Pulse Fracturing Devices and Methods. J. Eng. (2014) 14. Patents; Agency Reviews Patent Application Approval Request for “Pulse Fracturing Devices and Methods”. Polit. Gov. Week (2013) 15. Liao, S., Hu, J., Zhang, Y.: Investigation on the influence of multiple fracture interference on hydraulic fracture propagation in tight reservoirs. J. Petrol. Sci. Eng. 211, 110160 (2022) 16. Hao, C., Cheng, Y., Wang, L., et al.: A novel technology for enhancing coalbed methane extraction: Hydraulic cavitating assisted fracturing. J. Nat. Gas Sci. Eng. 72, 103040 (2019) 17. Zhang, Z., Mao, J., Yang, X., et al.: Advances in waterless fracturing technologies for unconventional reservoirs. Energy Sour. Part A: Recov. Util. Environ. Effects 41(2), 237–251 (2018) 18. Shao, Y., Wang, Z., Ren, G., Hu, X., Meng, X., Xue, X.: Development of PFT95-I pulse fracturing tool. Oil Field Equip. 44(08), 64–67 (2015) 19. New following. The study of the downhole coalbed methane well fracturing pulse generator. China University of Petroleum (Beijing) (2020). https://doi.org/10.27643/dcnki.Gsybu.2020. 000933 20. Wu, J.J., Liu, L.C., Zhao, G.H., Chu, X.S.: Design research on the composite process of consecutive perforation-strong pulse fracturing for multiple oil layers and thick interlayer. Adv. Mater. Res. 1674, 482–484 (2012) 21. Wu, F., Pu, C., Chen, D., Ren, S., Liu, B.: Coupling simulation of multistage pulse conflagration compression fracturing. Petrol. Explor. Dev. Online 41(5), 663–670 (2014)
The Common Reservoir Development Pattern of Highly Heterogeneous Bioclastic Limestone Reservoirs and Its Application in Well Completion Design: A Case Study on Mishrif B1-2 Reservoir in H Oilfield in the Middle East Min Gao1(B) , Lei Shao1 , Hai-ying Han1 , Guan-ming Shao2 , and Xiao-wei Sun2 1 Research Institute of Petroleum Exploration and Development, Beijing, China
{gaomin89,shaolei0414,hhying}@petrochina.com.cn
2 PetroChina Hangzhou Research Institute of Geology, Hangzhou, China
{shaogm_hz,sunxw_hz}@petrochina.com.cn
Abstract. In order to better understand the highly heterogeneous bioclastic limestone reservoirs and enhance the efficiency of exploration and development of such reservoirs, we took the Mishrif B1-2 reservoir in H Oilfield in the Middle East as an example, studied the common reservoir development pattern and discussed its application in well completion design. Four sedimentary facies, including tidal channel facies, high-energy shoal facies, low-energy shoal facies and lagoon facies, were identified from the studied strata based on key features of lithology, logging and seismic information, and the distribution and variation of these facies along with associated diagenetic modification were comprehensively analyzed. Five reservoir rock types were classified in the studied strata combining geological and petrophysical features including lithology, pore size, throat size, porosity and permeability. On the basis of sedimentary facies study and reservoir rock type study, two typical stacking patterns of reservoir rocks were proposed as tidal channel dominated reservoir complex and shoal dominated reservoir complex, and the application of these patterns in determining the perforation intervals in well completion design was summarized. Our study suggests that: the studied strata is characterized by frequently interbedded reservoir rocks of different types; Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information con-tained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been re-viewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial pur-poses without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 96–105, 2023. https://doi.org/10.1007/978-981-99-2649-7_10
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the favorable reservoir rocks usually developed in the tidal channel facies and shoal facies, and the barriers/baffles usually developed in the lagoon facies. The efficiency of oil production and water injection during reservoir development could both be improved by adopting reasonable perforation plans in well completion with full consideration of reservoir development patterns. Keywords: Bioclastic Limestone · Reservoir Development Pattern · Sedimentary Facies · Reservoir Rock Type · Perforation Interval
1 Introduction The oil production in the Middle East accounts for ~31% of the global oil production, of which oil production from carbonate rocks accounts for ~80%. The carbonate reservoirs in the Middle East are commonly composed of bioclastic limestones with high heterogeneity, and the H oilfield in the Upper Cretaceous Mishrif Formation in Iraq is a typical example. In such reservoirs, because the sedimentary facies changes fast both vertically and laterally, the spatial superimposition relationship of different types of reservoir rocks is very complex. This acts as the main factor affecting the fluid distribution and dynamics in the reservoirs, and thereby has become the research focus for making reasonable development strategies for oilfields. Researchers have conducted in-depth studies regarding the depositional environment, sedimentary facies, reservoir characteristics, high-permeability streaks and barriers/baffles of the Mishrif Formation in the H oilfield [3, 5, 8] and adjacent area [4, 7, 9], however, valuable studies about the reservoir development pattern and its important guidance on making well deployment strategies including determining perforation intervals are still rare. In this study, we established the sedimentary faices framework of the studied Mishrif B1-2 strata based on integrated analysis of cores, thin sections, well logs, seismic data and etc., and classified the reservoir rocks into five types combining the petrophysical properties such as pore size, throat radius, porosity and permeability to better characterize the distribution and connectivity of the effective reservoir zones. Two typical stacking patterns of reservoir rocks, the tidal channel dominated reservoir complex and the shoal dominated reservoir complex, were analyzed and illustrated into details, and the reasonable perforation strategies for oil producers and water injectors were suggested accordingly. The work provides improved methodology for the characterization of highly heterogeneous bioclastic limestone reservoirs, which has an important application significance in the development of oilfields with similar depositional background.
2 Geological Background The H oilfield locates in the southeastern part of Iraq, about 400 km southeast of the capital Baghdad. It is structurally located in the southeastern part of the Mesopotamia Basin in adjacent to the Zagros Foredeep (see Fig. 1). The structure of the oilfield is a gentle long-axis anticline striking NW-SE, and faults are not well developed. The Mishrif
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Formation in the study area belongs to the Cenomanian-Turonian stratigraphic interval, which has been proven to contain prolific, high-quality conventional carbonate reservoirs in the Arabian Plate [1]. The formation is composed of MA, MB, and MC groups, and the MB group is further divided into members of MB1-1, MB1-2A, MB1-2B, MB12C, MB2-1, MB2-2 and MB2-3. The formation is dominated by bioclastic limestone deposited during the Cenomanian regression, with a thickness of about 400 m, and is the main producing layer of the H oilfield. It was mainly deposited in a semi-restricted carbonate platform, which had sedimentary facies belts such as platform marginal shoals, intra-platform shoals, tidal channels and lagoons [5, 8]. The formation is characterized by high heterogeneity, with many high-permeability streaks and barriers/baffles developed in it [3]. This study focuses on the Mishrif B1-2 part of the formation, including the three members MB1-2A, MB1-2B and MB1-2C.
Fig. 1. Location and structural background of the study area.
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3 Reservoir Development Pattern 3.1 Sedimentary Facies The carbonate reservoirs in the Cenomanian-Turonian stratigraphic interval in the Middle East are largely influenced by sedimentation and diagenesis [11, 12, 14]. In this study, sedimentary facies analysis was conducted to examine the sedimentary and diagenetic features of the studied Mishrif B1-2 strata, using an integrated dataset of core, thin section, well logs and seismic data. Based on the combination and distribution of sedimentary facies, the depositional environment was determined to be a semi-restricted platform. Identification. Four sedimentary facies were identified from the studied strata: the tidal channel facies, high-energy shoal facies, low-energy shoal facies and lagoon facies. Key features of each facies are summarized in the following paragraphs and illustrated in Fig. 2. Tidal Channel. The tidal channels are the water exchange pathways between the lagoon and the ocean. They have some similar features as river channels, such as the scouring at the bottom shown as a sharp excursion on the GR curve. The tidal channel facies has a typical fining upward feature. The bottom part usually consists of grainstone, and as the lime mud content increases to the upper part, the lithology gradually changes to packstone and wackestone. The common logging features mainly include: the GR value is generally less than 20 gAPI at the bottom and increases upward; the Density is generally less than 2.35 g/cm3 at the bottom and increases upward; the Porosity and Permeability are both higher at the bottom and decrease upward. The channel shape could be recognized on the seismic profiles. High-Energy Shoal. The shoals form as small areas of relatively high topography in a large lagoon context. The high-energy shoals mainly consist of grainstone and graindominated packstone, and often show a coarsening upward feature. The common logging features mainly include: the GR value is generally less than 20 gAPI, and the Density is generally less than 2.35 g/cm3 . On seismic profiles, the high-energy shoal usually has a lenticular shape with strong reflection. Low-Energy Shoal. The low-energy shoals mainly consist of packstone, and the grading feature is less obvious compared to the high-energy shoals. The common logging features mainly include: the GR value is generally 20–30 gAPI, and the Density is generally 2.35– 2.45 g/cm3 . On seismic profiles, the low-energy shoal has weaker reflection compared to the high-energy shoal. Lagoon. The deposits in lagoon are characterized by frequently interbedded wackestone, mudstone and hardground layers. The common logging features mainly include: the GR value is generally 25–30 gAPI, and the Density is generally less than 2.45 g/cm3 .
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Fig. 2. Features of the four sedimentary facies on thin sections, well logs and seismic profiles.
Facies Distribution Characteristics. In the studied MB1-2 strata, lagoon facies dominated the semi-restricted platform environment. The high-energy shoals are scattered and discontinuous, and the low-energy shoals develop around the high-energy shoals with varying thickness and lateral scale. The tidal channels are meandering in plans and cutting through the other sedimentary facies. In some area, the tidal channels have multiple stages and the deposits of different stages superimposed vertically. Diagenesis modification differs in the four sedimentary facies and also varies among stratigraphic intervals. The tidal channel facies and high-energy shoal facies experienced relatively strong quasi-contemporaneous dissolution, which leaded to an increase in permeability and could result in the forming of high-permeability streaks in some local area. The low-energy shoals experienced relatively weak dissolution and the permeability remain moderate. In some of the uppermost parts of the lagoon facies, there are also highpermeability streaks formed by strong dissolution. The general distribution pattern and touching relationship between different sedimentary facies are illustrated in Fig. 3.
3.2 Reservoir Rock Types (RRTs) Reservoir rock typing is the process of classifying reservoir rocks according to the linked geological and petrophysical features [6, 13]. It is the most essential part of reservoir characterization, and has been widely practiced in various disciplines of oil industry, such as permeability prediction in uncored intervals and reservoir modeling [2, 10].
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Fig. 3. A sketch profile showing the development pattern of sedimentary facies in the studied strata.
Based on the geological and petrophysical properties including lithology, pore size, throat size, porosity and permeability, five reservoir rock types were classified in the studied strata (see Fig. 4). RRT-1 is mainly composed of grainstones, developed at the bottom of tidal channels and high-energy shoals with high porosity, high permeability and large pore throats. RRT-2 is mainly composed of grain-dominated packstones, developed in some high-energy shoals and tidal channels, with high porosity, medium permeability, and medium pore throats. RRT-3 is mainly composed of mud-dominated packstones, developed in low-energy shoals, with medium-high porosity, low permeability, and small
Fig. 4. Features of the five reservoir rock types in the studied strata.
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pore throats. RRT-4 is mainly composed of wackestones, developed in lagoons with lowmedium porosity, low permeability and small pore throats. RRT-5 is mainly composed of mudstones, developed in lagoons with low porosity, low permeability and small pore throats. 3.3 Typical Stacking Patterns of Reservoir Rocks Combining the sedimentary features, the petrophysical properties and their vertical and lateral variations, two typical stacking patterns of the reservoir rocks were summarized for the studied strata. Tidal Channel Dominated Reservoir Complex. The tidal channel facies could consist of one or several stages of channel deposits stacked vertically. The deposits in each channel body are usually formed as stacked lenses, and generally show a normal grading sequence from bottom to the top. The high energy depositional environment resulted in sedimentary structures like cross bedding and hummocky bedding. Laterally, lagoon facies and shoal facies were deposited outside the tidal channel. The channel facies is dominated by RRT-1 and RRT-2 and generally has good reservoir properties, especially the RRT-1 in the middle and bottom parts of each channel body. The lateral scope and connectivity of the reservoirs depend on the facies and rock type outside the channel. For example, Well-1 penetrates the main part of the channel facies, and has a thick reservoir interval; the area outside of the channel is dominated by lagoon facies with scattered poor reservoirs, and therefore the good reservoirs could not extend to Well-2 (see Fig. 5). Shoal Dominated Reservoir Complex. In the studied strata, such reservoir complexes usually form in associated to bioclastic shoals deposited in a lagoon background. The
Fig. 5. A sketch profile of the tidal channel dominated reservoir complex.
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reservoir architecture could also be largely influenced by diagenesis in addition to deposition. The main reservoir rock types include RRT-2 and RRT-3, and the reservoirs are usually in the form of relatively thin layers interbedded with the non-reservoir intervals. According to the differences in the scope and connectivity of reservoir layers, there are 3 typical patterns in such reservoir complexes in the studied strata. In MB1-2C, the shoals have relatively large extending range, and good reservoirs are connected among many wells; in MB1-2B, the extending range of the shoals is medium, and good reservoirs are connected only in adjacent wells; in MB1-2A, the extending range of the shoals is small, and good reservoirs are developed in very limited area and even not connected between adjacent wells (see Fig. Fig. 6).
Fig. 6. A sketch profile of the shoal dominated reservoir complex.
4 Guidance for Perforation Interval Design in Well Completion 4.1 Production Well In order to improve the well productivity, favorable reservoir intervals that composed of good and medium reservoir rock types including RRT-1, RRT-2 and RRT-3 are usually suggested to be perforated in order to guarantee an enough total perforation thickness. In addition, the possible production interference among different strata members should also be evaluated based on the reservoir development pattern. For example, if two strata members have distinct reservoir development patterns (such as MB1-2A and MB1-2C in Fig. 6), commingling production (having all the favorable reservoir layers perforated) in a producer may lead to an uneven recovery degree in different members, that is, the
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production will mainly come from the member with better reservoir properties (such as MB1-2C), while the member with poorer reservoir properties (such as MB1-2A) will barely contribute production. In this case, separate well patterns might be designed for these two members to improve the production efficiency, and the perforation intervals of producers should be designed accordingly. 4.2 Water-Injection Well The reservoir development pattern plays an essential role in determining the injectionproduction relationship. The general principles of designing perforation intervals for water-injection wells include: firstly, guarantee good connectivity between the injector and the producer, and secondly, isolate the high-permeability streaks to avoid early water breakthrough. In tidal channel dominated reservoir complexes, injection wells should not be deployed within the channel bodies in order to avoid early water breakthrough along the channel. For example, an injection well should be deployed at the location of Well-2 rather than Well-1 in Fig. 5 if needed. In shoal dominated reservoir complexes, injection wells should not be deployed in thin intervals that have widely distributed RRT-1 and/or RRT-2 (such as in MB1-2C in Fig. 6); in another hand, intervals that are dominated by poor reservoirs (such as in MB1-2A in Fig. 6) are also not suitable for water injection, and acidizing should be implemented to improve injectivity if needed.
5 Conclusions • The studied Mishrif B1-2 strata in the H oilfield were deposited in a semi-restricted carbonate platform environment, with sedimentary facies mainly including tidal channel, high-energy shoal, low-energy shoal and lagoon developed. The dominant facies in the strata is lagoon, with the other three facies scattered in it. The lateral and vertical fast changes of the sedimentary facies and the locally developed diagenesis modification together resulted in the high heterogeneity of the reservoir. • Two typical stacking patterns of reservoir rocks were summarized for the studied strata. In the tidal channel dominated reservoir complex, the channel bodies are embedded in the lagoon context and have obviously better reservoir properties compared to the surrounding strata. The favorable reservoir zones mainly consist of RRT-1 and RRT-2, and their distribution is limited by the shape of the tidal channels. The shoal dominated reservoir complex is characterized by more frequent changes in reservoir rock types, and the favorable reservoir zones mainly consist of RRT-2 and RRT-3. • The reservoir development pattern provides important guidance for determining perforation intervals in well completion design. For production wells, in addition to perforate the favorable and/or moderate reservoir layers to guarantee an enough total perforation thickness, the potential production interference among different strata members should also be evaluated based on the reservoir development pattern. For injection wells, the perforation intervals should guarantee good connectivity between the injector and the adjacent producers, and meanwhile isolate the high-permeability streaks to avoid early water breakthrough.
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Acknowledgments. The study is supported by National Science and Technology Major Project (2017ZX05030-001).
References 1. Bromhead, A.D., van Buchem, F.S.P., Simmons, M.D., et al.: Sequence stratigraphy, palaegeography and petroleum plays of the Cenomanian-Turonian succession of the Arabian Plate: an updated synthesis. J. Petrol. Geol. 45(2), 119–162 (2022) 2. Mohammadian, E., Kheirollahi, M., Liu, B., et al.: A case study of petrophysical rock typing and permeability prediction using machine learning in a heterogenous carbonate reservoir in Iran. Sci. Rep. 12, 4505 (2022). https://doi.org/10.1038/s41598-022-08575-5 3. Qiao, Z., Sun, Y., Cao, P., et al.: Genesis and development law of barrier and baffles and high permeable streak in the massive bioclastic reservoir: a case study of the Upper Cretaceous Mishrif Formation in H Oilfield, Iraq. Marine Origin Petrol. Geol. 27(1), 71–83 (2022) 4. Li, F., Song, X., Guo, R., et al.: Characteristics and genesis of interlayers in thick bioclastic limestone reservoirs: a case study of Cretaceous Mishrif Formation of the M oilfield in the Middle East. Acta Petrolei Sinica 42(7), 853–864 (2021) 5. Sun, W., Qiao, Z., Shao, G., et al.: Sedimentary and reservoir architectures of MB1-2 submember of Middle Cretaceous Mishrif Formation of Halfaya Oilfield in Iraq. Petrol. Explor. Dev. 47(4), 713–722 (2020) 6. Al-Jawad, S.N.A., Ahmed, M.A., Saleh, A.H.: Integrated reservoir characterization and quality analysis of the carbonate rock types, case study, southern Iraq. J. Petrol. Explor. Prod. Technol. 10, 3157–3177 (2020). https://doi.org/10.1007/s13202-020-00982-6 7. Al-Ali, A., Stephen, K., Shams, A.: Characterization of channelized systems in a carbonate platform setting: a case study on the Late Cretaceous reservoir from the Supergiant Oilfield, Iraq. In: Paper Presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, UAE, September 2019. Paper Number: SPE-196618-MS (2019). https://doi.org/10.2118/196618-MS 8. Yu, Y., Sun, L., Song, X., et al.: Sedimentary diagenesis of rudist shoal and its control on reservoirs: a case study of Cretaceous Mishrif Formation, H Oilfield, Iraq. Petrol. Explor. Dev. 45(6), 1007–1019 (2018) 9. Vogel, K.R., Follows, E.J.: Tectonic and eustatic control on Mishrif regional reservoir distribution. In: Paper Presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, November 2016. Paper Number: SPE-183192-MS (2016). https://doi.org/ 10.2118/183192-MS 10. Chandra, V., Barnett, A., Corbett, P., et al.: Effective integration of reservoir rock-typing and simulation using near-wellbore upscaling. Marine Petrol. Geol. 67, 307–326 (2015) 11. Vincent, B., Van Buchem, F.S.P., Bulot, L.G., et al.: Depositional sequences, diagenesis and structural control of the Albian to Turonian carbonate platform systems in coastal Fars (SW Iran). Marine Petrol. Geol. 63, 46–67 (2015) 12. Han, H., Mu, L., Guo, R., et al.: Characteristics and controlling factors of Cretaceous bioclastic limestone reservoirs in Ahdeb Oil Field, Iraq. Marine Origin Petrol. Geol. 19(2), 54–63 (2014) 13. Aliakbardoust, E., Rahimpour-Bonab, H.: Integration of rock typing methods for carbonate reservoir characterization. J. Geophys. Eng. 10(5), 055004 (2013). https://doi.org/10.1088/ 1742-2132/10/5/055004 14. Hollis, C.: Diagenetic controls on reservoir properties of carbonate successions within the Albian-Turonian of the Arabian plate. Petrol. Geosci. 17(3), 223–241 (2011)
Application of Multilateral Wells to Increase Well Productivity in Offshore Oil Field Case Study Salma Osama Taha Taha El Daly1 , Elhassan Mostafa Abdallah1(B) , and Yasir Mukhtar1,2,3 1 Department of Chemical and Petroleum Engineering, UCSI University, Kuala Lumpur,
Malaysia {1001542244,elhassan}@ucsiuniversity.edu.my 2 China University of Petroleum-Beijing, Beijing, China [email protected] 3 Sudan University of Science and Technology, Khartoum, Sudan
Abstract. Multilateral wells are mentioned as technologies to improve reservoir recovery rates. Some strategies are simple and straightforward, while others are far more complex. Such complex completions enable the use of multilateral wells in a much broader range of well-scenarios, but they also create a new set of obstacles, concerns, and threats. Few operators, however, were prepared to design a multilateral well. The Fishbone wells are new production techniques that have been introduced to improve productivity and provide access to complex geological types and reservoirs. The main benefit is the low cost and short time required to run this system. This study discusses a project that demonstrate the concept of using multilateral wells as an alternative by comparing it to two conventional horizontal wells, which can lead to a significantly lower operating cost. The primary goals of this work are mainly to design a multilateral well scenario with five wellbores (Wellbores #1, Wellbores #2, Wellbores #3, Wellbores #4, and Wellbores #5) to increase oil production from offshore oil fields and evaluate their productivity and economics. The Landmark Software, COMPASS is utilized to design the plan trajectories, CasingSeat is used to determine the best casing design Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the 2022 International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 106–119, 2023. https://doi.org/10.1007/978-981-99-2649-7_11
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and suitable casing ODs, and the tNavigator Software is used to assess oil recovery and economy. The most production was found in multilateral wells formed by Fishbone. When compared to conventional horizontal wells, these multilateral wells provided more oil over a longer period of time with lower operating costs. As a result, the net profit has been calculated, and the multilateral well performed better because its total net income exceeds that of the two horizontal wells to be drilled. Keywords: Multilateral well · Oil production · Offshore oil field · Horizontal
1 Introduction The changing financial matters of oil field improvement has come about in administrators, and thus, benefit companies, being challenged to deliver more prominent quantities of oil at diminished costs. More profound and more corrosive environments are being created to extend production capacities, and modern innovation is being empowered within the endeavor to create as much “value” from a well as possible. This interest and the resulting improvement of modern strategies has been a major factor in permitting projects to be endeavored that traditionally would not have been seen as financially doable. The multilateral concept could be a prime case of inventive technology that has been utilized to support current financial needs. But despite their expanding financial request, the mechanical stability of the multilateral junction remains one of the foremost challenging issues within the industry. A multilateral well could be an interesting framework that interfaces two or more laterals (horizontal, vertical, or deviated) with the most wellbore. Which permits one well to create from a few reservoirs. Multilateral wells are reasonable for complex geology where drilling more new wells to penetrate to those reservoirs isn’t conservative. Sidelong segments may be utilized to produce from a separated area in depleted, faulted, layered and heavy oil reservoirs. Can construct multilaterals in both new and existing wells. An ordinary establishment incorporates two laterals; the number of laterals would determine by: the number of targets, depth/pressure, risk analysis and well-designed parameters.
2 Methodology and Experimental Setup This chapter will cover up the methodology of the desired case study that will take place in this paper. The following steps will be assessed by operating the landmark Software (Compass, CasingSeat) and tNavigator program. Furthermore, the methodology of the case is to study the multilateral wells and its productivity by simulating data in the software mentioned above. 2.1 COMPASS The wellbore location needs to be precise to optimize production of every well drilled well into the target region. And by expanding the amount of the complicated wells in
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multilateral, extreme variations including long horizontals, it is much more significant. Many horizontal wells are being drilled quicker and near together, with small goal areas or also in already mature fields. In order to contribute, engineers need to drill rapidly while preventing geological risks and collisions to direct the bit into the productive pay zone. COMPASS program is the sector’s main program for the design of directional well pathways, data collection analyses, tracking and anti-collision tests. This was built for the petroleum industry and the drilling firms. It will improve the performance, safety, and expense-effectiveness of advice well programs. It includes various 2D and 3D modelling processes, optimized torque and drag research, Optimization of expenses and re-entry, planning, data interpretation of research and aim production of drillers. In a shared data and configuration framework, the program is built on the Engineer’s Data Model (EDM) platform enabling data integrity and decreased cycle times in preparation. Members of the product team must be informed that if any modifications arise due to software upgrades and alerts, the technical findings should still be changed in real time. Through interdisciplinary resources team settings this program is also an important aspect of integrated well planning. Assimilation with OpenWorks geoscience software means both geoscientists and engineers understand trajectory improvements generated by the other group, so each project manager can have direct guidance to accomplish both engineering and sub-surface targets. 2.2 CasingSeat CasingSeat program is a processor-based device that can assess the length and wellbore width of the casing and effective casing. Will optimize efficiency on tubular expense using the CasingSeat program in the early stages of the casing design method. The program incorporates assets-based control of appropriate hole and case size variations and offers thermal-based and lithology-based analysis of subsurface initial conditions and operational restrictions, including all those relevant to wellboard integrity, minimal unbalance, and variable sticking. CasingSeat program offers strategies of approach from the bottom up and top down, focused on minimal configuration-depth criteria and the highest allowable drill-ahead range for the definition and rating of casing systems, accordingly. CasingSeat application is based on the application model Engineer’s Data Model (EDM), which provides a highly developed range of well-engineering and information analytics technologies. This allows data to be accessed once, and only used in the program to encourage better strategies and a framework to maintain and navigate organizational information and learned lessons. 2.3 tNavigator Is a common downloadable program application that enables the user to construct static and dynamic reservoir models, operate dynamic simulations, measure PVT fluid properties, create surface network models, measure lifting tables and conduct advanced uncertainty analyses as result of an automated system. Both aspects of the process share a
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similar standardized internal data storing framework, super-scalable parallel numerical engine (tested up to 10,240 Processor and 35,840 GPU cores with model sizes greater than 1 billion active grid blocks), application I/O process, and graphical user interface.
3 Results and Discussion A new project named as Sakura has been created in an offshore oil field under the PETROSU company to design two different wells, multilateral well and horizontal well, with different slots for each, and compare between them to prove that the multilateral well is the best scenario compared to the other conventional horizontal well. The multilateral well designed successfully with five wellbores to reach five different targets with a much lower operating cost. The two wells designed successfully by simulating the data in the Landmark Software (COMPASS and CasingSeat) and the tNavigator. First, COMPASS software used to design the plan trajectories. Second, CasingSeat to find the best design of casing and suitable casing ODs. Finally, tNavigator Software to check the oil recovery and economy. 3.1 Multilateral Well The multilateral well named as Sakura_W1 designed successfully under one slot named as E1 with Easting of 545,617.00 m and Northing of 6,543,423.00 m. Is a Jack-up Rig with an elevation above the Mean Sea Level by 125.0 ft, with a mudline depth of 305.0 ft and mudline TVD of 430.0 ft. The multilateral well created with five wellbores, the mother wellbore (Wellbore #1) connected from the surface to a depth of 12,000.0 ft TVD, and the other four wellbores are the branches to Wellbore #1. Wellbore #2 tied up from Wellbore #1 at a depth of 4000 ft to reach its target at a depth of 5640.0 ft TVD. Wellbore #3 tied up from Wellbore #1 at a depth of 3000 ft to reach its target at a depth of 5275.0 ft TVD. Wellbore #4 tied up from Wellbore #1 at a depth of 5000 ft to reach its target at a depth of 6640.0 ft TVD. Wellbore #5 tied up from Wellbore #1 at a depth of 7000 ft to reach its target at a depth of 8645.0 ft TVD. COMPASS
Design #1 After creating the well and done with its properties. For Design #1, Wellbore #1 has been created with a depth of 12,000.0 ft TVD. However, for this design, Wellbore #1 will be contributed as a mother wellbore as it is the first well to be drilled. Wellbore #1 has been drilled from the surface to a depth of 12,054.6 ft MD with a 0° inclination and 0° azimuth. To reach Target1 at depth 12,000.0 ft TVD with a Northing of 6,543,423.0 m and Easting of 545,617.0 m. Design #2 For Design #2, Wellbore #2 has been created with depth of 10,021.9 ft MD tied-up from Wellbore #1 at a depth of 4000.0 ft TVD with 0° inclination and azimuth. However, until
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it reached depth 5636.6 ft TVD, started an inclination of 90° with an azimuth of 180° and started to decline until it reaches an inclination of 75.25° and azimuth of 99.48° to the zone of interest at depth of 5640.0 ft TVD with KOP at 4000.0 ft TVD and drop Sect. 5636.6 ft TVD. To reach Target2 at depth 5640.0 ft TVD with a N/S of –4651.9 ft and E/W of 12.7 ft. Design #3 For Design #3, Wellbore #3 has been created with depth of 10,043.1 ft MD tied-up from Wellbore #1 at a depth of 3000.0 ft TVD with 0° inclination and azimuth. However, until it reached depth 5273.2 ft TVD, started an inclination of 90° with an azimuth of 0° and started to decline until it reaches an inclination of 87.57° but the azimuth increased to 128.94° to the zone of interest at depth of 5275.0 ft TVD with KOP at 3000.0 ft TVD. To reach Target3 at depth 5275.0 ft TVD with a N/S of 5268.1 ft and E/W of 32.7 ft. Design #4 For Design #4, Wellbore #4 has been created with depth of 10,045.6 ft MD tied-up from Wellbore #1 at a depth of 5000.0 ft TVD with 0° inclination and azimuth. However, until it reached depth 6636.6 ft TVD, started an inclination of 90° with an azimuth of 0° and started to decline until it reaches an inclination of 85.83° but the azimuth increased to 135.73° to the zone of interest at depth of 6640.0 ft TVD with KOP at 5000.0 ft TVD. To reach Target4 at depth 6640.0 ft TVD with a N/S of 3628.1 ft and E/W of 32.7 ft. Design #5 Fortunately, for Design #5, Wellbore #5 has been created with depth of 12,070.6 ft MD tied-up from Wellbore #1 at a depth of 7000.0 ft TVD with 0° inclination and azimuth. However, until it reached depth 8636.6 ft TVD, started an inclination of 90° with an azimuth of 180° and started to decline until it reaches an inclination of 85.50° and azimuth of 17.88° to the zone of interest at depth of 8645.0 ft TVD with KOP at 7000.0 ft TVD and drop Sect. 8636.6 ft TVD. To reach Target5 at depth 8645.0 ft TVD with a N/S of –3601.9 ft and E/W of 32.7 ft. Finally, after created the five wellbores, the multilateral well has been successfully created with a mother wellbore (Wellbore #1) and four branches (Wellbore #2, Wellbore #3, Wellbore #4, Wellbore #5) to reach to five different targets, Target1, Target2, Target3, Target4, and Target5, at a depth of 12,000.0 ft TVD, 5640.0 ft TVD, 5275.0 ft TVD, 6640.0 ft TVD and 8645.0 ft TVD, respectively (Fig. 1). CasingSeat After results has been successfully accomplished in COMPASS software. By using a specific data that inserted to the desired casing size, hole size, lithology, pore, and fracture pressure. The five designs (Design #1, Design #2, Design #3, Design #4, Design #5) have been created successfully in the CasingSeat software. Design #1 For Design #1, the well schematic has been created successfully. The surface casing is 32 at 848.6 ft to a bore hole size of 36 , intermediate casing is 24 at 2847.7 ft to a bore hole size of 28 , intermediate casing is 16 at 8970.1 ft to a bore hole size of 22 ,
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Fig. 1. The designed multilateral well
conductor casing is 13 3/8 at 11,236.6 ft to a bore hole size of 16 and the production casing is 9 5/8 at 12,000 ft to a bore hole size of 12” (Fig. 2). Design #2 The well schematic has been created successfully for Design #2. As mentioned in COMPASS Design #2 is a tied-up well that starts from a depth of 4000.0 ft TVD with an intermediate casing of 13 3/8 to a borehole size of 17 1/2 . Then at a depth of 5000.0 ft, the intermediate casing is 9 5/8 to a borehole size of 12 1/4 , then followed by the conductor casing that is 7 at a depth of 6000.0 ft to a borehole size of 7 1/2 . And the production casing is 5 1/2 at a depth of 10,000.0 ft to a borehole of 6” (Fig. 3). Design #3 The well schematic has been created successfully for Design #3. As mentioned in COMPASS Design #3 is a tied-up well that starts from a depth of 3000.0 ft TVD with an intermediate casing of 13 3/8 to a borehole size of 17 1/2 . Then at a depth of 4000.0 ft, the intermediate casing is 9 5/8 to a borehole size of 12 1/4 , then followed by the conductor casing that is 7 at a depth of 6000.0 ft to a borehole size of 7 1/2 . And the production casing is 5 1/2 at a depth of 10,000.0 ft to a borehole of 6” (Fig. 4). Design #4 The well schematic has been created successfully for Design #4. As mentioned in COMPASS Design #4 is a tied-up well that starts from a depth of 5000.0 ft TVD with an intermediate casing of 13 3/8 to a borehole size of 17 1/2 . Then at a depth of 6000.0 ft, the intermediate casing is 9 5/8 to a borehole size of 12 1/4 , then followed by the conductor casing that is 7 at a depth of 7000.0 ft to a borehole size of 7 1/2 . And the production casing is 5 1/2 at a depth of 10,045.6 ft to a borehole of 6” (Fig. 5).
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Fig. 2. Design #1 in CasingSeat
Fig. 3. Design #2 in CasingSeat
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Fig. 4. Design #3 in CasingSeat
Fig. 5. Design #4 in CasingSeat
Design #5 The well schematic has been created successfully for Design #5. As mentioned in COMPASS Design #5 is a tied-up well that starts from a depth of 7000.0 ft TVD with an intermediate casing of 13 3/8 to a borehole size of 17 1/2 . Then at a depth of 8000.0 ft, the intermediate casing is 9 5/8 to a borehole size of 12 1/4 , then followed by the conductor casing that is 7 at a depth of 9000.0 ft to a borehole size of 7 1/2 . And the production casing is 5 1/2 at a depth of 12,070.6 ft to a borehole of 6” (Fig. 6). tNavigator and Petrel Static model was created using petrel. The reservoir was designed using following parameters such as porosity, permeability and net to gross. A multilateral well was designed in tNavigator to compare the oil production and economy between the conventional horizontal well. An average porosity of 0.08011, minimum porosity of 0.040003 and a
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Fig. 6. Design #5 in CasingSeat
maximum porosity of 0.11998 and a horizontal permeability of 98.69 mDarcy and a vertical permeability of 9.869 mDarcy. The reservoir demonstrates an average oil saturation of 0.77944. The model contains 17,250 grid cells for each 500 ft X, 500 ft Y to be estimated as one grid cell. In this model 50 layers as Z-direction (vertical) was estimated up on the thickness of reservoir. In addition, the reservoir contains three phases of fluid (light oil API 45°, gas and water). The maximum rate of oil production of the multilateral wells was set to be 60,000 stb/day and after 18 years dropped to 15.4772 thousand stb/day and a sudden drop in the last 2 years that results in shutting down the well, due to the pressure drop. However, the total oil production over 20 years is 365.629 million stb and 235.365 million Mscf total gas. tNavigator was utilized to design the dynamic model of reservoir to predict the recovery factor of oil and gas, which is 13.2661% and 18.7033%, respectively (Fig. 7). 3.2 Horizontal Well A horizontal well named as Sakura_W2 designed successfully under one slot named as E2 with Easting of 545,609.48 m and Northing of 6,543,422.4 m. Is a Jack-up Rig with an elevation above the Mean Sea Level by 125.0 ft, with a mudline depth of 305.0 ft and mudline TVD of 430.0 ft. The horizontal well drilled from the surface to a depth of 10,056.3 ft MD and 5275.0 ft TVD, to reach its target at a depth of 5275.0 ft TVD. COMPASS For this drilled horizontal well (Design #1), Wellbore #1 has been created with a depth of 10,056.3 ft MD from the surface with 0° inclination and azimuth. However, until it reached depth 5273.2 ft TVD, started an inclination of 90° with an azimuth of 0° and started to decline until it reaches an inclination of 89.90° but the azimuth increased to 178.09° to the zone of interest at depth of 5275.0 ft TVD with KOP at 3000.0 ft TVD. To reach Target1 at depth 5275.0 ft TVD with a N/S of 5268.1 ft and E/W of 32.7 ft (Fig. 8).
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Fig. 7. Reservoir model of the multilateral well
Fig. 8. How Wellbore #1 looks with Target1 after it has been created
CasingSeat After results has been successfully accomplished in COMPASS software. By using a specific data that inserted to the desired casing size, hole size, lithology, pore, and fracture pressure. The well schematic has been created successfully for Design #1 in the CasingSeat software. The surface casing is 14 at 1000.0 ft to a borehole size of 18 5/8 , intermediate casing is 11 3/4 at 1365.6 ft to a borehole size of 13 3/4 , intermediate casing is 10 3/4 at 1975.0 ft to a borehole size of 11 , conductor casing is 7 3/4 at 3705.6 ft to a borehole size of 9 1/2 and the production casing is 5 at 10,043.1 ft to a bore hole size of 6 1/2” (Fig. 9).
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Fig. 9. Design #1 in CasingSeat
tNavigator and Petrel Static model was created using petrel. The reservoir was designed using following parameters such as porosity, permeability, and net to gross. Two horizontal wells was designed in tNavigator to compare the oil production and economy between the multilateral well. An average porosity of 0.08011, minimum porosity of 0.040003 and a maximum porosity of 0.11998 and a horizontal permeability of 98.69 mDarcy and a vertical permeability of 9.869 mDarcy. The reservoir demonstrates an average oil saturation of 0.77944. The model contains 17,250 grid cells for each 500 ft X, 500 ft Y to be estimated as one grid cell. In this model 50 layers as Z-direction (vertical) was estimated up on the thickness of reservoir. In addition, the reservoir contains three phases of fluid, (light oil API 45°, gas and water). The maximum rate of oil production of the horizontal wells was set to be 10,000 stb/day of each well and after 20 years it decreases to 1905.6 stb/day. However, the total oil production over 20 years is 107.079 million stb and 57.9807 million Mscf total gas.
Fig. 10. Reservoir model of the horizontal wells
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tNavigator was utilized to design the dynamic model of reservoir to predict the recovery factor of oil and gas, which is 3.88412% and 4.60646%, respectively (Fig. 10).
4 Environmental Impact and Conclusion 4.1 Environmental Impact Routine oil and gas activities in each production, decommissioning and exploration process may have adverse environmental effects. Impacts can occur indirectly (traffic & sound) and physically directly (drilling fluids, drill cuttings and anchor chains) Drilling programs run around the clock, affecting biodiversity, sources of water, human safety, leisure activities and other public lands. The petroleum and gas perforations in our wild lands and ecosystems have serious consequences. Damage to marine life caused by seismic surveys aimed at estimating the scale of a petroleum and gas reserve pose environmental issues. Additive attack from seismic surveys have found that fish eggs and larvae are harmed or destroyed, that they hinder hearing and health of the fish and that they are unable to locate or interact with each other. Such disruptions intervention and displace essential patterns of migration that force marine life away from proper habitats such as nurseries, feeding stuffs, spawning and migration corridors. The 2010 BP Deepwater Horizon explosion destroyed about one million seabirds on the coast and offshore, five thousand of marine mammals, and one thousands of sea turtles. Spills of chemical and oil can. Damage the kidney, brain, liver, spleen, or other organ of animals. Causes cancer, reproductive failure, and suppression of the immune system. And cause long-term environmental changes by destroying the nesting or breeding grounds of animals. According to the United Nations, oil and gas production is one of the main culprits for the pollution of the atmosphere. Respiring this air can lead to asthma, cardiovascular disease, developmental disorders and even cancer. The process of “fracking,” which includes contaminants that cause cancer, birth defects and liver damage, is notorious for its pollution of water supplies. The effects of long wildfires, heavy hurricanes and extreme heat waves are all around us. Human have burned fossil fuels that led to the increasing of releasing greenhouse gasses into the atmosphere since the industrial revolution. Carbon dioxide is primarily emitted in the air by bubbling of oil, coal, and gas, is the most abundant source of greenhouse gas. During natural gas drilling, another gas, methane, is emitted using the “fracking” process. Building roads, facilities and sites known for the use of heavy equipment as well as pads can lead to the destruction of large sections of the untouched wild. Oil and gas complex development can cause serious and long-term land damages including destruction of the plant ecosystem, erosion, landslides, floods, and seriously fragmenting natural habitats for wildlife. 4.2 Conclusion The primary goal of this research has been accomplished. Using COMPASS software to create drilling trajectories for a multilateral well and a horizontal well. Sakura W1 is a
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multilateral well with five wellbores, Wellbores #1, Wellbores #2, Wellbore #3, Wellbore #4, and Wellbore #5, designed successfully under one slot called E1 with 545,617.00 m east and 6,543,423.00 m north; a Jack-up Rig with an elevation of 125.0 feet above mean sea level, a mudline depth of 305.0 feet, and a mudline TVD of 430.0 ft. The desired targets were reached at the desired depth, Target1 at 12,000 ft TVD, Target2 at 5640 ft TVD, Target3 at 5275.0 ft TVD, Target4 at 6640.0 ft TVD and Target5 at 8645.0 ft TVD of each branch. The well trajectories created for both multilateral and horizontal wells are J-type wells that were applied to each branch with a single fixed drilling platform. A horizontal well named Sakura W2 was successfully designed under one slot called E2 with an easting of 545,609.48 m and a northing of 6,543,422.41 m. Target1 must be reached at the desired depth of 5275.0 ft TVD. Besides, a static model and a dynamic model were developed using two software programs, tNavigator and Petrel, to estimate the oil recovery of both scenarios. The multilateral wells’ maximum rate of oil production was set at 60,000 stb/day, with a total oil production over 20 years of 365.629 million stb and 235.365 million Mscf total gas. The maximum rate of oil production for two horizontal wells was set at 10,000 stb/day each, for a total oil production of 107.079 million stb and 57.9807 million Mscf total gas over 20 years. After calculating the net profit via Excel, the total net profit of drilling two horizontal wells was $6,379,912,639, with a cost of $6,000,000. The multilateral net income was 22,592,449,839 dollars, with a drilling cost of 16,000,000 dollars.
5 Nomenclature
Symbol COMPASS TVD KOP TOC MD
Description Computerised Planning and Analysis Survey System True Vertical Depth Kick Off Point Top of Cement Measured Depth
Dimension / Unit Dimensionless ft. ft . ft. ft.
Acknowledgements. In the name of Allah, the Most Gracious and the Most Merciful. All praises to Allah and His blessing for the completion of this thesis. I thank God for all the opportunities, trials and strength that have been showered on me to finish writing the thesis. I would like to extend my appreciation to my Final Year Project supervisor, Mr. Elhassan Mostafa and my Final Year Project coordinator, Mr. Bonavian Hasiholan for their continuous guidance and deep concerns in my progress with regards to the project. I would also like to extend my gratitude to my family and especially my mother, who has been a source of support and comfort throughout the duration of this project.
References 1. Aabo, E.: MultiLateral wells - new opportunities in petroleum engineering. In: presented at the SPE Conference on Opportunities with Multilateral Drilling, Stavanger, vol. 9 (1995)
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2. Brodersen, F.: Achievements in drilling and completion of multiple lateral drain hole in chalk reservoir. In: Presented at the SPE Conference on Opportunities with Multilateral Drilling, Stavanger, vol. 9 (1995) 3. Cinco-Ley, H., Rarney, H.J., Miller, F.G.: Pseudo-skin factors for partially penetrating directionally-drilled wells. In: Paper SPE 5589, Presented at the 50th SPE Annual Fall Meeting, Dattas Sept (1975) 4. Dash, P.K., Mishra, S., Salama, M.A., Liew, A.C.: Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner IEEE Trans. Power Delivery 15(2), 472–477 (2000) 5. Garrouch, A.A., Lababidi, H.M.S., Ebrahim, A.: An integrated approach for the planning and completion of horizontal and multilateral wells. J. Petrol. Sci. Eng. 44(3-4), 283-301. In press (2004) 6. Hardrnan, P.: Multi-lateral dritting: Pasc present and future. In: Presented at the 5th International Conference on Horizontal Well Technology, Houston, Nov. 9–11 (1993) 7. Lababidi, H.M.S., Garrouch, A.A., Fahim, M.: A fuzzy heuristic approach for predicting asphaltene precipitation potential. Energy Fuel 18(1),242-250 (2004) 8. Metcalfe, P.: Multilateral applications from the North Sea to the South China Sea. In: Presented at the SPE Conference on Opportunities with Multilateral Drilling, Stavanger, 9 Feb (1995) 9. Peaceman, D.W: Representation of a horizontal well in numerical reservoir simulation. In: Paper SPE21217, Presented at the 1lth SPE Symposium on Nurnericat Simulation, Anaheim, Feb. 17–20 (1991) 10. Pucknell, J.K., Clifford, P.J.: Calculation of total skin factors, paper SPE 23106. In: Presented at the Offshore Europe Conference, Aberdeen, 3–6 Sept (1991) 11. Ramakrishna, G., Rao, N.D.: Fuzzy inference system to assist the operator in reactive power control in distribution systems. IEEE Proc. Gen. Trans. Distrib. 145(2), 133–138 (1998)
Analysis of Drilling Trajectory and Casing Design for Straight and Deviated Wells in a Malaysian Oil Field Nada Ahmed Abbas Ahmed Malek1 , Elhassan M. Abdallah1(B) , Mohd Azraai Miswan1 , and Yasir M. F. Mukhta1,2,3 1 Department of Chemical and Petroleum Engineering, UCSI University, Kuala Lumpur,
Malaysia {1001645423,elhassan,azraai}@ucsiuniversity.edu.my 2 Sudan University of Science and Technology, Khartoum, Sudan 3 China University of Petroleum-Beijing, Beijing, China [email protected]
Abstract. The drilling trajectory is optimized for maximum output. In the past, the common drilling methods included a straight line or a vertical well. The direction in which the well is drilled is referred to as the well trajectory. Wellbore trajectories can be classified into vertical and directional wellbore trajectories, including deviated and horizontal wellbores. The current study is to discuss the various well trajectories and casing designs applicable to reservoir formations. The study deals with the challenges, methodologies, and expected outcomes for each of the well trajectories and casing designs presented. Three wells (BAHRA1, BAHRA2, and BAHRA3) were drilled under one platform using a Jack-up rig, each of which was subjected to different slots, for example, BAHRA1 in E1. Three designs, such as S-type, J-type, and Slant-type, were drilled in Compass Software for each well, and three wells were drilled at different reservoir depths. Following the next strategy, CasingSeat Software was used to implement the best and desired casing for each Compass trajectory. Thus, the result of CasingSeat being inserted into StressCheck and the lowest cost design based on the casing grade chosen based on safety factors. Consequently, BAHRA1 (design 1-a), BAHRA2 Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 120–132, 2023. https://doi.org/10.1007/978-981-99-2649-7_12
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(design 2-a), and BAHRA3 (design 3-c) were chosen for implementation based on accessibility (inclination), casing design, and the minimum. Keywords: Drilling · Drilling Trajectory · Analysis of drilling wells
1 Introduction Oil and different Hydrocarbons are cited to surface through a hole known as well. Oil wells can be drilled by various drilling methods to increase the oil production economically. Conventional wells are the most in many instances drilled wells today. These wells are referred to as conventional/ traditional wells are as they are drilled in the popular manner in which the well is drilled vertically, by locating drilling platform right above the reservoir. Also, Wells with inappreciable deflection are also known as conventional wells. Horizontal wells are another type of wells. These types of wells are drilled at an angle of eighty degree to a vertical wellbore. It is a method being used to retrieve oil and natural gas in condition of difficult direct accessibility to the reservoir or due to an abnormal shape of the reservoir. This technique is most commonly active in recent years it has made it possible to access the type of reservoirs which were previously considered inaccessible. A more complex able type of unconventional well is a Multilateral well. Multilateral wells have several branches extending out from the primary borehole to access multiple parts of a reservoir. A drilling rig is an integrated system used to drill the earth subsurface all the way to the Hydrocarbon reservoir through various formations present between the surface and the target. There are numerous conceivable hole sizes.
2 Methodology and Experimental Setup Halliburton’s COMPASS and CasingSeat programming are utilized to reenact wellbore directions and casing designs. These software assists in determining what is accessible from a reservoir upon entering particular well plans. Such plans can be upgraded for respectability, productivity, cost, output, and safety. COMPASS is used for directional well planning and anti- collision analysis that enable the user to direct the drill bit to the profitable pay zone. COMPASS software is able to optimize drilling trajectories based on cost, drag, anti-collision or torque criteria. The software also has an option to recommend most appropriate well to sidetrack that can save days of trial-and-error analysis which are generally costly. CasingSeat is a software that assists in determining casing setting depth and casing or wellbore designs. Companies save significantly on casing cost by simulating casing design in the early completion plan process. The software has permissible-hole and casing-size combinations and provides layer/ lithology-based characterizations of subsurface boundary conditions and operating limitations, including the ones related to wellbore stability, minimum overbalance, and differential sticking. It also provides topdown, and bottom-up solution methods based on permissible drilling depths and setting depth requirements respectively, for ranking and identifying casing schemes.
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Stress check casing-design software takes the trial and error out of designing casing liners, and tubing strings and helps to minimize the cost of the well tubulars.it automatically generate the lowest-cost casing design based on user defines loads. This software enables quick, accurate evaluation of casing wear limits, minimum cost-design solution.
3 Results and Discussion 3.1 Case Description 1 (Compass Software) BAHRA1 (well1) has three designs to hit the target K that is at 9069.2 ft (TVD). • Design 1-a is a J-type: this well is drilled vertically until it reached the 2500 ft (TVD) with 0° inclination. Starting from 2500ft to 9069.2 ft (TVD) it inclined until it reached 58.37°. KOP at 2500 ft (TVD). • Design 1-b is J-type: Inclination started earlier at 439.3 ft (TVD) with inclination of 22.54° until it reached the pay zone with the same inclination at a depth of 9069.2 ft (TVD). KOP at 439.5 ft (TVD). • Design 1-c J-type: It is drilled vertically to 5000 ft (TVD) and started inclination of 45.65° from a depth of 5819.5 ft (TVD) to the zone of interest at depth of 9069.2 ft (TVD). KOP 5000ft (TVD) (Fig. 1).
Fig. 1. Final Designs for BAHRA1
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Case Description 1 (Casing Seat Software) • Design 1-a: This well is designed to be set for three casing. Conductor casing size 20 in. of a borehole 24 in. settled from a depth from the Mean sea level 34.3 ft to 600 ft and a Top of Cement (TOC) 551.0ft, Surface Casing 13 3/8 in. of a borehole 17 ½ in. set from mean sea level 34.3 ft to 1381.6 ft and TOC is from 551.0 ft to 1381.6 ft and Production Casing 9 5/8 of a borehole 12 ¼ in. from the mean sea level 34.3 ft to 10360.1 ft and TOC is from 1381.6 ft to 2513.2 ft • Design 1-b: This well is designed to be set for five casing. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 408.6 ft and a Top of Cement (TOC) 360.6 ft, Surface Casing 32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 453.8 ft and TOC is from 360.6 ft to 412.4 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3 ft to 991.2 ft and TOC is from 412.4 ft to 900.0 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 3171.9 ft and TOC is from 900.0 ft to 2895.6 ft, Production Casing 13 3/8 in. of a borehole 16 in. from the mean sea level 34.3 ft to 9794.6 ft and TOC is from 2895.6 ft to 9010.0 ft. • Design 1-c: This well is designed to be set for five casing. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 400.0 ft and a Top of Cement (TOC) 354.5 ft, Surface Casing32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 497.3 ft and TOC is from 354.5 ft to 447.9 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3 ft to 993.3 ft and TOC is from 447.9 ft to 901.3 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 2952.5 and TOC is from 901.3 ft to 2697.3 ft, Production Casing 13 3/8 in. of a borehole 16 in. from the mean sea level 34.3 ft to 10562.1 ft and TOC is from 2697.3 ft to 9525.4 ft (Figs. 2, 3 and 4).
Fig. 2. CasingSeat design 1-a
Fig. 3. Casing Seat Design 1-b
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Fig. 4. Casing Seat Design 1-c
Case Description 1 (StressCheck Software) BAHRA1 which has three designs of one well total TVD of 9069.2 ft • Design 1-a: This well is designed to be run with three casing. The 20 in., 13 3/8 in., and 9 5/8 in.. And the suitable grades recommended by the software was K-55, Q-125, T-95 respectively. The total design cost of this design is $436,127. • Design 1-b: This well is designed to be run with five casing. The 42-in., 32 in., 24 in., 16 in. and 13 3/8 in. And the suitable grades recommended by the software was X-46, X-60, X-60, P-110,C-90 respectively. The total design cost of this design is $711,908. • Design 1-c: This well is designed to be run with five casing. The 42-in., 32-in., 24-in., 16 in. and 13 3/8 in.. And the suitable grades recommended by the software was X-60, X-60, X-60, P-110, Q-125 and P-110 respectively. The total design cost of this design is $958,148. 3.2 Case Description 2 (Compass Software) BAHRA2 (well2) has three designs to hit the target 5that is at 12000ft (TVD). • Design 2-b is J-type: Inclination started earlier at 365.4 ft (TVD) with inclination of 18.60° until it reached the pay zone with the same inclination at a depth of 12000 ft (TVD). KOP at 365.4 ft (TVD). • Design 2-c S-type: It is drilled vertically to 3000 ft (TVD) and started inclination of 47.78° until it reached a depth of 7500 ft (TVD) and started decline until reached 0° to the zone of interest at depth of 12000 ft with KOP at 3000 ft (TVD) and Drop Sect. 7500 ft (TVD) (Fig. 5).
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Fig. 5. Final Design of BAHRA 2
Case Description 2 (CasingSeat Software) • Design 2-b: This well is designed to be set for five casing.. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 408.4 ft and a Top of Cement (TOC) 360.4 ft., Surface Casing 32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 610.8 ft and TOC is from 360.4 ft to 560.9 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3 ft to 2363.9 ft and TOC is from 560.9 ft to 2127.3 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 8786.9 ft and TOC is from 2127.3 ft to 8143.8 ft and Production Casing 13 3/8 in. of a borehole 16 in. from the mean sea level 34.3 ft to 12647.4 ft and TOC is from 8143.8 ft to 11530.1 ft. • Design 2-c: This well is designed to be set for five casing. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 400.0 ft and a Top of Cement (TOC) 354.5 ft, Surface Casing 32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 670.5 ft and TOC is from 354.5 ft to 598.0 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3ft to 2670.4 ft and TOC is from 598.0ft to 2424.5 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 9774.1 ft and TOC is from 2424.5 ft to 8949.9 ft and Production Casing 13 3/8 in. of a borehole 16 in. from the mean sea level 34.3 ft to 1314.5 ft and TOC is from 8949.9 ft to 12438.4 ft (Figs. 6 and 7).
Case Description 2 (StressCheck Software) BAHRA2 which has three designs of one well total TVD of 12000 ft • Design 2-b: This well is designed to be run with five casing. The 42-in., 32-in., 24-in., 16-in. and13 3/8 in.. And the suitable grades recommended by the software was X-60, X-60, X-60, P-110,P-110 and T-95 respectively. The total design cost of this design is $1370,919.
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Fig. 6. CasingSeat Design 2-b
Fig. 7. CasingSeat Design 2-c
• Design 2-c: This well is designed to be run with five casing. The 42-in., 32-in., 24-in., 16-in. and13 3/8 in.. And the suitable grades recommended by the software was X-60, X-60, X-60,P-110,T-95 respectively. The total design cost of this design is $1470,165. 3.3 Case Description 3 (Compass Software) BAHRA3 (well3) has four designs to hit the target that is at 5500 ft (TVD). • Design 3-a is a J-type: this well is drilled vertically until it reached the 2000 ft (TVD) with 0° inclination. Starting from 2997.6 ft to 5500 ft (TVD) it inclined until it reached 60.53°. KOP at 2000ft (TVD). • Design 3-b S-type: It is drilled vertically to 1000 ft (TVD) and started inclination of 80° until it reached a depth of 2226.3 ft (TVD) and started decline until reached 12.45° to the zone of interest at depth of 5500 ft with KOP at 1000 ft (TVD) and Drop Sect. 2226.3 ft (TVD). • Design 3-c is a J-type: this well is drilled vertically until it reached the 4200 ft (TVD) with 0° inclination. Starting from 5345.0 ft to 5500 ft (TVD) it inclined until it reached 87.72°. KOP at 4200 ft (TVD). • Design 3-d is J-type: Inclination started earlier at 809.0 ft (TVD) with inclination of 44.91° until it reached the pay zone with the same inclination at a depth of 5500 ft (TVD). KOP at 809.0 ft (TVD) (Fig. 8).
Case Description 3 (CasingSeat Software) • Design 3-a: This well is designed to be set for six casing. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 400.0 ft and a Top of Cement (TOC) 354.5 ft, Surface Casing 32 in. of a borehole 36 in. set from
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Fig. 8. Final Design BAHRA 3
mean sea level 34.3 ft to 437.7 ft and TOC is from 354.5 ft to 400.8 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3ft to 701.8 ft and TOC is from 400.8ft to 701.8 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 1403.3 ft and TOC is from 701.8 ft to 1262.0 ft, Intermediate Casing 13 3/8 in. of a borehole 16 in. set from the mean sea level 34.3 to 2513.8 ft and TOC is from 1262.0 ft to 2271.8 ft and Production Casing 9 5/8 in. of a borehole 12 in. from the mean sea level 34.3 ft to 8296.6 ft and TOC is from 2271.8 ft to 7374.7 ft. • Design 3-b: This well is designed to be set for seven casing.. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 400.0ft and a Top of Cement (TOC) 354.5 ft, Surface Casing 32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 431.7 ft and TOC is from 354.5 ft to 400.0 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3 ft to 689.9 ft and TOC is from 400.0 ft to 613.2 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 1353.5 ft and TOC is from 613.2 ft to 1201.3 ft, Intermediate Casing 13 3/8 in. of a borehole 16 in. set from the mean sea level 34.3 to 6306.5 ft and TOC is from 1201.3 ft to 6019.0 ft, Intermediate Casing 9 5/8 in. of a borehole 16 in. set from the mean sea level 34.3 to 8204.1 ft and TOC is from 6019.0 ft to 7792.1 ft and Production Casing 6 5/8 in. of a borehole 7 1/2 in. from the mean sea level 34.3 ft to 8800.8 ft and TOC is from 7792.1 ft to 8336.4 ft (Figs. 9 and 10). • Design 3-c: This well is designed to be set for six casing. Conductor casing size 42 in. of a borehole 48 in. settled from a depth from the Mean sea level 34.3 ft to 400.0 ft and a Top of Cement (TOC) 354.5 ft, Surface Casing 32 in. of a borehole 36 in. set from mean sea level 34.3 ft to 440.5 ft and TOC is from 354.5 ft to 402.6 ft, Intermediate Casing 24 in. of a borehole 28 in. set from mean sea level 34.3ft to 724.4 ft and TOC is from 402.6 ft to 664.2 ft, Intermediate Casing 16 in. of a borehole 22 in. set from the mean sea level 34.3 to 1522.2 ft and TOC is from 664.2 ft to 1365.1 ft, Intermediate Casing 13 3/8 in. of a borehole 16 in. set from the mean sea level 34.3 to 2855.4 ft and TOC is from 1365.1 ft to 2609.7 ft and Production Casing 9 5/8 in. of a borehole 12
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Fig. 9. CasingSeat Design 3-a
Fig. 10. CasingSeat Design 3-b
in. from the mean sea level 34.3 ft to 9851.4 ft and TOC is from 2609.7 ft to 5152.3 ft. • Design 3-d: This well is designed to be set for five casing.. Conductor casing size 24 in. of a borehole 28 in. settled from a depth from the Mean sea level 34.3 ft to 1167.9 ft and a Top of Cement (TOC) 1036.7 ft, Surface Casing 16 in. of a borehole 22 in. set from mean sea level 34.3 ft to 1250.2 ft and TOC is from 1036.7 ft to 1107.4 ft, Intermediate Casing 13 3/8 in. of a borehole 16 in. set from mean sea level 34.3 ft to 2924.4 ft and TOC is from 1107.4ft to 2609.3 ft, Intermediate Casing 9 5/8 in. of a borehole 12 in. set from the mean sea level 34.3 to 6702.4ft and TOC is from 2609.3ft to 6134.0 ft, and Production Casing 6 5/8 in. of a borehole 7 1/2 in. set from the mean sea level 34.3 to 7521.4 ft and TOC is from 6134.0 ft to 6881.0 ft (Figs. 11 and 12).
Fig. 11. CasingSeat Design 3-c
Fig. 12. CasingSeat Design 3-d
Case Description 3 (StressCheck Software) BAHRA3 which has four designs of one well total TVD of 5500ft • Design 3-a: This well is designed to be run with six casing. The 42 in., 32 in., 24 in., 16 in., 13 3/8 in. and 9 5/8. And the suitable grades recommended by the software was X-60,X-60,X-60,P-110,P-110,Q125, N-80 respectively. The total design cost of this design is $529,665.Details on the minimum safety factor (Abs) shown below.
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• Design 3-b: This well is designed to be run with seven casing. The 42 in., 32 in., 24 in., 16 in., 13 3/8 in., 9 5/8 in. and 6 5/8. And the suitable grades recommended by the software was X-60, X-60,X-60,P-110,Q-125, T-95, N-80 respectively. The total design cost of this design is $917,648. • Design 3-c: This well is designed to be run with six casing. The 42 in., 32 in., 24 in., 16 in., 13 3/8 in. and 9 5/8 in.. And the suitable grades recommended by the software was X-60, X-60,X-60,P-110,P-110,Q-125,N-80 respectively. The total design cost of this design is $561,942. • Design 3-d: This well is designed to be run with five casing. The 42 in., 24 in., 16 in., 13 in. and 95/8 in. and 6 5/8 in.. And the suitable grades recommended by the software was X-60, P-110,Q-125,T-95,N-80 respectively. The total design cost of this design is $609,643.
4 Discussion After analyzing the results for the three wells in the three softwares being mentioned above based on the outcomes. In Bahra1 (well1) design 1-a is to be chosen to be drilled as it is easier to reach the zone of interest at a TVD 9069.2ft and MD of 10360.1ft.However in the StressCheck it shows that 1-a costs $463,127 which is less expensive than the other two designs. It has an inclination of 58.37°while design 1-b starts to incline from the surface which makes it more challengeable and more casing required the will result in high cost too. In BAHRA2 ( well2) 2-a is the best to be selected 2-c and In BAHRA 3 (well 3) 3-c is selected is a it is a normal horizontal well the can be drilled with less challenges and it costs $ 561,1942 (Fig. 13).
Fig. 13. Final well in Compass
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5 Environmental Impact Oil and gas operations may affect animals, organisms, groups or habitats by changing a broad variety of ecological criteria The most hazardous stage will be observed, because it becomes irreversible, in comparison to other potential events, such as oil spills, that may arise at certain times. Oil rigs release oil waste E&P in this process. The key component of these discharges is Water produced that makes up 98 per cent of the overall pollution. It is made up of hydrocarbons that cause water toxicity, and ultimately aquatic pollution. Drilling fluids (mud fluid) discharged while drilling. These include hazardous compounds such as: benzene, zinc, arsenic, chromium, carbon, mercury, barium and other pollutants used for lubricating drill bits and retaining heat, e.g. barium serves as a lubricant and improves mud consistency. High amounts of these metals collected in the seabed, frequently causing: deformity, smothering organisms, genetic disruption and fish embryo extinction. • Air pollution: A single oil rig can pollute up to 7,000 automobiles a day traveling 50 miles (80 km). The major polluting factor is greenhouse gasses (GHG) emitted directly by offshore plants (rigs) and indirectly by pollution from refineries. The gasses causing climate change include: global warming, melting ice at the poles, and water acidification which means that ocean absorbs more of the CO2, that means that marine organism need to grow. • Oil spills: According to numerous causes, such as equipment breakdown, shipping collisions, human error, tectonic phenomena and unpredictable environmental patterns, oil spills are much more frequent. The various adverse effects on aquatic and human life have been triggered by pollutants in the leaked oil. These toxins act as hormones or antimonopoly in the aquatic environment and trigger unusual phenomena
Fig. 14. Impact of Drilling Offshore [Adapted from Alexandra Elbakyan, Environmental impact of deep water, 2016]
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like: deformations of growth, genetic mutations and reproductive problems. Scientists in reality discovered multiple strange details, such as Red crabs contain large amounts of contaminants such as arsenic, barium, chromium and mercury. Birds suffer when their feather loses its waterproofing due to hypothermia. Turtles die of oil-coated food upon ingestion (Fig. 14).
6 Conclusion This study’s goal has been accomplished. For this study, three proposed cases were investigated. To determine which trajectory is most suitable for the selected case with fixed targets at a given distance, three types of well trajectories: L-type, J-type, and Stype were applied to each case with a fixed drilling platform and end of drilling location. In addition, the COMPASS software was used to simulate an optimal well trajectory for comparison with the first three trajectory types. CasingSeat is one of the software tools used in this study to determine the best casing for each well based on data such as pore pressure, fracture gradient, and lithology. Furthermore, this software will determine the appropriate allowable casing OD. The casing, TOC, and Casing shoe were displayed in the active well schematic section. The final step was to enter the CasingSeat results into StressCheck software to calculate the appropriate grades for each casing based on the Pore pressure, Fracture gradient, and Hydrostatic pressure from the CasingSeat Software. Finally, after comparing the technical aspects of each well in the StressCheck Software, the minimum design cost was calculated. Nomenclature Symbol COMPASS TVD KOP TOC MD
Description Computerized Planning and Analysis Survey System True Vertical Depth Kick Off Point Top of Cement Measured Depth
Dimension / Unit Dimensionless ft . ft . ft . ft .
Acknowledgement. In the name of Allah, the Most Gracious and the Most Merciful. All praises to Allah and His blessing for the completion of this thesis. I thank God for all the opportunities, trials and strength that have been showered on me to finish writing the thesis. I would like to extend my appreciation to my Final Year Project supervisor, Mr. Azraai Miswan and my Final Year Project coordinator, Mr. Bonavian Hasiholan for their continuous guidance and deep concerns in my progress with regards to the project. I would also like to extend my gratitude to my family and especially my mother, who has been a source of support and comfort throughout the duration of this project.
References 1. Downton, G., Hendricks, A., Klausen, T.S., Pafitis, D.: New directions in rotary steerable drilling: oil-field review. Spring 12(1), 18–29 (2000)
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2. Shepherd, M.: Types of wells, in M Shepherd, oil field production geology. AAPG Mem. 91, 231–297 (2009) 3. Meehan, D.N.: Geological steering of horizontal wells. J. Petrol. Technol. SPE 29242 46(1), 3–12 (1994) 4. Fayers, F.J., Arbabi, S., Aziz, K.: Challenges in reservoir engineering from prospects for horizontal wells: Petrol. Geosci. 1, 13–23 (1995) 5. Tankersley, T.H., Waite, M.W.: Reservoir modeling for horizontal exploitation of a giant heavy oil field-Challenges and lessons learned. In: Presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, November 4-7, 2002, Calgary, Canada, SPE Paper 78957, 6 (2002) 6. Adams, A.J., Hodgson, T.: Calibration of casing/tubing design criteria by use of structural reliability techniques. SPE Drill Compl. 14(1), 21–27. SPE- 55041-PA (1999). https://doi. org/10.2118/55041-PA 7. Adams, A.J., MacEachran, A.: Impact on casing design of thermal expansion of fluids in confined annuli. SPE Drill Compl. 9(3), 210–216. SPE- 21911-PA (1994). https://doi.org/10. 2118/21911-PA 8. Halal, A.S., Mitchell, R.F.: Casing design for trapped annular pressure buildup. SPE Drill & Compl. 9(2), 107–114. SPE-25694- PA (1994). https://doi.org/10.2118/25694-PA 9. Klementich, E.F., Jellison, M.J.: A service-life model for casing strings. SPEDrill Eng. 1(2), 141–152. SPE-12361- PA (1986). https://doi.org/10.2118/12361-PA 10. Prentice, C.M.: Maximum load casing design. J. Pet Tech 22 (7), 805–811. SPE-2560-PA 1970. https://doi.org/10.2118/2560-PA 11. Carter, D.C., Kortlang, W., Smelcer, M., Troncoso, J.C.: An integrated approach to horizontal well design and planning in Widuri field, offshore southeast Sumatra, Indonesia. In: Proceedings of the Indonesian Petroleum Association, 26th Annual Convention, 2, 135–162 (1998)
How the Oil Recovery Factor Changes in Different Polymer Concentrations on in the Basis of Increasing Well Drainage Area Jabrayil Eyvazov1(B) , Mehri Guliyeva1 , and Urfan Guliyev2 1 Oil and Gas Scientific Research and Design Institute, 88a Hasan Bey Zardabi Avenue, Baku,
Azerbaijan [email protected] 2 Azerbaijan Technical University, 25 Huseyn Javid Avenue, Baku, Azerbaijan
Abstract. Polymer flooding can increase the effectiveness of oil recovery. It is primarily used at the moment to advance oil recovery technology (EOR). The polymer exhibits a high degree of viscoelasticity due to its long-chain structure and high molecular weight. A high viscosity polymer solution is injected into a formation as part of the EOR procedure known as polymer flooding in order to reduce the fluidity ratio, increase the swept volume, and improve oil recovery. When developing an oil and gas field, polymer flooding is useful. When polymer solution and injection water are combined, flow resistance and displacement pressure are increased. The method of polymer flooding involves mixing polymer solution into injection water to make the injection water more viscous, which raises flow resistance and displacement pressure. Additionally, by causing the solution to flow to the low-permeability layer, this will decrease the water phase’s permeability, increase the swept coefficient, improve the water-to-oil mobility ratio, and enhance oil recovery. Keywords: Enhanced oil recovery · Oil recovery factor · Polymer flooding · Polymer concentration · Mobility ratio
Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permis-sion to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 133–140, 2023. https://doi.org/10.1007/978-981-99-2649-7_13
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1 Introduction The process of enhanced oil recovery (EOR), which is a type of oil recovery, includes injecting elements into the reservoir that are not typically found there. The bulk of oil recovery chemicals as well as all oil recovery techniques (drive, push-pull, and well treatments) are covered in this description. Additionally, techniques for enhanced oil recovery are used for in-situ organic pollutant extraction from permeable media. In order to increase output, secondary production techniques are employed to increase depleted pressure in a formation. As the oil or gas in a formation is removed, the hydrocarbons left in the reservoir may become trapped as the pressure in the formation lowers, resulting in either a significant decline in production or complete cessation [1]. Chemical enhanced oil recovery technology known as polymer flooding was initially applied in the late 1960s. In this chemical EOR method, polymer is added to the injected water to increase the viscosity of the fluid and improve oil displacement in reservoirs. According to reports, the Daqing oil field in China saw the first commercial success after implementing the polymer flooding method, which led to an up to 20% improvement in oil recovery. Now that some successful trials have been completed, it is believed that polymer flooding could be a practical EOR technology [2]. Macromolecules are massive molecules and chemical compounds also known as polymers. Polymer molecules are the chemical entities that are produced when a significant number of relatively small and repetitive molecular units, known as mon-omers, are chemically bound together. The chemical process of joining monomers to create polymer molecules is called a polymerization reaction. There have been two fundamentally distinct types of water-soluble and viscosityenhancing polymer chemistries utilized during polymer water flooding and conformance improvement treatments. The first category includes biopolymers like Xanthan gum polymer. The second category includes synthetic polymers manufactured by humans, like those based on acrylamide [3] (Fig. 1).
Fig. 1. Structure of polymers: Polyacrylamide (PAM) and Partially Hydrolyzed Polyacrylamide (PHPA)
Because both the carboxyl groups and the mineral surfaces have a negative charge, the amount of hydrolyzed polyacrylamide that may bind to the surface of rocks reduces. Additionally, due to electrical repulsion between the negatively charged carboxylate groups on the polymer chain, partially hydrolyzed polyacrylamides might increase water viscosity more than un-hydrolyzed polyacrylamide. The lengthening of the polymer
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chains as a result of this repulsion raises the viscosity and fluid mechanical volume of the polymer. The monomer chemical links of the polymer backbone of polysaccharides (also known as poly sugars) are glycoside linkages, which consist of chemical bonds between carbon, oxygen, and carbon. The prolonged molecular conformation of the polymer molecules is brought about by the relatively rigid nature of the multi-stranded molecular complexes of xanthan polymer in aqueous solution. Synthetic polymers employed in compliance enhancement are typically made of extremely flexible molecules with a backbone composed of a single, flexible carboncarbon bond and a very chemically stable carbon molecular chain. The polymer molecule becomes water soluble when it contains chemical groups that are actually water soluble, such as amide groups. Synthetic polymers have become the most popular and soughtafter type of polymer for use in commercial oilfield conformance improvement activities due to its inherent chemical and biological stability, injectivity, and cost considerations [4]. Long-chain organic compounds known as polymers are created by joining smaller molecules called monomers. They are flexible due to their high molecular weight, which ranges from 2 106 to 21 106. PAM, or HPAM (PAM partially hydrolyzed), and Xanthan are two polymers that are frequently used in EOR. Xanthan has been the biopolymer that has been used most frequently for polymer water flooding. It shows the chemical structure of the xanthan biopolymer molecule. A xanthan molecule with a molecular weight of 4 million daltons (atomic mass units) contains about 20,000 repeating sugar monomer units. When microorganisms are fermented to create xanthan polymer, a sizable proportion of cell debris typically ends up in the finished polymer solution [5]. This is another commonly used EOR polymer, with an average stated molecular weight of 1 × 106 to 15 × 106 . A biopolymer called xanthan polymer is created when glucose is fermented in order to shield microorganisms from dehydration [6]. This procedure makes the polymer particularly sensitive to bacterial attack on the surface, even after it has been injected into the reservoir. The key benefit of Xanthan polymer over HPAM in EOR is that it is more resistant to the salinity and hardness of brine. Additionally, Xanthan does not have the same tendency to retain as PAM’s, hence it has less of an impact on lowering reservoir heterogeneity due to the adsorption of molecules on the surface [7]. For polymer flooding and conformance improvement treatments in polymers and polymer-gels, acrylamide polymers have been the most widely used synthetic polymer family. This is largely because of worries about the price and supply, as well as chemical resistance and biological stability. Improved sweep efficiency and hence increased oil recovery are the two main objectives of polymer flooding, which are accomplished by the following procedures (Table 1): • Reduction in the water to oil mobility ratio; • Reduction in the amount of capillary trapped oil; • Increase in the viscosity of the injected fluid.
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Range
Oil Viscosity
From 10 to 3000 cp
Reservoir temperature
up to 120 C
Reservoir permeability
10 md to 10 Darcy
Reservoir type
sandstone
Oil gravity
>15 API
Water salinity
50%
Water injectivity
Good
This graph shows the screening standards for polymer floods. This criterion will be used to determine which reservoir to inject polymer into [8]. Polymer is added to water to increase viscosity, which lowers the water-oil mobility ratio. The efficiency of the areal, vertical, and displacement (or microscopic) sweeps are improved, which lowers the water-oil mobility ratio and improves oil recovery. Mobility Ratio. Based on the study of DYES, CAUDLE and ERICSON (1954), the mobility ratio is defined as: M =
Kw /µw Ko /µ0
where, M- Mobility ratio, Kw - relative permeability to water, Ko -relative permeability to oil, µw - water viscosity, µo - oil viscosity.
Fig. 2. The effect of fingering in water and polymer flooding
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A good displacement occurs when the mobility ratio is equal to or less than one, according to the mobility ratio equation. To achieve a low M, chemicals are added to the injected fluid to increase water viscosity, hence lowering the mobility factor [9] (Fig. 2). This figure shows how polymer added water will push oil towards production well. It sweeps oil from the layers and increases the oil recovery factor. This occurs due to the polymer added water injection [10].
2 Experimental Part In this study, Shallow Water Gunashli has been chosen for polymer flooding. The reservoir model was created for X and Fasila horizon. All historical production, injection, pressure, perforation, and PVT data are included in the model. Firstly, history matching was done for the model. Four water injection wells are selected for polymer flooding purposes. They are Gun-085, Gun-086, Gun-087, and Gun-104. It was considered that, from April 2022, it was started to inject polymer added water from these wells. The experiment has been done based on sensitivity analysis of 5 different polymer concentrations in polymer flooding and how it effects to the oil production rate. The main purpose was to determine the optimum polymer concentration in polymer flooding for this oil field.
3 Result and Discussion The study was based on the determination of influence of various polymer concentrations to the oil production rate and hereby to the cumulative oil production. This polymer will increase viscosity of the water, which will be injected into the reservoir. Thus, help to sweep residual oil from the porous media (Table 2). This table represents yearly oil production rate in different concentration of polymer flooding. Oil production prediction shows that, at the end of 2034 year, yearly oil production rate will be 906000 m3 from both horizons. The highest yearly oil production rate will be in polymer flooding with 1000 ppm. By increasing polymer concentration, yearly oil production rate will be decreased. It shows that, optimal concentration for polymer flooding in this case is 1000 ppm (Fig. 3). Here, OPT stands for Oil Production Total. Polymer was increased the viscosity of the displaced fluid and it will help to displace oil from the reservoir. Therefore, oil production total will be increase as a result of polymer flooding (Table 3) (Fig. 4). A water-soluble polymer is added to the floodwater in polymer flooding. The viscosity of water is increased as a result of this. Polymer flooding can improve the oil recovery process in three ways: (1) by affecting fractional flow, (2) by lowering the water/oil mobility ratio, and (3) by directing injected water away from swept zones. The temperature of the reservoir and the chemical characteristics of the reservoir water are the most significant preconditions for polymer flooding. A polymer cannot be kept stable at high temperatures or with high salt in reservoir water, and the polymer concentration will lose the majority of its viscosity. The concentration of 1000 ppm is the optimal concentration value under testing conditions because the recovery degree rose quickly
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Table 2. Yearly oil production rate (m3 ) in different concentration of polymer flooding over the years Years
Polymer concentration, basic case
500 ppm
1000 ppm
1500 ppm
2000 ppm
2500 ppm
2022
1394
1473
1471
1444
1427
1416
2023
1345
1567
1565
1482
1432
1406
2024
1311
1550
1551
1491
1423
1392
2025
1266
1484
1487
1456
1393
1358
2026
1219
1417
1420
1405
1353
1318
2027
1175
1384
1385
1350
1316
1285
2028
1136
1365
1368
1316
1287
1256
2029
1095
1338
1337
1287
1239
1221
2030
1057
1359
1352
1262
1204
1185
2031
1019
1344
1351
1224
1178
1148
2032
984
1296
1305
1200
1155
1117
2033
943
1247
1255
1186
1123
1086
2034
906
1209
1219
1194
1090
1059
Fig. 3. Yearly oil production rate in different concentration of polymer flooding
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Table 3. Oil production total in different concentration of polymer flooding over the years Years
Polymer concentration basic case
500 ppm
1000 ppm
1500 ppm
2000 ppm
2500 ppm
1000 m3
1000 m3
1000 m3
1000 m3
1000 m3
1000 m3
2022
157018
157091
157089
157062
157045
157034
2023
158363
158658
158654
158544
158477
158440
2024
159674
160208
160205
160035
159900
159832
2025
160940
161692
161692
161491
161293
161190
2026
162159
163109
163112
162896
162646
162508
2027
163334
164493
164497
164246
163962
163793
2028
164470
165858
165865
165562
165249
165049
2029
165565
167196
167202
166849
166488
166270
2030
166622
168555
168554
168111
167692
167455
2031
167641
169899
169905
169335
168870
168603
2032
168625
171195
171210
170535
170025
169720
2033
169568
172442
172465
171721
171148
170806
2034
170474
173651
173684
172915
172238
171865
Fig. 4. Oil production total in different concentration of polymer flooding
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and the water content fell quickly when the polymer concentration was 1000 ppm. The degree of recovery increases as the slug size increases. Polymer concentration is a key aspect in the effect of polymer flooding. The higher the polymer concentration, the higher the viscosity of the polymer solution, the bigger the water cut reduction range, and the higher the polymer flooding recovery rate under experimental circumstances. The bigger the polymer solution slug, the greater the reduction in water cut and the better the polymer slug flooding recovery rate.
References 1. de Aguiar, K.L.N.P., de Oliveira, P.F., Mansur, C.R.E.: A comprehensive review of in situ polymer hydrogels for conformance control of oil reservoirs, oil & gas science and technology – Rev. IFP Energies nouvelles 75, 2–3 (2019) 2. Lyons, W.C., Plisga, G.J.: Standard Handbook of Petroleum and Natural Gas Engineering, pp. 87–89. Gulf Professional Publishing, s.l. (2011) 3. Tapdigov, S.Z., Ahmad, F.F., Hamidov, N.N., Bayramov, E.E.: Increase in the efficiency of water shut-off with the application of polyetylenpolyamine added cement. Chem. Prob. 20(1), 59–67 (2022) 4. Medad, T.: Polymer Flooding EOR. s.l. : Statoil ASA, pp. 11–12 (2006) 5. Littmann, J.: Polymer Flooding: Developments in Petroleum Science, vol. 24, pp. 10–11. Elsevier Inc, Amsterdam (1988) 6. Amro, M.M.: Investigation of polymer adsorption on rock surface of high saline reservoirs. Soc. Petrol. Eng. 4–5 (2002) 7. Huifen, X., et al.: Effect of elastic behavior of HPAM solutions on displacement efficiency under mixed wettability conditions. s.l.: SPE 90234, pp. 6–7 (2004) 8. Sun, Y., Fang, Y., Chen, A.: Gelation Behavior study of a resorcinol-hexamethyleneteramine crosslinked polymer gel for water shut-O_ treatment in low temperature and high salinity reservoirs. Energies 10, 913 (2017) 9. Sheng, J.: Modern Chemical Enhanced Oil Recovery (Theory and Practice), pp. 4–5. Elsevier Inc, USA (2011) 10. Wang, D., et al.: The influence of visco-elasticity on micro forces and displacement efficiency in pores, cores and in the field. s.l.: SPE 127453. pp. 2–3 (2010)
The Effect of Sand Production to the Well Drainage Area Jabrayil Eyvazov1(B) , Mehri Guliyeva1 , and Urfan Guliyev2 1 Oil and Gas Scientific Research and Design Institute, 88a Hasan Bey Zardabi Avenue, Baku,
Azerbaijan [email protected] 2 Azerbaijan Technical University, 25 Huseyn Javid Avenue, Baku, Azerbaijan
Abstract. One of the main issues facing the oil and gas industry is the generation of formation sand into a well because of its detrimental effects on well productivity and equipment. The majority of the time, it is discovered in shallow, immature geological deposits with little to no spontaneous cementation holding individual sand grains together. When the wellbore pressure is lower than the reservoir pressure, drag forces are created during fluid production that contribute to the development of sands. In the event that the formation’s restraint forces are exceeded, sand will be drawn into the wellbore. There is no market for the sand that is created. On the other side, formation sand has the potential to gather in surface vessels and degrade equipment in addition to plugging wells. Formation sand control is expensive and typically involves either lowering production or implementing control measures.
1 Introduction Sand production is anticipated to become an issue at some time throughout the field’s life because the majority of the world’s oil and gas reserves are found in sandstone reservoirs. When the reservoir sandstone is vulnerable to failure under in situ stress levels and the imposed stress variations brought on by hydrocarbon production, sand generation happens during the hydrocarbon production from a well [6]. The failed rock is transported by the oil or gas flow, which results in a number of issues, including sand Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permis-sion to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 141–146, 2023. https://doi.org/10.1007/978-981-99-2649-7_14
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disposal, well integrity, and erosion of the surface infrastructure. On the other hand, it has been demonstrated that limiting sand generation increases a well’s productivity and, if accepted, may completely replace the need for sand management. Sand production is anticipated to become an issue at some time throughout the field’s life because the majority of the world’s oil and gas reserves are found in sandstone reservoirs. When the reservoir sandstone is vulnerable to failure under in situ stress levels and the imposed stress variations brought on by hydrocarbon production, sand generation happens during the hydrocarbon production from a well [6]. The failed rock is transported by the oil or gas flow, which results in a number of issues, including sand disposal, well integrity, and erosion of the surface infrastructure. On the other hand, it has been demonstrated that limiting sand generation increases a well’s productivity and, if accepted, may completely replace the need for sand management [1]. Normal drilling and reservoir management operations result in sand production. Under the influence of physical (earth stress) and chemical forces, sand particles separate from the rock matrix structure. To develop a field as efficiently as possible, one must understand the mechanism of sand generation in terms of sand, quantities, and sand-producing patterns in the reservoir. The formation’s strength, flow stability, viscous drag forces, and pressure drop into the wellbore are all factors in the mechanisms that lead to sand production. Formation strength, in-situ stress, and production rate are crucial variables that affect how accurately sand production potential and sand output are predicted [8]. Additionally, there are formation features, pressure drawdown, reservoir pressure, produced fluid kinds and phases, natural permeability, formation cementation, compressibility, exposed surface to flow, and reservoir depth. Creating analytical and empirical methods for predicting sand production is necessary. Sand output is correlated empirically with one or more characteristics, such as porosity, flow, or drawdown. Rock stresses are related to analytical methodologies. Sometimes, analytical methods based on numbers are employed. Additionally, there are formation features, pressure drawdown, reservoir pressure, produced fluid kinds and phases, natural permeability, formation cementation, compressibility, exposed surface to flow, and reservoir depth. Creating analytical and empirical methods for predicting sand production is necessary. Sand output is correlated empirically with one or more characteristics, such as porosity, flow, or drawdown. Rock stresses are related to analytical methodologies. Sometimes, analytical methods based on numbers are employed [10]. Soft or weakly cemented formations have long been a concern for sand production. The end consequence is typically decreased production as a result of formation sand and fines clogging separators, surface flow lines, tubular flow lines, screens, and perforations. Casing erosion and damage to surface facilities are other potential problems, in addition to damaging pumps or other downhole equipment. [9] Sanding issues could really result in casing and/or hole collapse, which would result in the loss or recompletion of a well. Traditional methods used to reduce the impact of sand production include: 1. 2. 3. 4.
Critical Production Rate Gravel Packing Sand Consolidation FracPacking
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5. Oriented and/or Selective Perforation 6. Combination of the above techniques Based on sand characteristics and failure mechanism, completion strategies are chosen. Based on sand characteristics, laboratory testing and mathematical models utilized for sand prediction are chosen [4]. There are two categories of sand control techniques: passive sand management and active sand control equipment (Active). Without putting in down-hole equipment or utilizing a key production rate, sand management refers to surviving with sand production. This approach is not permitted in all industries because the required production rate might not be feasible in that industry. The second kind of sand control should be applied in this situation. For various completions and well designs, different down-hole equipment is available [2]. With Sand Management, production is managed by the monitoring and control of well pressures, fluid rates, and sand input instead of the conventional sand control methods that are typically used. Numerous wells in the North Sea and elsewhere have used Sand Management in conventional oil and gas production over the past four years. Due to self-cleanup brought on by the episodic sand bursts that occur, it has nearly always proven to be successful and generated highly favorable well skins. Each of the wells where sand management has been successful has shown greater oil or gas production rates. These low skins have in turn caused higher productivity indices. Additionally, costly sand control devices are avoided, and it is ensured that future well interventions are feasible [5]. Often, slowing down production is not a viable solution to the problem of excess sand output. Therefore, using sand control strategies is advised. For the completion of wells, sand control methods and extra equipment are used. Although this equipment uses a variety of methods to stop formation sand from entering the wellbore, it reduces reservoir productivity. On the other hand, the sand control method results in an additional skin factor. This suggests that when choosing a sand management strategy for a sand producing well, the magnitude of the skin is also a crucial consideration. Therefore, it is crucial to understand the skin factor of a method and properly assess production economically over a given time frame before selecting one to stop the production of sand. This study examines the cutaneous effects of several sand control techniques and identifies the most effective, economically sound technique [3]. Research based on how modern sand control method can increase oil production and can prolong well lifetime and underground and surface equipment lifetimes. Project was conducted on Prosper model. The project based on Well № 625 in Darvin bankasi field. There is sand production problem in this well. Before using sand control method daily oil production rate was 1.4 t per day. Sand control method was consisted of fastening wellbore zone with polymer-containing tamponing material. Daily oil production rate was increased to 1.6 t per day. This article based on how daily oil production rate will be in case of using gravel pack method (Figs. 1, 2, 3 and 4).
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Soluon GOR , m3/m3
119
Oil Gravity, kg/m3
838.369
Gas Gravity,kg/m3
0.81328
Water Salinity, ppm
0
Fig. 1. PVT parameters for the well model
Reservoir
100
Permeability,md Reservoir Thickness,m
18
Drainage Area,m2
77494.3
Dietz Shape Factor
1.96133
Wellbore Radius
0.07
Fig. 2. Reservoir and well parameters for the well model
Sand production problems are causes to water cut. Therefore, it has been analyzed how daily oil production rate will be in 20, 30, 40% of water cut. As shown from nodal analysis, daily oil production rate will be highest in case of water cut = 20%. Daily oil production rate will be 7.2 t per day when gravel pack is utilized in the well. By using gravel pack we can increase daily oil production rate 5 times.
The Effect of Sand Production to the Well Drainage Area
Gravel Pack Permeability, md
35000
Perforaon Diameter,m
0.0254
Shot Density,1/m
6
Gravel Pack Length ,m
0.0508
Perforaon Interval,m
30.48
Perforaon Effiency,m
0.5
Method
Mulphase
145
Fig. 3. Gravel Pack parameters for the well model
Fig. 4. Daily oil production rate in different water cut values
2 Conclusion This research shows that, by using gravel pack method, it is possible to increase daily oil production rate of well. This method will increase water production from the well. As a result of using gravel pack method, heavy components will become to flow to the
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wellbore zone. Afterwards, oil well can require using additional external energy –for example gas lift method. In this case, operational expenditure will increase for this well. It requires economical evaluation for better estimation. Utilization of gravel pack method will save layer and reservoir integrity. Because, regular sand production is destroying reservoir integrity and therefore reduce well drainage area. Except that, this will increase well and wellbore and surface equipment lifetime
References 1. 2. 3. 4. 5. 6. 7.
8. 9.
10.
Dehgani, M.: Oil Well Sand Production Control, pp. 1996–2000 Hassan, W.: Selection of optimum sand control for a field in PCSB operation, pp. 3–5 (2008) Khamehchi, E., Ameri, O., Alizadeh, A.: Choosing an optimum sand control method, pp. 1–10 Abass, H.H., Nasr-El-Din, H.A., BaTaweel, M.H.: Saudi Arabian Oil Company sand control: sand characterization, failure mechanisms, and completion methods, SPE 77686 (2002) Tronvoll, J., Dusseault, M.B., Sanfilippo, F., Santarelli, F.J.: Oifield Rock Mechanics Integrated Services (ORMIS) The Tools of Sand Management SPE 71673 (2001) Isehunwa, S.O., Ogunkunle, T.F., Onwuegbu, S.M., Akinsete, O.O.: Prediction of sand production in gas and gas condensate wells. J. Petrol. Gas Eng. 8(4), 29–35 (2017) Ikporo, B.: Okotie Sylvester Niger Delta University, Amasoma, Bayelsa State Department of Petroleum and Natural Gas Engineering, Federal University of petroleum resources Effect of Sand invasion on Oil Well Production: A Case study of Garon Field in the Niger Delta, pp. 64–71 Tananykhin, D., Saychenko, L.: Sand control methods for the development of oil & gas fields with hard to recover reserves. Espacios (ISSN: 07981015) 38(48), 31 (2017) Maduabuchi, O.F., Appah, D., Okoro, E.S.: Centre for Petroleum Geosciences, School of Graduate Studies, University of Port Harcourt, Port Harcourt, Nigeria. Petroleum Technology Development Fund Gas Research Group, University of Port Harcourt, Port Harcourt, Nigeria Relative Study of Internal Gravel Packing and Chemical Sand Consolidation: Sand Control Techniques of Niger Delta Wells, 6(5), 261–268 e-ISSN: 2320–0847 p-ISSN : 2320–0936 Alakbari, F.S., Mohyaldinn, M.E., Muhsan, A.S., Hasan, N., Ganat, T.: Chemical sand consolidation: from polymersto nanoparticles. Polymers 12, 1069 (2020). https://doi.org/10.3390/ polym12051069
Pressure Minor Losses Coefficient in Cracked Pipelines Jafar A. Ali(B) Department of Petroleum Engineering, Faculty of Engineering, Koya University, Koysinjaq, Kurdistan, Iraq [email protected]
Abstract. The present study aims to comprehend the behavior of fluid flow in a pipeline using experimental and numerical methods. Crude oil pumped into a pipe with a fixed velocity and pressure, 1.1 m/s and 16.5 kPa, respectively. The experiment was conducted in a horizontal pipe with a diameter of 24 mm to study the pressure drop due to crack without leakage. Flow meter and pressure gauges were utilized to measure the flow and pressure. 20 trials were carried out with different crack size in the pipe, at each trials the major and minor pressure losses were measured. The results revealed a noticeable pressure drop in the pipes with cracks. The pressure losses increase with increasing the length of the cracks. The obtained experimental results were employed to define a coefficient to predict the value of minor losses as function of crack length and pipe diameter. Keywords: Pipeline · Cracks · Pressure Drop · Minor Losses · CFD
1 Introduction Minor losses in pipes come from changes and components in a pipe system. This is different from major losses because those come from friction in pipes over long spans. If the pipe is long enough the minor losses can usually be neglected as they are much smaller than the major losses [1]. Pipe fittings like elbows, bends and valves refer to the Copyright 2022, IPPTC Organizing Committee This paper was prepared for presentation at International Petroleum and Petrochemical Technology Confer-ence 2022 held online between 12-13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publi-cation review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Elec-tronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain con-spicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 147–154, 2023. https://doi.org/10.1007/978-981-99-2649-7_15
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minor losses and they are essential in many industrial applications, such as hydraulic, nuclear and chemical engineering systems, and the prediction of the pressure drop across these fittings is crucial in the design of piping systems [2]. The pipelines are vulnerable to losing their functionality by internal and external corrosion, cracking, third party damage and manufacturing flaws [3]. The causes of the failures are either intentional (like vandalism) or unintentional (like device/material failure and corrosion) damages [4]. Measuring the head losses in the pipe lines is more difficult than in straight pipe flows due to the additional sources of local energy dissipation caused by secondary flow and flow separation [2]. The structure and formulation of the pipe system are among the major driver forces impacting on the coefficient value of the losses, geometry plays an important role and K (minor loss coefficient) will vary depending on the size and configuration of the pipes [5]. In addition to the frictional and connectional losses there are some losses of pressure in the pipe where crack exist, pressure drop in the crack zone even where no leakage occurs [6]. Henrye Fauske considers the pressure losses due to friction, bends, and protrusions in the crack flow path [7]. Fluid flow may decrease in tortuosity with increasing crack opening displacement [8]. Variation in head loss with the width of the fissure when water flows through L-shaped fissures [9]. The pressure profiles are independent of oil viscosity, although the formation of core flow reduces the pressure drop for viscous oils [10]. Related to the models for the estimation of load losses in pipes, other researchers developed a theoretical experimental equation take in consideration the flowed and dense phases [11]. This paper aims at finding the value of minor losses in cracked pipes including fittings such as valves, tees, reducers, elbows and entire connections in pipe line system. The paper is developing a model to predict the value of head loss due to crack in pipe.
2 Experimental Setup The experimental work was carried out at the laboratory at room temperature. Crude oil of properties; density of 841 kg/m3 and dynamic viscosity of 0.003704 kg/m. s is used. The oil is added to a primary tank to be discharged out into a pipe. The pipe length 2 m, inner diameter is 20 mm and pipe thickness is 5 mm. The pipe is made from carbon steel widely used in pipelines manufacturing for oil transportation. A 2 kW centrifugal pump is used to provide enough crude oil with desired pressure head. A valve was located at the discharge point to control the amount of discharged crude into the pipe. Exactly and after the valve, flow meter was installed to measure the velocity of crude inlet the pipe. Pressure gauges were installed at three different locations, at the inlet, crack zone and at the end of the pipe. The process flow diagram is represented in (Fig. 1).
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Discharged tank Pressure gauges Pump
Cistern
Flowmeter
Valve
Fig. 1. Schematic diagram of experimental setup
3 Numerical Simulation The main aim of the current study is to emphasize the empirical works supporting by theoretical. The experiment simulated using CFD package to analyze the flow characteristics inside the pipe. It has done by solving the Navier-Stokes Equation, with the help of commercial simulation software ANSYS (WORKBENCH and FLUNET) [12]. ANSYS software has been utilized to generate a structured mesh grid, 50000 cells were created and the dense mesh grid was around the crack. The representative mesh of the pipe was generated using the block strategy, in which a single block is initially created involving the area of study, then the mesh was refined on the geometry [13]. The physical properties of crude oil used including density, enthalpy, specific heat and viscosity were empirically measured at the laboratory and they were (841 kg\m3, 74100 j\kg, 1.96 at 20 oc and 0.003704 kg\m.s) respectively. The inlet velocity was 1.1 m\s, pressure 16.5 kpa and temperature 290 k. The program then runs with 10000 iterations for the cracked
Fig. 2. Accumulation around the crack.
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pipes, whilst the results converged within 1000 iterations for the pipe with no crack. The flow of the crude was affected by the crack as illustrated in (Fig. 2) and (Fig. 3).
Fig. 3. Crack slowdown the flow.
4 Mathematical Model Energy loss through friction in the length of pipeline is commonly termed the major loss hf . This is the loss of head due to pipe friction and the viscous dissipation in flowing liquid. The magnitude of the major losses depends on the friction factor. The friction factor is a function of the dimensions of the pipe, the material of the pipe is made out of, and the Reynolds number. Several studies have been found the resistance to flow in a pipe is; independent of pressure under which the liquid flows. Linearly proportional to the pipe length, L, inversely proportional to some water power of the pipe diameter, proportional to some power of the mean velocity, u and related to the roughness of the pipe, if the flow is turbulent. Total pressure drop = major losses + minor losses hT = hf + hm
(1)
The pressure drops in a pipe, due to friction, is the major pressure loss hf it is a function of; velocity u, fluid density ρ and viscosity μ, pipe diameter D, pipe surface roughness ε, friction factor f and length of the pipe L. hf = F(f , u, ρ, , L, D)
(2)
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Losses which occur in pipe lines because of bends, elbows, joints, valves, etc.…, are called local or minor losses. The general equation for calculating the minor loss hm of a fitting in a pipe system is: hML =
K
u2 2g
(3)
where; K is the minor loss coefficient for the particular fitting. This is a misnomer, because in many situations they are more important than the losses due to pipe friction. The minor losses are mainly functions of diameter and velocity. The minor losses coefficient for pressure drop due to crack is a function of crack length Lc and pipe diameter. K = F(Lc, D)
(4)
The relation is developed using the theoretical and empirical measured data to have the form (Eq. 5); by using regression the coefficient a was found. The losses due to cracks smaller than the pipe diameter are too small and can be ignored. 2 D (5) K =a b− Lc when, Lc > D
K = 0.7 1 −
D Lc
2 (6)
5 Results and Discussion However, as transporting hazardous substances using miles-long pipelines has become popular across the globe in recent decades, the chance of the critical accidents due to pipeline failures increases [4]. The major threat that occurs in pipelines is leakage. The effects of leakage go beyond repair expense and cost of lost oil or gas, it also significantly affects the human lives and environment [3]. Crack in pipes is changing to fracture if not treated in time; this is leading to pipeline failure and thus resulting in irreversible damages which include financial losses and extreme environmental pollution, particularly when the leakage is not detected in a timely way. As initial stages cracks are causing drop in pressure, then increasing in viscosity of the liquid at the crack zone. This pressure loss is different with the frictional losses. Because of geometry changes at the crack zone, (see Fig. 4) the losses then could be similar to those caused by turbulence occur due to connections and fittings. This kind of losses is called minor losses, even though they are termed “minor”, the losses can be greater than the major losses. For example, when a valve is almost closed the loss can be almost infinite or when there is a short pipe with many bends in it [1].
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Fig. 4. Cracked pipe cross section.
The minor loss coefficient value is dependent on the geometry of the component, and flow characteristics. The values can be estimated using a table of values but this method results in a high degree of uncertainty. Manufacturer testing data should be consulted rather than relying on the representative data. For round elbows, the pressure drop is inversely proportional to the curvature ratio C = R/D, where R is the elbow curvature radius and D is the diameter of the elbow [2]. Sharp-angled elbows suffer from higher localized losses than round elbows due to the even more intense flow separation [2]. There are also minor losses in pressure where sudden expansion or contraction happen, the loss of head in these cases is due to the changes in cross section of the pipe. Similarly, the changes will happen to the pipe cross section when the crack occurs. Furthermore, the rate of deformation (Eq. 7) will be changed for the pipes with crack exactly at the crack zone. This is happened due to change in the thickness of the fluid in the pipe dy. τ =μ
du dy
(7)
where the flow is forced to follow the profile of the crack, the oil particles were slow down, (see Fig. 5). As the crack is widened further, or the driving pressure is increased,
Fig. 5. Oil particles at the crack
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the inertial forces begin to dominate the minor loss [8]. The derived model obtained from the current study is applied on both the experimental collected data and the simulation data, the result is presented in (Fig. 6).
0.8 0.7 0.6
Kc
0.5 0.4 0.3 0.2 0.1 0 0.1
0.2
0.3
0.35 KcT
0.4 D/Lc kcP
0.45
0.5
0.6
0.65
KcM
Fig. 6. Model validation.
6 Conclusion In this research work it is reached to a fact that the crack in the pipelines will cause problem to the flow of the fluid. As the pressure drop and the discharge of crude oil in the pipelines are two important issues in the oil and gas industries. The work concluded that the pipelines that have cracks are less efficient to transport the oil from one location to another as compared to pipes with no cracks. There is a pressure drop in the crack zone even where no leaks occur. In addition, a minor loss coefficient is developed to predict the losses due to cracks in pipelines.
References 1. Balsiger, A., Bastos, L., Behm, J.: Minor Losses in Pipes. Colorado State University (2014) 2. Al-tameemi, W., Office, P., Ricco, P.: Pressure-loss coefficient of 90 deg sharp-angled miter elbows. J. Fluids Eng. 140(6), 198–207 (2018) 3. Golmohamadi, M.: Pipeline leak detection, Master thesis, Missouri University of Science and Technology (2015) 4. Adegboye, M., Fung, W., Karnik, A.: Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches. Sensors 19(11), 1–36 (2019) 5. Frost, W.H.: Minor loss coefficients for storm drain modeling with SWMM. J. Water Manag. Model. 517–546 (2006)
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6. Kamal, K., Ali, J.A.: Modeling the flow of crude oil in cracked pipeline. Int. J. Sci. Res. Sci. Technol. 7(4), 226–233 (2020) 7. Park, J., Cho, Y., Kim, S., Lee, J.: Estimation of leak rate through circumferential cracks in pipes in nuclear power plants. Nucl. Eng. Technol. 47(3), 332–339 (2015) 8. Cox, A.: What are communities of practice? a comparative review of four seminal works. J. Inf. Sci. 31(6), 527–540 (2005) 9. Liu, J., Mou, C., Song, K., Luo, P., He, L., Bai, X.: A fast calculation model for local head loss of non-darcian flow in flexural crack. Water 12(1), 1–15 (2020) 10. Kumar, R., Sankar, G., Mandal, A., Naiya, T.: Studies on emulsified crude oil flow through horizontal pipeline. J. Mod. Chem. Chem. Technol. 7(1), 82–90 (2016) 11. Falconi Borba, M., et al.: Model of pressure losses in pipes during the transport of heavy oil with 11 API gravity. Int. J. Mech. 12, 8–13 (2018) 12. Islam, M., Basak, A., Sarkar, M.: Study of minor loss coefficient of flexible pipes for different bend angles and different bend radius by experiment and simulation. Glob. J. Res. Eng. 16(4), 27–32 (2016) 13. Vasconcellos Araújo, M., Luna, F., Barbosa, E., Farias Neto, S., Lima, A.: Numerical study of oil flow in tee junction with leaks. Adv. Petrol. Explor. Dev. 6(2), 1–11 (2013)
Duvernay Shale Sweet Spot Identification and Resource Evaluation Model Building in Alberta Basin Jing Ran1(B) , Rui Zhou2 , Jin-rui Guo1 , and Na-xin Tian1 1 Sinopec Exploration and Production Research Institute, Beijing, China
{ranjing.syky,guojr.syky,tiannx.syky}@sinopec.com
2 Sinopec International Petroleum Exploration and Production Corporation, Beijing, China
[email protected]
Abstract. Unconventional oil and gas are continuous play as common, besides, sedimentary diagenesis and reservoir characteristic is different in each of them. Maximum usage of information in shale resources evaluation is bottle neck in play exploration and field development. The research defined sweet spot in 2 aspect which are geologic body spatial distribution and real production data statistic, with the combination of traditional geology study method and GIS based production database. Establish individual resource model including 2 aspects in geology and engineer by mapping and 2D matrix analysis based on production big data statistic and geological factor. Three results can be seen. Sequence stratigraphy framework based lithofacies spatial distribution as sweet spot is reliable in Duvernay shale deep basin. Kaybob in the north is favorite area with depth and TOC are main control factors for high production. Multiple parameter mapping overlay in accurate interpreted geology process match well with production big data information and coincide with single well core level observation. High correlation geological factor provides new concept in sweet spot study, contribute to consistent result in geology evaluation and engineer evaluation. The research illustrated a prediction method in unconventional oil and gas, create a multi-data based spatial analysis in sedimentary basin. Sequence stratigraphy framework is a not to scale prediction tool, whereas resources evaluation model is flexible to real conditions. Construct geologic database with existing knowledge, refine new recognition with additional data, then fit it into the base is future work for digital basin description. Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 155–168, 2023. https://doi.org/10.1007/978-981-99-2649-7_16
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J. Ran et al. Keywords: Shale gas · Sweet spot · Resource evaluation · Big data · Canada
1 Introduction The success of the North American shale gas revolution has driven the global shale oil and gas exploration and development upsurge [1]. Meanwhile, the success of China’s continental shale oil and gas exploration and development has further realized the exploration potential of the unconventional oil and gas field globally, promoting China a world class shale player with international pioneers [2, 3]. However, the turbulence of the international geopolitical situation, the requirements of resource countries for their own development and environmental protection, and global climate change have all put forward new requirements for the exploitation of traditional fossil energy. For economic success, producers need to propose a resource evaluation plan integrating geology and engineering according to the real field scenario and change the mind from resource-oriented to data-oriented. As a super basin in North America, the Alberta Basin in Canada has the natural advantage of abundant resources and data. At the same time, operators in Canada lead technology of the surging period. With the detailed work in modeling underground, Alberta Basin is the suitable place to develop new resource evaluation method with data.
2 Geological Overview and Production Situation of Duvernay 2.1 Duvernay Geology Overview Duvernay is known as the deepest source rock in Alberta basin, Devonian shale filled conventional carbonate reservoir has a daily output of over 10,000 wells. Drilling in recent years reveals that Duvernay zone has the typical characteristics of continuous accumulation [4]. In 2017, the Canadian Energy Agency estimated that the Duvernay layer has recoverable natural gas reserves of 449 tcfg, condensate recoverable reserves of 14.5 billion barrels, and oil recoverable reserves of 61.7 billion barrels. The core of unconventional Duvernay in western shale basin is deep basin area along with the NW-SE Cordillera organic belt, which bend syncline and deepen the formation. Kaybob, Brazeau, Buck Lake-Williston Green lies from north to south, ended by Rimbey structure, however, seaway at 385Mya spreading eastwards across the atoll to eastern shale basin and deposit in a shallower platform, presenting Duvernay an 80000 km2 huge bed in secondary order sequence maximum flooding surface period [5] with rich organic matters, 3000–5000 m deep buried. The depositional environment of the Duvernay layer is a shallow-semi-deep anoxic epeiric sea with a water depth of about 150 m, warm water near equator. As a source rock with TOC content of 2–5%, type II kerogen [6], Duvernay is also a producing zone lies between Leduc atolls. There are two stages of exploration concept. First is leading by Shell, treat the target as a sources rock, the main reservoir rock type is bioturbated siliceous, pyritic mudstone (LF4) and Planar laminated siliceous mudstone (LF1). The second stage lead by Chevron and Chinese operators, focus on wavy-laminated siltstones and silty mudstones (LF2) [7] (Fig. 1).
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Fig. 1. Duvernay profile in Alberta Deep basin trend. (Cited from Core Lab 2015, modified)
2.2 Duvernay Production Status Duvernay Shale is a frontier unconventional exploration and development zone in North America and the second largest unconventional pay zone in Canada except for Montney. In 2010, with the support of government taxation, Celtic, Chevron, Shell and other companies first entered, from 2012 to 2013, CNPC and SIPC purchased the assets in and start exploration and development work. After a new round of land policy in 2017, play come into mature stage with long term FDP. According to IHS statistics (2019, now IHS is part of S&P), there are 1,322 wells drilled in the Duvernay zone, including 1,071 wells in the West Shale Basin. The production in this area has continued to increase since 2012. Till April 2021 the play shows that cumulative production of oil is 191.81 mmbbl, condensate is 222.73 mmbbl, and natural gas is 17 tcfg. The main production area located in the West Shale Basin, some are overlap with Montney, condensate is widely accepted as sweet spot. Operating method varies between companies and landscape, production varies with landing zone and treatment. Earlier report from Shell, Encana, and Chevron with single well IP30 190–700 bpd.
3 Resource Evaluation Method Combining Geology and Engineering 3.1 Mapping Based Evaluation Concept Unconventional oil and gas are produced from formations with both characteristics of sources and reservoir [8]. With a comprehensive comparison of the resource evaluation standards of EIA 2006 methodology and the evaluation plans of pioneer companies, unconventional reservoir can be summarized by 4 features: 1. Located in lower part of basin, continuous deposition. 2. The source rock and the reservoir are in the same stratum or the adjacent strata with short distance migration. 3. Pore types are dominated by organic pores, with the porosity of 4–6%, extreme low permeability at 100–200 nD. 4. Horizontal drilling with reservoir treatment. Meanwhile Chinese pioneer shale
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gas evaluation method include 5° about reservoir’s rock depth, thickness, organic matter abundance, RO, and brittleness [9]. Single well EUR economic appraisal turn the market Tech-driven preference rather than Geo-research hooked. Identification of engineering sweet spots and fine-grained reservoir characterization greatly reduces operational risk, the well factory operation technology can reduce the operation cost by about 30%. Simultaneous fracturing technology stabled production and greatly improved initial daily production [10–12]. Operators are chasing new sweet spot with both geology and engineering. Conventional O&G resources evaluation emphasizes geological knowledge [13– 15], transmits information by means of map compilation, connects test parameters with geological concept, realizes quantification of properties and establish Geo-model, then combine well log and seismic data achieve a digital model. With the development of big data and artificial intelligence, core test data and model parameters increase rapidly and trend their way to patterns, merging to well log and seismic data naturally and share the algorithm race to zero, leaving human fell behind in a lower mindset of mapping. Combining graceful geologic concept and data lake is imminent. It is also a way to connect geology side with engineering side, who treat the formation different way but sharing the same physical discipline. North America stratigraphy give the advantages for data and pool forming. Monocline stratigraphic relationship benefits multi parameters stacking [16–19]. This study divides the evaluation parameters into two aspects: commonality and personality, set up key parameters and individual parameters for formation attribute analysis, combined with the production big data, the comparison between the speculative knowledge and the actual knowledge can be revised [20, 21] (Fig. 2).
Fig. 2. Concept of combination in geology and engineering, from geology side to the left the engineering side to the right, data is the connection setting the fast track intelligent. Mapping stands for human idea is the slow track and real-world condition.
3.2 Duvernay Regional Evaluation in West Shale Basin Parts of the Duvernay play have entered the development stage and are in the detailed evaluation stage. Deep basin zone can be divided into 3 areas from north to south.
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GIS spatial graphic interpolation method is the most suitable method for this stage of evaluation [22]. In this study, evaluation parameters and preferences are based on practice summaries from EIA, USGS, Exxon Mobil, BP, and Chevron. Main parameters such as reservoir thickness, TOC content, and Ro maturity are important indicators for a common unconventional play. Duvernay is an ‘Integration of source and storage’, which can be identify by both reservoir parameters and source rock parameters, and both has a relationship with engineering perspective. Production data is from IHS Accumap 2019 for planar show, after stacking different attributes, key parameters and individual parameters can be analyzed. Accumulation Control Factors and Key Parameters. 627 wells drilled in Duvernay area are above the lower production limit, there are 2 concentration areas of high yield, the north one and the south one, which of both related with structures. Record the limitation of high yield. Record high and low number of each parameter stacking with high yield area in the base map. Compare 3 deep basin areas and 1 conventional area with high production area in each parameter. Within the 6 sets of number, choose two outstanding marks in red. If there are similar ones, mark it red too. The results shows that northern Kaybob area has the most similar characteristics to the high-yield area. Pore pressure gradient in reservoirs, Ro in source rocks, and orthogonal faults in engineering parameters compose the basic control factor of hydrocarbon rich zone. Kaybob is similar to high yield gas zone. Except the common part, key parameter of Kaybob is thicker reservoir formation, higher TOC, higher effective porosity, and structure fault control. Fault is a commonly used reservoir evaluation index in engineering evaluation. From the observation of the Duvernay formation, high-yield wells are located at the fault endpoints. The regional high-yield oil and gas areas developed by orthogonal faults to the north and monoclinic fault to the south. Hydrocarbon accumulation different from north to south. Orthogonal faults derived from cubic crystalize carbonate (Table 1 and Figs. 3, 4, 5). Table 1. Duvernay E&P Potential Appraisal Parameters Matrix Reservoir Parameter
Source Parameter
Engineer Parameter
Thickness
Eff. Por
Quartz
Carb.Th ickness
Geothermal Grad.
Por. Pres.Grad
TOC
Ro
m
%
%
m
0C/km
psi/ft
%
%
H.Oil Prod.
16-42
2-6
30-50
5-10
35-40
0.725-0.8
2-3
1.2-1.3
40-100
28003500
H.Gas Prod.
32-48
5-6
20-50
3-14
35-40
0.775-0.85
3-5
1.2-1.4
25-75
28003700
Kaybob
32-48
4-5
20-40
5-14
30-35
0.775-0.85
3-5
1.2-1.3
40-75
28003400
HI
Structure
m
Brazeau
23-26
2-3
30-35
5-15
30-35
0.75-0.775
2-3
>1.4
20-90
Buck Lake
27-30
4
30-35
γ /2
(3)
so that coarsening will be ceased once the surface elasticity E is large enough and bubble sizes no longer grow. In many previous studies Surface-active nanoparticles (NPs) were reported to significantly improve foam stability [14–17]. As the abundant, low cost, and environmental friendly materials with high attachment energy at the interface, NPs tend to irreversible adsorb at interface, which benefits stable foams and emulsions against coalescence and coarsening. Moreover, various surface modifications can be conducted on NPs to provide tunable interfacial and colloidal properties, to achieve desired hydrophilic-lipophilic balance and salt tolerance [18]. However, one of the major challenges for NPs to be applied for reservoir applications is the issue of salt tolerance. According to the classic DLVO theory, stable dispersion of particles in aqueous phase can be achieved when electrostatic repulsion, steric repulsion and Van Der Waals (VDW) attraction in aqueous phase are balanced [18, 19]. However, in concentrated brine, the high ionic strength screens the electrostatic repulsion, leaving the VDW attraction as the dominating effect [18]. Furthermore, the divalent ion bridging between negatively-charged silica NPs enhances the aggregation of NPs and form severe precipitation in brine [19]. Thus a necessary step to solve this problem is to graft ligands on silica NP surface so that additional steric stabilization against VDW attraction is provided in high salinity brine, and a portion of SiO− sites on silica surface is replaced to reduce divalent ion bridging [20]. In this study, we present a foam formulation with an anionic surfactant as the foaming agent and a functionalized silica NP as foam stabilizer. The rheological, colloidal and interfacial properties of the formulation are studied through viscosity, zeta potential and surface tension measurements. The NPs grafted with binary ligands show balanced colloidal stability in concentrated brine, and thus can be used to stabilize foams due to strong adsorption at the gas-water interface. The effect of NPs lead to further understanding of how destabilizing mechanisms on foams are retarded. Moreover, the potential of foams to improve oil displacement efficiency in porous media is verified through microfluidic tests. The clarified effect of foams in presence of functionalized NPs to increase oil
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production could be of significant benefit in the selections of surface-active agents for reservoir applications.
2 Experimental Section 2.1 Materials Surfactant AOS C14-16 from Macklin (Sodium alpha-olefin sulfonate) was used as foaming agent in this study. LUDOX AS-40 (40 wt%) colloidal silica nanoparticles were purchased from Aldrich and used as received. Silane agent 3-glycidyloxypropyl trimethoxysilane (purity of 98%) was purchased from Innochem, and dimethoxydimethylsilane (purity of 95%+) was purchased from Thermo Scientific. The structures of the three chemicals mentioned above are shown in Fig. 1. Methanol (anhydrous, purity of 99.8%) was purchased from Sinopharm. The procedure of the two-step surface modifications on silica NP was described in great details and can be found somewhere else [20]. The surface coverages of ether diol (ED) and dimethyl (DM) ligands grafted on the silica NP are roughly 2 and 1.5 μmol/m2 . The foaming formulation was prepared both in 1 g/L sodium chloride and a high salinity water (HSW), with composition of 41.041 g/L NaCl, 2.384 g/L CaCl2 ·2H2 O, 17.645 g/L MgCl2 ·6H2 O, 6.343 g/L Na2 SO4 , 0.165 g/L NaHCO3 .
a).
b).
O
O
c).
OH
O
Si O
OH
O Si O
Fig. 1. Chemical structure of a). AOS, b). 3-glycidyloxypropyl trimethoxysilane and c). dimethoxy dimethylsilane
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2.2 Aqueous Phase Viscosity The viscosities of solutions with AOS and NP in brines with different salinities were measured using a hybrid rheometer (TA Instrument, US). Samples were prepared at different concentrations, and the viscosity was measured under the shear rate between 0.1 and 500 s−1 . 2.3 Surface Tension Surface tension of the foaming solution was measured using the plate method by DCAT 21 (Dataphysics, Germany). Each reported surface tension value was averaged from at least three replicated measurements at room temperature 25 °C. 2.4 Zeta Potential Zeta potential of NPs in the solutions were also measured with a Zetasizer nano Z (Malvern, UK) with samples loaded in the folded capillary cells (DTS1070), and was calculated using Smoluchowki model from electrophoretic mobility of the NPs. Each sample was measured 3 times and the average was recorded. 2.5 Bulk Foam Tests Bulk foam stability was studied through a Dynamic Foam Analyzer DFA-100 (Kruss, Germany). The solution was loaded in to the cylinder and nitrogen was bubbled into the solution at flow rate of 0.1 mL/min for 1 min. Then the foam height and bubble sizes were scanned and lively recorded for an hour. The measurements were repeated for 3 times to ensure reproducibility. 2.6 Microfluidic Tests Microfluidic tests were conducted under ambient conditions to evaluate the oil displacement efficiency of foams. The network pattern of the glass microfluidic chip was in-house developed to form a 4 cm × 4 cm pore structure. The porosity of the micromodel is 39.44%, with pore size ranging from 120 to 480 μm [21]. Crude oil was first injected into the model to setup oil saturation. Then water was injected into the micromodel at flow rate 0.005 mL/min to displace the oil with the real time images recorded. Then the foaming solution and air was co-injected at a total flow rate 0.005 mL/min and foam quality of ~80% to displace the residual oil. The gas and aqueous phases passed through several layers of meshes in the pipeline to generate foams before entering the microfluidic chip. The injection volume was controlled by the injection time at the fixed injection rate. The injection line was prefilled with the injected solution through the bypass line to minimize the dead volume. The images recorded were analyzed and the oil recovery during each injection step was calculated.
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3 Results and Discussion 3.1 Characterizations on Foaming Solution The formulation of surfactant AOS and ED-DM NP showed good compatibility in both 1 g/L NaCl and HSW without aggregation or precipitation. The hydrophilic ED ligands provided additional steric repulsion under ionic strength to achieve colloidal stability even in concentrated brine. The interactions between AOS and ED-DM NP are minimized since both amphiphiles are negatively charged [22], shown as the zeta potential results in Table 1. As the salinity increases, higher ionic strength in aqueous phase screens the negative charge on both AOS and ED-DM NP, resulting in more neutralized zeta potential in HSW compared to in 1 g/L NaCl. Table 1. Surface tension and zeta potential of surfactants and NPs in different brines Foam formulation
Brine
Surface tension (mN/m)
Zeta potential (mV)
0.1% AOS 0.5% NPs
HSW
29.343 ± 0.025
−5.92
1 g/L NaCl
34.425 ± 0.023
−19.00
1% NPs
HSW
47.313 ± 0.042
−0.53
1 g/L NaCl
52.348 + 0.030
−5.12
0.1% AOS
HSW
28.945 ± 0.024
−6.37
Surface tension measurements indicated strong surface activity of the ED-DM NP, also shown in Table 1. Without presence of surfactant, the ED-DM NP could reduce the surface tension from 72 mN/m to 52 mN/m in 1 g/L NaCl, and from 74 mN/m to 47 mN/m in HSW. The reduced surface tension suggested strong adsorption of NPs at the air-water interface. Lower surface tension with higher salinity may be explained by the screened electrostatic repulsion between NPs under stronger ionic strength, resulting in closer packing of NPs at the interface. The strong adsorption of the ED-DM NP at the interface was also proved by high surface elasticity and dilational modulus in previous studies [14]. The addition of AOS further reduce the surface tension to Surfactant-2 in solid state. The starting decomposition of the surfactants can be attributed to the decomposition of the head groups, the –COONa, -SO4 Na and -SO3 Na respectively. This also indicate the thermal stability of head groups is -COONa > -SO3 Na > -SO4 Na. The stability of these surfactants in solutions will be discussed in the following part. 120 Surfactant-1
Surfactant-2
Surfactant-3
100
Mass / %
80 60 40 20 0 0
100
200
300 Temperature/ °C
400
500
Fig. 1. TGA curves of Surfactant-1, Surfactant-2 and Surfactant-3.
600
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3.2 Surface Property The long-term stability tests of all the three surfactants were conducted with or without oxygen dissolved in the solutions. For convenience, the samples without oxygen will be mentioned as the surfactant name and the samples with oxygen will be marked as under oxygen. Figure 2 and Fig. 3 present the IFT and SF of three surfactants in 1 M NaCl after aging from 0 to 150 days respectively. The IFT and SF of Surfactant-1 after 34 days were not determined as the solutions were turbid, indicating severe compatibility problem and the formation of precipitations (Fig. 4). The IFT of Surfactant-2 in 1 M NaCl slightly decreased in the first 22 days and started to increase after 34 days. After 50 days aging, the IFT was almost one magnitude higher than the original solution. In the condition of Surfactant-3, the IFT is very stable in 150 days aging. LAS solution was stable in a month. The surface tension of three surfactants were not sensitive as IFT performance, which did not increase obviously in the tests. But there existed a bigger fluctuation of Surfactant-2 than Surfactant-3. These results demonstrate Surfactant-3 should be more stable than Surfactant-2. Besides, the compatibility problem of Surfactant-1 must be considered in surfactant development. 100
Interfacial tension (mN/m)
Surfactant-1
Surfactant-2
Surfactant-3
10
1
0.1 0
20
40
60
80
100
120
140
160
Aged days
Fig. 2. Interfacial tension of Surfactant-1 (orange), Surfactant-2 (blue), Surfactant-3 (grey) with crude oil in 1 M NaCl after aging from 0 to 150 days at 95 °C.
Figure 5 presents the interfacial tension and surface tension of surfactant-2 in 1 M NaCl under oxygen. Even though the surface tension did not change a lot, the IFT clearly increased after 22 days and the value at 34 days was higher than the original solution. After 50 days aging, the solutions were turbid and the IFT and surface tension data were not recorded. The experiments demonstrate that oxygen in the solution accelerated the increase of IFT and the decomposition of surfactant-2. Figure 6 of HPLC of surfactant-2 shows the active component in both Surfactant-2 without oxygen and under oxygen after
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Surface tension (mN/m)
100
10
Surfactant-1
Surfactant-2
Surfactant-3
1 0
20
40
60
80
100
120
140
160
Aged days
Fig. 3. Surface tension of Surfactant-1 (orange), Surfactant-2 (blue), Surfactant-3 (grey) in 1 M NaCl after aging from 0 to 150 days at 95 °C.
Fig. 4. The appearances of fresh prepared surfactant-1 and the solution after aging 34 days at 90ºC.
36 days aging decreased. Most of surfactant-2 molecules with dissolved oxygen were decomposed. Figure 7 presents the interfacial tension and surface tension of surfactant-3 in 1 M NaCl under oxygen after aging at high temperature. The surface tension and the IFT were identical to those of the original solution, indicating the stability under oxygen. This demonstrates that oxygen in the solution did not have a great impact of surfactant-3 in 1 M NaCl in 70 days. But after 70 days, precipitations appeared in the aged solutions. The HPLC spectra in Fig. 8 of Surfactant-3 shows the active component under oxygen after 34 days aging did not decrease. The results confirm that surfactant-3 is more stable than surfactant-2 even in the presence of oxygen.
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Surface Property (mN/m)
100
10
1 Surface Tension Interfacial tension
0.1 0
10
20
30
40
50
60
Aged Days Fig. 5. Interfacial tension and surface tension of surfactant-2 in 1 M NaCl under oxygen at different aged days at 95 °C.
1200000
Surfactant-2 in 1M NaCl Surfactant-2 Day 36 Surfactant-2 Day 36 under oxygen
Intensity (UI)
1000000 800000 600000 400000 200000 0 0
5
10
RetenƟon Ɵme (mins)
15
20
Fig. 6. HPLC spectra of surfactant-2 in 1 M NaCl, including freshly prepared solution (blue line), after aging 36 days without oxygen (orange line) and under oxygen (grey line).
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100
Surface Property (mN/m)
Surface tension
Interfacial tension
10
1
0.1 0
10
20
30
40
50
60
70
80
Aged Days Fig. 7. Interfacial tension and surface tension of surfactant-3 in 1 M NaCl under oxygen at different aged days at 95 °C. Surfactant-3 in 1M NaCl Surfactant-3 Day 34 under oxygen
1000000
Intensity (UI)
800000 600000 400000 200000 0 0
5
10
15
20
RetenƟon Ɵme (mins)
Fig. 8. HPLC spectra of Surfactant-3 in 1 M NaCl, including original solution (black line) and after aging 36 days under oxygen (green line).
4 Conclusions 1) Surfactant-3 with sulfonate group is the most stable surfactant among the three anionic surfactants. The surface property did not change in the 150 days aging at 95 °C when oxygen is excluded.
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2) Though the Surfactant-1 with carboxyl group have the most stable chemical structure, the compatibility of the solution could be a problem in application. 3) The dissolved oxygen in the solution will accelerate the decomposition of anionic surfactants in the long-term aging at high temperature high salinity condition. The sulfonate surfactant is more tolerant to oxidation than the sulfate surfactant. 4) The work demonstrates the sulfonate-type anionic surfactant presents significant long-term stability in the application of chemical injection at elevated temperature, which giving a hint for surfactant selection in HTHS reservoirs.
References 1. Hirasaki, G.J., Miller, C.A., Puerto, M.: Recent advances in surfactant EOR. In: SPE Annual Technical Conference and Exhibition SPE-115386-MS. Denver, Colorado, USA (2008) 2. Shen, P., Wang, J., Yuan, S., Zhong, T., Jia, X.: Study of enhanced-oil-recovery mechanism of alkali/surfactant/polymer flooding in porous media from experiments. In: SPE EOR Conference at Oil & Gas West Asia SPE-126128-MS. Muscat, Oman (2008) 3. Gao, P., Towler, B., Li, Y., Zhang, X.: Integrated evaluation of surfactant-polymer floods. In: SPE EOR Conference at Oil & Gas West Asia SPE-129590-MS. Muscat, Oman (2010) 4. Han, M., Alsofi, A., Fuseni, A., Zhou, X., Hasan, S.: Development of chemical EOR formulations for a high temperature and high salinity carbonate reservoir. In: International Petroleum Technology Conference IPTC-17084-MS. Beijing, China (2013) 5. Alsofi, A.M., Liu, J., Han, M.: Numerical simulation of surfactant–polymer coreflooding experiments for carbonates. J. Petrol. Sci. Eng. 111, 184–196 (2013) 6. Sheng, J.J.: A comprehensive review of alkaline–surfactant–polymer (ASP) flooding. AsiaPac. J. Chem. Eng. 9, 471–489 (2014) 7. Chatzis, I., Morrow, N.R.: Correlation of capillary number relationship for sandstone. SPE J. 24, 555–562 (1984) 8. Fuseni, A., Han, M., Al-Mobith, A.: Phase behavior and interfacial tension properties of an amphoteric surfactant for EOR application. In: SPE Saudi Arabia Section Technical Symposium and Exhibition SPE-168104-MS. Al-Khobar, Saudi Arabia (2013) 9. Kamal, M.S., Hussein, I.A., Sultan, A.S.: Review on surfactant flooding: phase behavior, retention, IFT, and field applications. Energy Fuels 31, 7701–7720 (2017) 10. Handy, L.L., Amaefule, J.O., Ziegler, V.M., Ershaghi, I.: Thermal stability of surfactants for reservoir application. Soc. Petrol. Eng. J. 22(05), 722–730 (1982). https://doi.org/10.2118/ 7867-PA 11. Zielgler, V.M.: Laboratory investigation of high temperature surfactant flooding. SPE Res. Eng. 3(02), 586–596 (1988) 12. Kamal, M.S., Hussain, S.M.S., Fogang, L.T.: Role of ionic headgroups on the thermal, rheological, and foaming properties of novel betaine-based polyoxyethylene zwitterionic surfactants for enhanced oil recovery. Processes 7, 908 (2019) 13. Adkins, S., Arachchilage, G.P., Solairaj, S., Lu, J., Weerasooriya, U., Pope, G.: Development of thermally and chemically stable large hydrophobe alkoxy carboxylate surfactants. In: SPE Improved Oil Recovery Symposium SPE-154256-MS. Tulsa, Oklahoma, USA (2012) 14. Kamal, M.S., Sultan, A.S., Hussein, I.A.: Screening of amphoteric and anionic surfactants for cEOR applications using a novel approach. Colloids Surf., A 476, 17–23 (2015) 15. Neign, C., Ali, S., Xie, Q.: Most common surfactants employed in chemical enhanced oil recovery. Petroleum 3(2), 197–211 (2017)
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16. Pal, N., Saxena, N., Divya Laxmi, K.V., Mandal, A.: Interfacial behavior, wettability alteration and emulsification characteristics of a novel surfactant: implications for enhanced oil recovery. Chem. Eng. Sci. 187, 200–212 (2018) 17. Guo, J.-X., et al.: Temperature-resistant and salt-tolerant mixed surfactant system for EOR in the Tahe Oilfield. Pet. Sci. 18(2), 667–678 (2021). https://doi.org/10.1007/s12182-020-005 27-w 18. Hocine, S., Cuenca, A., Magnan, A. Tay, A., Moreau, P.: An extensive study of the thermal stability of anionic chemical EOR surfactants – part 1 stability in aqueous solutions. In: International Petroleum Technology Conference IPTC-18974-MS. Bangkok, Thailand (2016) 19. Hocine, S., Pousset, B., Courtaud, T., Degre, G.: Long term thermal stability of chemical EOR surfactants. In: SPE EOR Conference at Oil and Gas West Asia SPE-190361-MS. Muscat, Oman (2018) 20. Nguyen, H.M., Phan, C.M., Sen, T.: Degradation of sodium dodecyl sulfate by photoelectrochemical and electrochemical processes. Chem. Eng. J. 287(1), 633–639 (2016)
Study on Feasibility of Surface Concentric Pipe Type Zonal Water Injection Technology in Middle East Xue-qin Huang(B) , Zheng-xue Du, Gui Hu, Zhen Nie, and Chun-peng Wang Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China {huangxueqin,duzhengx,hugui,niezhen,wangcp69}@petrochina.com.cn
Abstract. Oilfield in Middle East has entered the middle and late stage of development. It is urgent to carry out layered water injection to supplement formation energy and improve development effect. The development status of zonal water injection technology at home and abroad is analyzed. According to the characteristics of large water injection rate, high risk of corrosion and scaling, few zonal layers and unable to long-term field measurement and adjustment of zonal water injection in Middle East, surface concentric pipe type zonal water injection technology is proposed. The most outstanding feature of this technology is to move the complex downhole measurement and adjustment device to the ground. It realizes the real-time measurement and adjustment of water injection through the remote monitoring system, without going down the well with steel wire or cable. Taking two layers water injection in 7” production casing in H oilfield of Middle East as an example, through nodal analysis and research, water injection string composition of 4” outer tubing and 2–3/8” inner tubing is designed. It is predicted that the single-layer daily water injection will reach 250 m3 /d–850 m3 /d, the single well daily water injection will reach 500 m3 /d–1600 m3 /d, and the allowable running depth of tubing is 3792 m. The study results show that surface concentric pipe type zonal water injection technology can meet the requirement of zonal water injection development of oilfield in Middle East. Keywords: Middle East · Surface zonal water injection · Real-time measurement and adjustment · Nodal analysis · Water injection rate Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 308–320, 2023. https://doi.org/10.1007/978-981-99-2649-7_29
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1 Introduction The Middle East is dominated by marine carbonate reservoirs [1], which are gradually changing from depletion development to water injection development. Due to the strong vertical and horizontal heterogeneity of carbonate reservoirs in the Middle East, there are high permeability belts [2–5]. When commingled water injection is adopted, the injected water preferentially flows along the high permeability layer, resulting in low water injection sweep efficiency and poor production effect. Therefore, zonal water injection is urgent demand. Carbonate reservoirs in the Middle East have the characteristics of generally developing stable physical property interlayers, which can play a barrier in zonal water injection development [6], and have a good foundation for zonal water injection. Zonal water injection in carbonate reservoirs in the Middle East is quite different from that in China: 1) First, the average oil layer thickness of super thick carbonate reservoir is 120 m [7]. Due to the large thickness of reservoir, in order to ensure the water injection swept volume, the water injection rate of a single well needs to be kept high. The water injection rate of single well is 500 m3 to 1600 m3 , while the single well water injection rate of China is generally less than 160 m3 . 2) Second, the salinity of formation water is generally high, generally in the range of 150 g/L to 200 g/L, while the injected water is mostly the formation water after simple treatment, so the risk of corrosion and scaling of water injection string is high. The salinity of formation water of H oilfield in Middle East is shown in Table 1. 3) Third, the security situation in the Middle East is severe. Workers cannot frequently go to the site to measure and adjust the water injection rate. It is required that the zonal water injection system can realize remote automatic monitoring of water injection parameters and automatic control of water injection rate. It also requires long service life of water injection string. 4) Finally, the number of layers of zonal water injection is mainly 2 or 3. Most water injection wells are highly deviated wells with an average depth of 3000 m. Zonal water injection technology should have good adaptability to water injection wells with large deviation angle.
2 Optimization of Zonal Water Injection in Middle East 2.1 Application Status of Zonal Water Injection Technology in Middle East At present, water injection in the Middle East is dominated by commingled water injection. However, due to the strong heterogeneity of the reservoir, the existence of high permeability zones, water injection development is facing great challenges [8, 9]. The injected water flows preferentially along the reservoir with good permeability, resulting in low injection water swept efficiency, poor water drive development effect, rapid water cut rise and other problems. In May 2016, the pilot test of zonal water injection was carried out in H oilfield, Iraq. The movable concentric zonal water injection technology
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Formation
unit
Formation 1
Formation 2
Formation 3
Formation 4
type
CaCl2
CaCl2
CaCl2
CaCl2
pH
7.1
5.95
6.9
6.3
Total Salinity
ppm
202795
166840
166661
Na+
mg/l
67257
60369
60015
Ca2+
mg/l
9200
8000
8681
Cl−
mg/l
129575
114488
107098
SO4 2− HCO3 −
mg/l
320
360
874
mg/l
427
451
7263
74565
is adopted. The number of zonal injection layers is two, and the daily water injection rate is 1670 m3 /d. Two layers of water regulators are installed on the same axis, and each water regulator has several liquid outlets. Use the steel wire to lower and fish the water regulator and replace the water nozzle on the surface without tripping the pipe string. In July 2018, the downhole water regulator was pulled out and it was found that the outer wall of the water regulator was seriously worn. The analysis shows that the water injection rate is large and the salinity of the injected water is high. The liquid outlet of the water regulator is not aligned with the liquid outlet of the working cylinder, the opening of the effective liquid outlet of the water regulator is small, and the outer wall of the water distributor core is sprayed by high-pressure fluid, resulting in serious wear. The zonal water injection process has a large workload of measurement and commissioning, and has high requirements for personnel and equipment. When testing the flow rate in layers, the layers interfere with each other, the accuracy of test data is low, and the zonal pressure test cannot be carried out. It can be seen that the application of movable concentric layered water injection technology in H oilfield has poor adaptability. Zonal water injection in the Middle East lacks mature experience and is still in the exploration stage. It is necessary to study zonal water injection technology that can adapt to the characteristics of reservoirs in the Middle East as soon as possible. 2.2 Development of Zonal Water Injection in Middle East In the early 1960s, the fixed zonal layer water injection technology was successfully developed and applied, and the quantitative water injection in multi-layer was realized for the first time [10]. The nozzle of water distributor is fixed, and the nozzle size is selected according to the water distribution rate. The nozzle of the fixed water distributor can not be adjusted in the well, so when adjusting the water injection rate of the interval, it is necessary to pull out the water injection string and replace the water nozzle of the water distributor on the ground, which results in heavy workload. This technology has been widely used in Daqing Oilfield. With the oilfield development entering the stage of high water cut, the contradiction between layers is becoming more and more serious. The fixed zonal water injection
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technology can not meet the needs of oilfield water injection development. In the 1980s, the steel wire fishing zonal water injection technology was developed, which adopted the steel wire fishing water distribution plug or adjustment of water distribution nozzle opening in downhole. Five kinds of process strings are formed, including movable zonal water injection, eccentric zonal water injection, bridge eccentric zonal water injection, concentric integrated zonal water injection and bridge concentric zonal water injection [11, 12]. Because the bridge eccentric zonal water injection technology is not limited by the number of layers and can avoid interference between layers during the test, it was most widely used at that time. In the 1990s, in order to improve the accuracy and the efficiency of testing, cable testing zonal water injection technology was developed. Its core is to replace steel wire with steel pipe cable to carry downhole electric measuring and adjusting instrument to connect with the plug of eccentric water distributor. Automatic flow rate adjustment was realized through electric drive mechanism, without repeatedly putting and fishing the plug. “Bridge eccentric + cable testing and adjustment” zonal water injection technology has greatly improved the efficiency of test and adjustment, and has become the main zonal water injection technology of PetroChina water injection wells [13]. With the deepening of oilfield development, water injection development is faced with the problems of complex relationship between injection and production, uneven production of oil layer, etc. Therefore, the zonal water injection technology is developing to the direction of remote real-time monitoring and flow rate automatic control. In recent years, the fourth generation of zonal water injection technology has been developed, which is represented by cable control zonal water injection, digital wave code communication zonal water injection and surface zonal water injection [14–18]. The core tool of cable control type and digital wave code communication zonal water injection technology is downhole integrated water regulator. The integrated water distributor and the surface control system realize two-way communication through cable or fluid, so as to complete the transmission of surface and downhole water injection data and the control of downhole zonal flow rate [19]. Because the downhole water distributor is integrated with motor, flowmeter and pressure gauge, etc., it has high failure rate, no-high temperature resistance and service life of less than 3 years. In contrast, surface concentric pipe zonal water injection moves the testing technology from the downhole to the surface, there is no water distributor in the downhole, and the surface solenoid valve controls the flow rate independently, which greatly improves the reliability and service life. 2.3 Optimization of Zonal Water Injection in Middle East The movable concentric layered water injection technology used in H oilfield in Iraq belongs to steel wire fishing zonal water injection technology. According to the major requirements and challenges faced by zonal water injection in Middle East, such as large daily water injection rate of a single well, high risk of corrosion and scaling, large well deviation and complex and severe safety situation, by comprehensively comparing the characteristics and investment and operation cost of each zonal water injection technology, surface concentric pipe zonal water injection technology is selected as the
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zonal water injection technology in Middle East. The technical characteristics of surface concentric pipe zonal water technology are as follows: 1) It’s suitable for large water injection rate. As long as the flow resistance of water injection tubing is not too large and there is a certain pressure when the water can be injected to the water injection interval, a certain water injection pressure difference can meet the water injection requirements. The water injection rate of single well can be more than 1600 m3 /d. 2) The string can avoid the risk of well sticking and has high safety and reliability. The drillable bridge plug is made of drillable composite material. In case of failure, minor overhaul and can be used to sweeping the can be used to avoid the risk of string sticking and ensure the smoothness of wellbore. 3) It can realize remote surface intelligent control. The surface water injection wellhead is equipped with electromagnetic flowmeter, pressure sensor, electric water control valve and wellhead automatic control module, etc. Remote real-time monitoring and intelligent control are realized through wellhead data transmission unit and digital platform.
3 Principle and Tools of Surface Concentric Pipe Zonal Water Injection Technology 3.1 Structure and Principle The surface concentric pipe zonal water injection process is composed of special water injection wellhead, remote monitoring system, drillable bridge plug, sealing cannula and tubing of different specifications [20, 21]. Taking the two-section zonal water injection as an example, the system composition is shown in Fig. 1. First, the drillable bridge plug is set to the designed position with the bridge plug setting tool, and two or three layers of concentric tubing are run into the same wellbore. Each layer of tubing is connected with the sealing cannula to form an independent water injection channel with the drillable bridge plug plugging seal. Water injection channel does not affect each other. The tubing is suspended through the special injection well on the ground. The special water injection wellhead is equipped with electromagnetic flowmeter and solenoid valve. By using remote control technology and ground controller, the remote real-time monitoring and flow control of pressure and flow are realized. 3.2 Matching Tools Drillable Bridge Plug The drillable bridge plug is used as a downhole interval packer. The main parts of the bridge plug are made of composite materials, which are drillable, as shown in Fig. 2. In case of failure, minor overhaul and can be used to sweeping the drillable bridge plug. The drillable bridge plug and the tubing are inserted and sealed through the sealing cannula. When inspecting the pipe, only the tubing and the sealing cannula need to be
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Fig. 1. Composition of two-section surface concentric pipe zonal water injection system
pulled out. The drillable bridge plug can be reused. The technical parameters of drillable bridge plug are designed according to the casing size. Taking 7” casing and two-section zonal water injection as an example, the technical parameters of drillable bridge plug are shown in Table 2. Table 2. Technical parameters of drillable bridge plug Drillable bridge plug
Outer diameter (mm)
Inner diameter (mm)
Setting pressure (MPa)
Working pressure (MPa)
Working temperature (°C)
First level
147.32
90
15
35
−30–120
Second level
147.32
60
15
35
−30–120
Sealing Cannula The sealing cannula is a sealing element between the drillable bridge plug and the tubing. The sealing ring is installed on the outer surface of the sealing cannula. The bridge plug and the sealing cannula realize the sealing of the primary pump with strong sealing reliability. In order to ensure success of one-time insertion in deep wells and highly deviated wells, a guide steel plate is added to the upper part of the drillable bridge plug, and a suitable inclination angle is designed to guide the sealing cannula to insert the drillable bridge plug smoothly. The indoor test results show that when the pressure is
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35.5 MPa, the pressure will not drop after 10 min. Taking 7” casing and two-section zonal water injection as an example. Wellhead Control System The wellhead control system adopts the modular design and has the following functions: first, remote real-time monitoring and control of water injection rate, with data storage, export and other functions. Second, the pressure water absorption indicator curve behind the nozzle is generated to reflect the real water absorption capacity of the reservoir. Finally, the automatic alarm function of drillable bridge plug failure ensures the effectiveness of water injection. Main Technical Parameters
(1) (2) (3) (4) (5)
Resistance to interlayer pressure difference: 35 MPa; Temperature resistance: ≤ 120 °C; Suitable for well conditions: no deformation, damage and channeling of casing; Suitable for casing: 5 1/2”or 7” casing; Suitable well depth: < 3500 m.
Field Application As of July 2020, surface concentric pipe zonal water injection technology has been applied in more than 100 wells in Chinese oilfields. On December 18, 2015, it was tested in well Yi + 45-2-3 with a depth of 2458 m. The three-section surface zonal water injection technology with drillable bridge plug was adopted, and the injection rate of well was 35 m3/d. The field test results show that the bridge plug setting and the tubing insertion of each layer are successful at one time, and the water distribution string of each layer is qualified. The water test and deployment time is only 0.5 d. The test and commissioning efficiency is high. The maximum interlaminar pressure difference is 19 MPa, and the string seal is reliable.
4 Adaptability Analysis of Surface Concentric Pipe Zonal Water Injection Technology in Middle East 4.1 Checking the Running Depth of Tubing Taking 7” casing and two-section zonal water injection as an example, 4” thickened tubing is selected for outer tubing and 2 3/8” integral joint tubing is selected for inner tubing. Both inner and outer tubing are sprayed with nano coating, which has excellent anti-corrosion performance and economy. When the safety factor is 1.8, the allowable running depth of outer tubing is 3792 m and that of inner tubing is 3836 m. The technical parameters and running depth check of tubing are shown in Table 3. The average well depth in the Middle East is about 3000 m, and the running depth of tubing meets the requirements.
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Table 3. Check of tubing running depth Specifications
Wall thickness (mm)
Steel grade
Average weight (kg/m)
Tensile strength (kN)
Allowable depth(m) n = 1.8
2 3/8 TBG integral joint
4.83
N-80
6.87
473
3836
4 UPTBG
6.65
N-80
16.37
1095
3792
4.2 Adaptability Analysis of Water Injection Rate Taking 7” casing and two-section zonal water injection as an example, the flow resistance of tubing water injection is analyzed. Resistance Along the Way For inner tubing, the average velocity of fluid in the tubing is as follow: u1 =
4Q πd1 2
(1)
For the annulus of outer and inner tubing, the average velocity of annulus fluid is as follow: u2 =
4Q π d2 2 − d1 2
(2)
ud υ
(3)
Reynolds number is as follow: Re =
When the water flow rate is 79.5 m3 /d, the fluid Reynolds number is more than 4000. Therefore, the flow state of water is turbulent. The discrimination and calculation formula of resistance coefficient λ is showed in Table 4. Table 4. Discrimination and calculation formula of resistance coefficient λ Flow state
Resistance zone
Discriminant formula
Calculation formula of λ
Turbulence
Smooth zone
8 d 7 4000 < Re < 26.98
λ = 0.3164 0.25
8 d 7 < R < 191.2 √ d 26.98 λ e
68 0.25 λ = 0.11 d + Re
√ d Re > 191.2 λ
0.25 λ = 0.11 d
Turbulent transition zone Rough zone
Re
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Resistance along the way is as follow: hf = λ
l ρu2 d 2
(4)
Q——water injection rate, m3 /s; d1 , d2 ——inner diameter of inner tubing and outer tubing respectively, m; υ——kinematic viscosity of fluid, m2 /s; ——the equivalent absolute roughness of fluid kinematic viscosity is 0.04 mm for coated tubing; λ——resistance coefficient along the way, dimensionless; l——tubing length, m; u——average fluid velocity, m/s; hf ——resistance along the way, Pa; ρ——fluid density is 1050 kg/m3 . Local Resistance The local resistance is mainly caused by the fluid passing through the tubing coupling, the annulus between the sealing cannula and the tubing, etc. The local resistance loss coefficient of the sudden increase of cross section is as follows: 2 A2 ζ = −1 (5) A1 The local resistance coefficient of the sudden reduction of cross section is as follows: A3 ζ = 0.5 1 − (6) A4 Local resistance is as follows: hw = ζ
ρu2 2
(7)
A1 ——area of small cross section, m2 ; A2 ——area of large cross section, m2 ; ζ——local resistance coefficient, dimensionless; u——average fluid velocity, m/s; hw ——local resistance, Pa. Total Flow Resistance The total flow resistance of the fluid in the tubing is the sum of the resistance along the tubing and the local resistance. h = hf + hw
(8)
When calculating the flow resistance, the length of tubing should be less than the allowable running depth 3500 m. According to the above calculation formula, when the
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single-layer water injection is 80 m3 /d to 1000 m3 /d, the fluid flow resistance of outer and inner tubing annulus and inner tubing are shown in Fig. 2. With the increase of water injection rate, the flow resistance of fluid increases. At the same water injection rate, the flow resistance of inner tubing is greater than that of outer tubing and inner tubing annulus. Therefore, the size of the inner tubing should not be too small. Under the condition of ensuring a certain tensile strength, the tubing with small wall thickness should be selected to reduce the friction of the inner water injection string.
Fig. 2. Fluid flow resistance of tubing
Water Injection Calculation Example The water injection rate is related to formation pressure, formation water absorption index, wellhead rated pressure and water injection string friction. The relationship between the required water injection differential pressure and water absorption index under different daily water injection is shown in Fig. 3. It can be seen that under the same water injection rate, the required water injection pressure difference decreases with the increase of water absorption index. The water injection rate is judged by back calculation of wellhead pressure, which should be lower than the wellhead pressure of field water injection pipeline. Wellhead pressure is back calculated as follows. Pw = Pf + P + Pstart + h − Pliquid
(9)
Water injection pressure difference is as follows. P =
Qinjecton PI
Pw ——wellhead pressure, psi; Pf ——formation pressure, psi; P——pressure difference for water injection, psi; Pstart ——starting pressure difference for water injection, psi; h——fluid flow resistance, psi;
(10)
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Pliquid ——injection water column pressure, psi; Qinjecton ——daily water injection rate, bbl/d; PI ——water absorption index, bbl/d/psi. Taking H oilfield in Iraq as an example, the formation pressure is 18.2 MPa– 26.8 MPa, the water absorption index is 32.1 m3 /d/MP–179.2 m3 /d/MPa, and the rated wellhead pressure of the oil field is 3.45 MPa. Therefore, it is predicted that the singlelayer water injection volume will reach 254 m3 /d–859 m3 /d, and the daily water injection volume of single well will reach 509 m3 /d–1 654 m3 /d.
water injection differential pressure, MPa
40
159 m³/d 318 m³/d 477 m³/d 636 m³/d 795 m³/d
35 30 25 20 15 10 5 0 23
46
69
92 115 138 161 water absorption index, m³/d/MPa
184
208
231
Fig. 3. Water injection pressure difference and water absorption index under different daily water injection rate
5 Conclusion The Middle East oilfields has entered the stage of water injection development. There is an urgent demand for zonal water injection technology. Based on the above analysis, the conclusions are as follows: (1) Zonal water injection in Middle East carbonate reservoirs is characterized by high water injection rate, high risk of corrosion and scaling, and no frequently going to the site to measure and adjust water injection rate. (2) In view of the challenges faced by zonal water injection in Middle East, the surface concentric pipe zonal water injection technology is proposed, and its adaptability is demonstrated. It can adapt to large water injection rate, avoid the risk of string sticking, and has high safety and reliability. It can realize remote real-time monitoring and intelligent control. The results show that the technology can meet the requirements of zonal water injection in Middle East. (3) In view of the large daily water injection rate of a single well in Middle East, the high salinity of the injected water, the large erosion of the water injection string,
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and the influence of corrosion and scaling factors, the stress of the water injection string is very complex. It is suggested that the pilot test of surface two-stage layered water injection should be carried out first in the early stage, and then the three-stage layered water injection test should be carried out when the conditions are mature.
References 1. Wang, Y., Song, X., Wang, G., et al.: Key technologies and practice for rapid and large-scale production increase in cooperation oil and gas fields of the middle east. Acta Petrolei Sinica 41(12), 1633–1642 (2020) 2. Al-Dabbas, M., Al-Jassim, J., Al-Jumaily, S.: Depositional environments and porosity distribution in regressive limestone reservoirs of the Mishrif formation, Southern Iraq. Arab. J. Geosci. 3(1), 67–78 (2010) 3. Liu, H., Tian, Z., Liu, B., et al.: Classification and prediction of giant thick strongly heterogeneous carbonate reservoirs in the middle east area: a case study of mid-cretaceous Mishrif formation in the W Oilfield of Iraq. Acta Petrolei Sinica 40(6), 677–691 (2019) 4. Zhao, L., et al.: Control factors of reservoir oil-bearing difference of cretaceous Mishrif formation in the H Oilfield, Iraq. Petrol. Explor. Dev. 46(2), 314–323 (2019). https://doi.org/ 10.1016/S1876-3804(19)60011-X 5. Sun, W., Qiao, Z., Shao, G., et al.: Sedimentary and reservoir architectures of MB1-2 submember of middle cretaceous Mishrif formation of Halfaya oilfield in Iraq. Pet. Explor. Dev. 47(4), 713–722 (2020) 6. Deng, Y., Guo, R., Tian, Z., et al.: Geologic features and genesis of the barriers and intercalations in carbonates: a case study of the cretaceous Mishrif formation, West Qurna oil field. Iraq. Petrol. Explor. Dev. 43(1), 136–144 (2016) 7. Song, X., Li, Y.: Optimum development options and strategies for water injection development of carbonate reservoirs in the Middle East. Pet. Explor. Dev. 45(4), 679–689 (2018) 8. Zhang, Q., Li, Y., Li, B., et al.: Identification methods and development strategy study of thief zone in reef-bank carbonate reservoirs: A case study of the Mishrif reservoir in Rumaila oilfield. Petroleum Geology and Recovery Efficiency 23(2), 1–6 (2016) 9. Chawathe, A., Dolan, J., Cullen, R., et al.: Innovative enhancement of an existing peripheral waterflood in a large carbonate reservoir in the Middle East. SPE 102419-MS (2006) 10. Gang, Z., Wei, X.: Review and outlook of separate layer water injection technology in Daqing. Special Oil & Gas Reservoirs 13(5), 4–9 (2006) 11. Yupu, W.A.N.G., Guangyun, W.A.N.G.: Injection Production Technology in High Water Cut Stage in Daqing Oilfield. Petroleum Industry Press, Beijing (2001) 12. Yang, L., Hu, G., Wang, M., et al.: Research and application of integrated bridge concentric seal test and adjustment technology. Well Logging Technology 43(5), 550–553 (2019) 13. Pei, X., Yang, Z., Ban, L., et al.: History and actuality of separate layer oil production technologies in Daqing oilfield. SPE 100859 (2006) 14. Liu, H., Pei, X., Jia, D., et al.: Connotation, application and prospect of the fourth-generation separated layer water injection technology. Pet. Explor. Dev. 44(4), 608–614 (2017) 15. Li, D.: Intelligent layered polymer injection technology with preset cable. China Petroleum Machinery 44(10), 93–96 (2016) 16. Zhang, Xu., Han, X., Lin, C.: Application of wireline intelligent separate-layer water injection technology in Huabei oilfield. China Petroleum Machinery 47(3), 87–92 (2019) 17. Wei, D., Li, Z., Wei, Y., et al.: Application of the remote measurement and adjustment intelligent injection technology in Tuha oilfield. Xinjiang Oil & Gas 13(2), 93–96 (2017)
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18. Yu, Y.: The Preset Cable Stratified Water Injection Testing Technology Research. Harbin University of Science and Technology, Harbin (2016) 19. Yao, B., Yang, L., Yu, J., et al.: Digital layered water injection based on wave code communication. China Petroleum Machinery 48(5), 71–77 (2020) 20. Ye, Q.: Research and application of surface intelligent zonal injection technology for special shaped pipe. Petroleum Knowledge 33(1), 56–58 (2018) 21. Jia, F., Yu, H., Wang, G.: Multistage tube cuttage grafting ground separate injection technology for drillable bridging plug of middle-deep wells. J. Changchun Univ. Technol. 40(1), 94–98 (2019)
Analysis and Measures Research on Inefficiency of Produced Water Treatment Station in Water Injection Development of Low Permeability Oilfield Zhen-peng Ma(B) , Zhi-gang Yang, Tian-qi Ma, and Hui Li Research Institute of Yanchang Petroleum (Group) CO. LTD., Xi’an, Shaanxi, China [email protected]
Abstract. The water treatment process of a produced water treatment station in an oilfield in northern Shaanxi is as follows: inclined plate deoiling sedimentation + dissolved air flotation + multi-media filtration + double filters material filtration. The water injection quality has not reached the standard for a long time in the past year. After sufficient investigation and water quality analysis of the produced water treatment station, it is found that due to the large increase in the amount of water and the change of water quality, the reagent system does not change with the change of water quantity and quality. In addition, the residence time in the inclined plate deoiling sedimentation tank is insufficient, resulting in that the effluent quality cannot meet the requirements of oil ≤ 5 mg/L, SS ≤ 3 mg/L, and the median particle size ≤ 2 µm. After laboratory test and field application, under the condition of not changing the original water treatment process, it is determined to use more efficient flocculant polysilicate aluminum ferric (PSFA) instead of the original flocculant polyaluminum chloride (PAC) in the station, which shortens the residence time, optimizes the types and dosage of iron remover, scale inhibitor, corrosion inhibitor and fungicide, and ensures that the effluent meets the water quality requirements in water injection development of low permeability oilfield. Keywords: Low-permeability Oil and Gas Fields · Water Injection Development · Produced Water Treatment · Inefficiency Analysis · Reagent Selection Copyright 2022, IPPTC Organizing Committee International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 321–332, 2023. https://doi.org/10.1007/978-981-99-2649-7_30
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1 Introduction Located in the Ordos Basin, Yanchang Oilfield is a rare “three-low” (low permeability, low pressure, and low abundance) oil and gas field in the world. It is difficult to develop. Water injection is one of the main development methods of oilfields, especially for the “three lows”. For the Jingbian Oilfield (low permeability, low pressure, and low abundance), the importance of water injection development is self-evident [1, 2]. After decades of development, the water content of the produced fluid in Yanchang Oilfield has been increasing year by year, and some oil areas have reached more than 90% [3, 4], and the amount of produced water to be treated has also increased, in addition to most produced water treatment stations (water injection stations). There are widespread problems such as aging equipment, frequent maintenance, backward technology, and poor dosing effectiveness. The above reasons together cause the water quality after treatment to fail to meet the standard, which affects the normal crude oil production. In addition, the injection of substandard water into the formation will produce undesirable effects. It will cause the suspended solids to block the pores of the reservoir, and the suspended particles will block the pore throats and cause the permeability to decrease. Blocking the gaps in the oil layer affects the water absorption capacity of the oil layer [5–7], which directly leads to a decrease in the water absorption index of the formation and an increase in water injection pressure. Finally, the block cannot be injected with water, water injection exploitation cannot be implemented, and the formation pressure cannot be replenished, which affects crude oil production. Eventually lead to a decline in oilfield recovery [8].
2 Analysis and Solutions of Low Efficiency of Produced Water Treatment Station 2.1 Analysis of Low Efficiency of Produced Water Treatment Station The water treatment station was built and put into operation in 2010. The water treatment process is: inclined plate oil removal settlement + dissolved air flotation + multi-media filtration + double filter material filtration. The output water of the extension group is treated with the original design capacity of 200 m3 /day. Due to the expansion of the development area and the increase of the water content of the produced liquid, the current treatment capacity is about 300 m3 /day, which has exceeded the original design capacity. The oil content and suspended matter content of the treated water exceed the standard seriously. After 1h of natural storage, the treated water sample is turbid; indicating that the treated water quality is unstable. The investigation found that the designed treatment capacity of the water treatment system was 30 m3 /h, and the hydraulic retention time was about 6.6 h. The designed hydraulic retention time of the inclined plate oil removal sedimentation tank was 2 h, and the treatment capacity was 100 m3 /h. The operation status is that the wastewater treatment capacity is about 300 m3 /day, the hydraulic retention time is still 6.6 h, the actual treatment capacity of the water treatment system is 45 m3 /h, and the hydraulic retention time of the inclined plate oil removal sedimentation tank is still 2 h, and the treatment capacity increases to 150 m3 /h.
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In the water treatment system, the inclined plate oil removal settling tank undertakes to remove about 80%–90% of the suspended solids and petroleum load in the incoming water [9]. Due to the increase of water volume, under the condition of constant residence time, suspended solids and petroleum do not have enough time to settle, resulting in a substantial increase in suspended solids and petroleum entering the back-end process, exceeding the design load of each treatment unit, and ultimately leading to the effluent after treatment is not up to standard. Secondly, the original dosing scheme is still used in the reagent system, and it is not dynamically adjusted with the change of water quality and quantity. The original dosing scheme has not adapted to the current water quality and quantity, and finally the water quality after treatment does not meet the first-level water injection quality standard of Yanchang Oilfield (suspended solids ≤ 3 mg/L, median particle size ≤ 2 µm, and oil content ≤ 2 mg/L). 2.2 Solutions of Low Efficiency of Produced Water Treatment Station Due to the limitation of field space and investment, the actual conditions do not allow the expansion of new water treatment systems, which can only be improved on the basis of existing water treatment systems. Based on the above problems and current situation, without changing the original water treatment process, the reagents system was optimized to reduce the residence time of sewage and improve the water treatment efficiency, so as to achieve the goal of reaching the effluent standard. Additive is an important part of oilfield wastewater treatment. Appropriate types, appropriate dosage and ratio are essential to ensure the effect of water treatment [10, 11]. Therefore, it is necessary to carry out a large number of experiments to screen and determine the types and dosage of flocculants, coagulant aids, fungicides, corrosion inhibitors, scale inhibitors and iron removers, so as to ensure the treatment effect and reduce the treatment cost [12].
3 Materials and Methods 3.1 Reagents and Instruments Reagents: FeSO4 ·7H2 O, HCl, NaOH, K2 Cr2 O7 , AgNO3 , Fe2 (SO4 )3 , KCl, analysis pure, Xi’an chemical reagent factory. Instruments: Spectrophotometer (7230G), Drum Dryer (101-1ES), Muffle Furnace (SX-12-16), Constant Temperature Water bath (DK-98-II), Biochemical Incubator (SPX-150), Constant Temperature Magnetic Stirrer (JB-1B), Electronic Balance (FA2004), etc. 3.2 Evaluation Method of Reagent Screening The basis and methods of reagent evaluation follow the following principles: if there are national standards or industry standards, they are carried out according to the standards stipulated by national standards or industry standards. If there is no national standard or industry standard, it will be tested according to the enterprise standard [13]. The specific reagent evaluation methods and standards are shown in Table 1 below.
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Reagent’s Name
Standards and Methods for the Detection
Flocculating Reagent Flocculant Evaluation Method SY/T 5796-1993 Technical Requirements of Flocculants for Conventional Oilfield Produced Water Treatment Q/SH 0357-2010 Coagulant Aid
Flocculant Evaluation Method SY/T 5796-1993 Technical Requirements of Flocculants for Conventional Oilfield Produced Water Treatment Q/SH 0357-2010
Corrosion Inhibitor
Technical specifications and evaluating methods of corrosion-inhibitors for oilfield produced water SY/T 5273-2000
Scale Inhibitor
Performance evaluation method of scale inhibitor for oilfield SY/T 5673-1993
Germicide
General technical conditions of fungicides for oilfield produced water treatment QSH10200688-2016
4 Results and Discussion 4.1 Water Quality Analysis From the overall analysis of water quality, the water from the treatment station belongs to CaCl2 type water quality. The saturation index (SI) of CaCO3 is -0.05, indicating that the water quality is basically stable. The results of water quality analysis are shown in Tables 2 and 3. Table 2. Results of water quality analysis of inlet and outlet water in treatment station Item
First Sampling
Second Sampling Third sampling
Average Concentration
Inlet Water
Outlet Water
Inlet Water
Outlet Water
Inlet Water
Outlet Water
Inlet Water
Outlet Water
Oil (mg/L)
135.16
15.61
145.36
14.74
132.58
12.74
137.67
14.38
SS (mg/L)
81.12
12.62
86.24
10.70
75.13
12.81
80.83
12.05
S2− (mg/L)
0.17
11.08
0.04
25.03
0.12
18.02
0.17
18.02
Total Iron (mg/L)
7.59
0.86
9.02
2.55
5.11
1.37
7.21
4.63
4.2 Flocculant Screening and Evaluation The self-owned flocculant in the station are PAC (produced from Texas Ruixing, industrial grade) and liquid organic coagulant aid PAM (produced from Xinfeng Chemical
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Table 3. Results of ion total analysis of outlet water in treatment station
Industry, industrial grade). The flocculants to be evaluated are polyferric chloride (PFC), polyferric sulfate (PFS) and polyaluminum ferric chloride (PAFC). Taking 200 mL station water in the beaker, dosing flocculant (0 mL, 20 mL, 40 mL, 60 mL and 80 mL) and stirring at 200 r/min, 25 °C for 1 min, then adding organic coagulant aid PAM 2 mL, stirring at 200 r/min, 25 °C for 1 min [9], standing for 30 min after taking photos, the station’s own flocculant experimental effect is shown in Fig. 1, the produced water treatment station to be screened HF-X03 flocculant experimental effect is shown in Fig. 2.
Fig. 1. Experimental results of self-owned flocculant in the station (Dosage of flocculant from left to right: 0 mg/L, 20 mg/L, 40 mg/L, 60 mg/L, 80 mg/L)
From the experimental results, it can be seen that after adding the flocculant + coagulant aids in the station, the flocs generated are small and easy to suspend in the water body, and all of them sink to the bottom of the cup for a long time. After adding the same dose of flocculant HF-X03 + coagulant aid, a large floc is produced in a short
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（Dosage of flocculant from left to right: 0 mg/L、20mg/L、40mg/L、60mg/L、80mg/L）
Fig. 2. Experimental effect of flocculant to be evaluated in the station (Dosage of flocculant from left to right: 0 mg/L, 20 mg/L, 40 mg/L, 60 mg/L, 80 mg/L)
time, and quickly sinks to the bottom of the cup. The water quality is much clearer than that of the station’s own flocculant treatment. The oil content and suspended solids in the water treated by the four reagents are detected respectively, as shown in Figs. 3 and 4: 100 98
OiL removal rate (%)
96 94 92 90 88
PAC PFC PFS PAFC
86 84 82 20
30
40
50
60
70
80
Dosage of flocculant (mg/L)
Fig. 3. Oil removal effect of four flocculant under different dosage
According to the test results, it can be found that PFC, PFS and PAFC showed better treatment effect in oil removal compared with the self-owned reagents in the station at the same dosage, and the oil content in the water after treatment was significantly reduced. In terms of SS removal, the treatment effect of self-owned reagents in the station is similar to that of PFC, which is manifested as slow subsidence of suspended flocs in water, and good treatment effect of PFS and PAFC [14]. The flocs generated after dosing of reagents are large and dense, with fast subsidence and clear water body. Considering the treatment effect and cost, PAFC was selected as experimental flocculant with dosage of 40 mg/L and organic coagulant aid of 2 mg/L. 4.3 Screening and Evaluation of Iron Removal Reagents The self-owned iron removal reagent is HK-4, light yellow liquid, pH≈9, and the manufacturer is Shaanxi Petrochemical Research and Design Institute. 200 mL produced
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90
SS removal rate (%)
80
70
60
50
PAC PFC PFS PAFC
40
30 20
30
40
50
60
70
80
Dosage of flocculant (mg/L)
Fig. 4. SS removal effect of four flocculant under different dosage
water was taken in four beakers, respectively. The iron removal doses were 0 mg/L, 50 mg/L, 100 mg/L and 150 mg/L, respectively, and stirred at 200 r/min for 1 min. Then the iron ion content in water was detected. The results are shown in Table 4. Table 4. Experimental results of iron removal reagent evaluation NO.
Name of Reagent
1
HK-4
Dosage (mg/L) 0
Fe3+/Fe2+ (mg/L) 0.40/0.60
Removal rate (%) -
2
50
1.00/0.00
0.0
3
150
1.00/0.00
0.0
4
100
0.90/0.00
10.0
According to the data in the table, all Fe2+ was oxidized to Fe3+ after adding iron remover, but the total iron did not precipitate much, so the removal effect of HK-4 on iron in produced water was not ideal. The removal effect of water purification reagent (flocculant + coagulant aid) on total iron in water was explored. The selected flocculant PAFC was combined with organic coagulant aid (2 mg/L) to investigate its iron removal performance [15]. The iron removal effect is shown in Fig. 5. It can be seen from Fig. 5 that PAFC has good flocculation and sedimentation removal effect on total iron in produced water, and it can achieve better removal effect when the dosage is 40 mg/L. Considering that HK-4 is an oxidizing iron removal reagent, it has certain corrosion to the equipment and pipeline, and the total iron content in the produced water is not high (average content 4.63 mg/L). The iron removal reagent can be stopped, and the flocculation of PAFC alone can achieve the effect of iron removal in water [16, 17].
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Total iron removal rate (%)
100
98
96
94
Total iron removal rate
92
90 20
30
40
50
60
70
80
Dosage of PAFC (mg/L)
Fig. 5. Iron removal effect of PAFC under different dosage
4.4 Screening and Evaluation of Scale Inhibitors Three scale inhibitors HF-G01, HF-G02 and HF-G03 were selected for evaluation in combination with the on-site proprietary reagents. Taking 100 mL water into the colorimetric tube, adding scale inhibitor, shaking and standing at the field temperature for 24 h, the scale inhibition rate was measured. The scale inhibition effect is shown in Fig. 6. 100 95
Anti-scaling rate(%)
90 85 80 75 70 65
self-owned HF-G01 HF-G02 HF-G03
60 55 50 20
30
40
50
60
70
Dosage of scale inhibotor (mg/L)
Fig. 6. Scale inhibition effect of different scale inhibitors
According to the experimental results, HF-G03 showed good scale inhibition effect under three doses. Considering the treatment cost and effect, the dosage of HF-X03 was determined to be 60 mg/L to achieve more than 85% of the scale inhibition effect, which was better than the scale inhibition effect of the station’s self-owned reagent [18]. 4.5 Screening and Evaluation of Corrosion Inhibitors Three corrosion inhibitors HF-H01, HF-H02 and HF-H03 were selected for evaluation. The reagent evaluation and screening experiments were carried out by comparing the
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three inhibitors screened in the laboratory. 250 mL water was taken into the conical flask, and the corrosion inhibitor was added in a dose-by-dose manner. After shaking, the corrosion inhibitor was put into the test piece and placed at the field temperature for 72 h [19]. The slow-release effect of different reagents and the corrosion rate under different conditions were shown in Figs. 7 and 8. 100
Release rate(%)
80
60
40
self-owned HF-H01 HF-H02 HF-H03
20
0 20
40
60
80
Dosage of corrosion inhibitors (mg/L)
Fig. 7. Corrosion inhibition rate of different inhibitors
0.20
Corrosion rate(%)
0.15
0.10
self-owned HF-H01 HF-H02 HF-H03
0.05
0.00 20
30
40
50
60
70
Dosage of corrosion inhibitors (mg/L)
Fig. 8. Corrosion rate under different corrosion inhibitors
The corrosion rate of water quality decreased after the addition of corrosion inhibitor. Under the premise of the same dosage, the corrosion rate of water quality decreased most significantly after the addition of HF-H01 corrosion inhibitor. The relative corrosion inhibition rate was higher, and the corrosion inhibition effect of the reagent was better, which was more suitable for the field water quality. HF-H01 corrosion inhibitor was selected and the dosage of the reagent was 60 mg/L.
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4.6 Screening and Evaluation of Fungicides The number of three kinds of bacteria in the water is 2.5 × 102 /mL, although the number of bacteria is not much, but has exceeded the water quality requirements; need to add fungicides to control. Reagent evaluation and screening experiments were carried out on the site and indoor screening of three fungicides. 100 mL water was taken, and the fungicide was added gradually. After shaking, the bacteria were placed in the field temperature for 40–60 min [20, 21]. The number of bacteria was determined by the dilution method (according to Recommendation standard and analysis method of water injection quality in clastic reservoir SY/T 5329-2012). The results of the evaluation and screening of fungicides in the combined station are shown in Table 5. Table 5. Evaluation and screening results of fungicides NO.
SRB (/mL)
TGB (/mL)
IB (/mL)
Water untreated
2.5 × 102
2.5 × 102
2.5 × 102
1
2.5 × 102
2.5 × 102
2.5 × 102
HF-J11
2.5 × 102
2.5 × 102
6.0 × 101
HF-J12
6.0 × 100
6.0 × 101
2.5 × 102
HF-J13
6.0 × 100
6.0 × 101
2.5 × 100
2.5 × 102
6.0 × 101
2.5 × 101
HF-J11
2.5 × 101
2.5 × 101
6.0 × 100
HF-J12
0.6 × 100
2.5 × 100
2.5 × 101
HF-J13
2.5 × 100
0.6 × 100
0.6 × 100
2.5 × 102
2.5 × 101
2.5 × 101
HF-J11
2.5 × 100
2.5 × 100
0.6 × 100
HF-J12
0
0
0.6 × 100
HF-J13
0
0
0
2
3
Name of Reagent Self-owned
Self-owned
Self-owned
Dosage(mg/L)
20
40
60
Water contains SRB, TGB and iron bacteria, and the number of three bacteria is similar. In order to ensure that the three bacteria were up to the standard, the four fungicides all had good effects but the dosage of fungicides used in the field was slightly larger, with the dosage of 40 mg/L, while the dosage of fungicides HF-J12 (quaternary ammonium salts) and HF-J13 (organic biguanidines) was 20 mg/L. Considering the resistance of bacteria, two or more fungicides can be used alternately. 4.7 Reagent Cost According to the screening results of this reagent, the cost of the adjusted reagent was calculated to be CNY 2.729/m3 , and compared with the current reagent cost; the reagent cost of the produced water treatment station was reduced by CNY 0.951/m3 . The reagent cost after adjustment is shown in Table 6.
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Table 6. Reagent cost after adjustment Name of Reagent
Flocculating reagent
Coagulant Aid
Germicide
Scale Inhibitor
Corrosion Inhibitor
Dosage (mg/L)
40
2
60
60
60
Price (CNY/t)
2300
38500
24500
10500
11500
Single Cost (CNY/m3 )
0.092
0.073
1.470
0.630
0.690
Reagent cost after screening (CNY/m3 )
2.729
Current reagent cost(CNY/m3 )
3.68
5 Conclusion (1) Due to the increase of water quantity in the produced water treatment station, the current residence time is not enough to completely settle the suspended solids and petroleum, and the suspended solids and petroleum entering the back-end process are greatly increased, exceeding the design load. At the same time, the reagent system is still used in the original scheme, resulting in the water quality after treatment not meeting the first-level water injection standard of the Yanchang oilfield ( suspended solids ≤ 3 mg/L, median particle size ≤ 2 µm, oil content ≤ 2 mg/L). (2) In view of the current situation, the new reagent scheme was studied without changing the original process, and the types and dosages of flocculants, coagulant aids, scale inhibitors, corrosion inhibitors and fungicides were screened and determined. According to the experiments, the location and concentration of the dosing reagents were screened out, including 40 mg/L of flocculant (PAFC), 2 mg/L of coagulant aids (PAM), 60 mg/L of scale inhibitors HF-X03), 60 mg/L of corrosion inhibitors (HF-H01) and 20 mg/L of fungicides (HF-J12/HF-J13). (3) After water quality improvement through reagents screening, the reagents’ cost of the station was significantly reduced, and the reagent cost could be reduced from CNY 3.68/m3 to CNY 2.72/m3 , with a decrease of CNY 0.96/m3 . The goal of cost reduction and efficiency increase was achieved while the water quality reached the standard.
Acknowledgments. The project is supported by Yanchang Petroleum Group Science and Technology Invest Plan (Number: ycsy2021ky-B-18).
References 1. Xi, J.Z., Liu, Y.W.: Technical improvement of sewage disposal and water quality enhancement in the 10th united station of Jingbian oilfield. Oil-Gas Field Surf. Eng. 35(03), 62–65 (2016)
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2. Shu-Bin, L.I., Jiang, P., Chen, H.X.: Progress on greening study of the agents for water treatment in oil field. Chemical Engineer (2004) 3. Jiang, H.Y., Li, Z.P., Zhong, T.X., et al.: Current situation and prospects of development technology for low permeability oil and gas fields in the world. Special Oil & Gas Reservoirs 16, 13–17 (2009) 4. Yu, Y.J., Kong, W.: Closed reformation of sewage treatment process at unite station of oilfield. Petrol. Eng. Constr. 42(06), 66–69 (2016) 5. Al-Kindi, S., Al-Bahry, S., Al-Wahaibi, Y., et al.: Partially hydrolyzed polyacrylamide: enhanced oil recovery applications, oil-field produced water pollution, and possible solutions. Environmental Monitoring and Assessment 194(12) (2022) 6. Zhong, C.: Selection and application of reagent for gas-field water treatment. Environ. Prot. Oil & Gas Fields (2005) 7. Wei, J.: The Making and Indoor Experiment on Compound Flocculate Reagent with Polyaluminum Chlorate and Partially Hydrolyzed Polyacrylamide. Environmental Protection of Oil & Gas Fields (2002) 8. Zong, M.Y., Sun, S.L.: Treatment screening and performance evaluation for Shinan oilfield produced water. Environ. Prot. Oil & Gas Fields 25(06), 29–32 (2015) 9. Shen, Z., Huang, Z.Y.: Compatibility of the main reagent in the oilfield water treatment. Oilfield Chemistry 34(04), 688–693 (2017) 10. Li, Y.H., Yu, Z.Q.: Study on compatibility of water treating corrosion and fouling inhibitors and bactericides. Corr. Protect. Petrochem. Ind. 27(03), 27–28 (2017) 11. Li, G.J., Yan, X.Z., Zhang, W.: A selection and application of the sewage treatment reagents of shallow and low permeability reservoir in the north of Shaanxi province. Northwest. Geol. 44(02), 141–148 (2011) 12. Chen, W., Diao, L.T., Yin, X.Q.: Performance evaluation of imidazoline corrosion/scale inhibitor NY-HGA in produced water of Weizhou-12–1 offshore oil field. Oilfield Chemistry (02), 126–129(2005) 13. Meng, X.H., Zhao, P., Han, Y.G.: Optimization and evaluation of Fe2+ remover for the water used for polymer solution in offshore oilfields. Oil-Gas Field Surf. Eng. 38(02), 7–11 (2019) 14. Peng, B.: Influencing factor analysis on the application result detection of the bactericide for oilfield water treatment. Oil-Gas Field Surf. Eng. 39(06), 48–51 (2020) 15. Zheng, S.Z., Teng, H.K., Wang, S.F.: The exploitation and application of water treatment technology in Liuhua oilfield. Strategic Study of CAE 13(05), 41–49 (2011) 16. Gao, W.L., Liu, Z., Tong, H.: Evaluation and screening of wastewater treatment reagents in a combined station in Yanchang oilfield. Liaoning Chemical Industry 49(05), 598–600 (2020) 17. Liu, J.J., Sun, M.Q.: Corrosion inhibitors for acidizing and waste water treatment in oil field. J. Chengde Petroleum College (2005) 18. Gao, W.F., Zhang, H.J., He, Z.: Selection of flocculants in oil field sewage treatment. Green Petroleum & Petrochemicals 2(03), 34–38 (2012) 19. Wang, Y.Y.: Measures to strengthen water injection in ultra-low permeability oilfield. Petrochemical Industry Technology 28(02), 130–131 (2021) 20. Lei, F.Q., Qin, F.L., Zhang, S.X.: Experimental study on dynamic scale formation trend of water injection in oilfields. Oil-Gas Field Surf. Eng. 39(10), 22–25 (2020) 21. Zhang, J., Qiao, W.L., Pei, H.H.: Study on corrosion factor of wastewater reinjection well in Shengli oilfield. Appl. Chem. Ind. 50(05), 1195–1198 (2021)
Laboratory Experimental Study of Air Foam Flooding in Low Permeability Reservoirs Jin-yuan Zhang1,2 , Jun-bin Chen1,2(B) , Xu Jiang1,2 , Chen Sun1,2 , Yuan-yuan Kou1,2 , and Wen-xin Liu1,2 1 Shaanxi Key Laboratory of Well Stability and Fluid and Rock Mechanics in Oil and Gas
Reservoirs, Xi’an Shiyou University, Xi’an 710065, Shaanxi, China [email protected] 2 College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, Shaanxi, China
Abstract. Petroleum is the country’s strategic energy and plays a pivotal role in the development of the national economy. With the in-depth development of oil fields, the problem of shortage of oil resources will become increasingly prominent. Water injection development has a better effect on maintaining formation pressure and oil displacement. Air foam flooding technology can not only form formation pressure, but also avoid water channeling and gas channeling problems, thereby improving oil recovery. In this paper, a foam scanner is used to evaluate the foaming performance of the foaming agent, and to screen the air foam system. According to the performance evaluation of the foaming agent, it is recommended that the on-site water injection station use 0.4~0.6%P + 0.05~0.075%W (the ratio of foam to stabilizer P/The W concentration is 8) Strengthen the foam system formula. The foaming agent’s temperature resistance, stability, salt resistance, adsorption resistance, oil resistance, emulsification and foam regeneration ability were evaluated. It has certain guiding significance for the mine field test. Keywords: Low Permeability · Air Flooding · Foam Flooding · Enhanced Oil Recovery
Copyright 2022, IPPTC Organizing Committee. This paper was prepared for presentation at the International Petroleum and Petrochemical Technology Conference 2022 held online between 12–13 October 2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of IPPTC Technical Committee is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 333–346, 2023. https://doi.org/10.1007/978-981-99-2649-7_31
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1 Introduction Air foam flooding technology is widely used at home and abroad, and the technology is relatively mature [1, 2]. With the further development of water injection in lowpermeability oilfields, water channeling and flooding have occurred [3]. Air foam flooding has the characteristics of wide gas source, low cost and no geographical restrictions. This technology can not only maintain the formation pressure, but also avoid the problems of water channeling and gas channeling, thereby improving the recovery factor [4, 5]. Air foam drive is a low-temperature oxidation reaction between oxygen in the air and crude oil, which produces carbon dioxide and nitrogen to expand the volume of crude oil and reduce its viscosity [6–8]. Foam is a dispersion system formed by insoluble or slightly soluble gas dispersed in a liquid. To form a stable foam, there must be more than two components in the liquid. The aqueous surfactant solution is a typical foam-prone system [9, 10]. Carrying out the screening of foaming agent system and the evaluation of influencing factors of foam performance have certain guiding significance for the application of low-permeability oil reservoirs.
2 Air Foam Agent Screening The experiment collected dozens of different types of foaming agents such as HA, HB, FYP~1, FYP~2, HN~F1, HN ~F2, YC, etc. The foaming agent solution was prepared Table 1. Preliminary screening of foaming agent Name of foaming agent
Foam volume/mL
Antifoam half-life/min
HA
120
7
HB
129
15
HC
132
22
HD
127
26
HE
128
21
FYP~1
128
26
FYP~2
124
19
FYP~3
126
28
FYP~4
132
26
FYP~5
126
31
FYP~6
120
28
HN~F1
128
22
HN~F2
120
21
HN~F3
123
26
SH6
96
35
YC
129
42
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with the ground water of M oil field, and the concentration was 0.4%. The foam scanner was used to evaluate the foaming performance of the foaming agent. The experiment temperature was 30 °C, and the gas medium used in the experiment was air. The experimental data is shown in Table 1. It can be seen from Table 1 that under the same concentration conditions, the foaming volume of YC foaming agent, FYP~4, and HC is the best; the defoaming half-life of YC foaming agent is the longest 42 min. Comprehensive evaluation shows that the stability of YC foaming agent is better than others Foaming agent. Therefore, YC foaming agent was selected for further evaluation. YC foaming agent is currently being tested in the Chang 6 reservoir in the Yezhumaozhen 653 well block of the Qili Village Oil Production Plant.
3 Evaluation and Preparation of Basic Performance of Foaming Agent 3.1 Foaming Ability and Stabilizing Ability of Foaming Agent It is characterized by evaluating the foaming volume and half-life of the foaming agent by a foam scanner. Prepare YC foaming agent solutions of different concentrations with clean water, and the experiment temperature is 30 °C. The experimental results are shown in Table 2. Table 2. Evaluation of the relationship between foaming agent concentration and foam performance Concentration/%
Foam volume/mL
Antifoam half-life/min
0.10
120
14
0.20
124
22
0.30
127
35
0.40
129
42
0.50
129
42
0.6
128
37
0.8
127
27
It can be seen from Table 2 that when the foaming agent concentration is less than 0.4%, as the foaming agent concentration increases, the foaming volume increases to a certain amount, from 120 mL with a foaming agent concentration of 0.10% to 129 mL with a foaming agent concentration of 0.4%; The defoaming half-life is greatly increased, from 14 min with a foaming agent concentration of 0.10% to 42 min with a foaming agent concentration of 0.4%. When the foaming agent concentration is greater than 0.5%, with the increase of the foaming agent concentration, the foaming volume decreases slightly.
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When the foaming agent concentration is 0.8%, it decreases to 127 mL; but the defoaming half-life decreases significantly, and the foaming agent concentration decreases when the foaming agent concentration is 0.8%. To 27 min. The results show that YC foaming agent has good foaming and foam stabilization performance when the concentration is 0.4~0.5%. 3.2 Foaming Agent Solubility Prepare YC foaming agent solutions of different concentrations with M oilfield water, and observe the dissolution time while stirring. The results are shown in Table 3. Table 3. Foaming agent dissolution test results Foaming agent concentration/%
Dissolution time
0.10
99%), optimizer serial function, communication functions, and so on. Gao Zhiyang [23] optimized the sampling circuit and designed a power optimizer based on the BUCK circuit. The drive circuit design, PWM wave feedback modulation, and protection algorithm were all tested using the PV simulator and an electronic load. Zhu T. et al. [24] proposed a componentlevel DMPPT system with dual-loop control based on the concept of DMPPT, which has a time-sharing self-adjusting maximum current tracking algorithm method, which by detecting the output current of series-connected DC-DC converters, can always guarantee that all PV element outputs its maximum power. Hanson A. J. [25] et al. discovered that partial occlusion components with no built-in component-level optimizer lost 13% compared to 8.3% for components with built-in component-level power optimizers and 8.3% for components with built-in component-level power optimizers. The piece recovered 36% of the occlusion power. The annual power generation of commercial PV systems was simulated by Doubleday K. et al. [26] The results showed that components with built-in optimizers can reduce loss by 3548%, and that optimizer modules in densely packed arrays can increase annual power generation by up to 7%. The research on sub-cascade power optimizers focused primarily on the basic characteristic analysis, performance test, and optimizer combination. Robert C. N. [27] et al. designed a substring based on a buck circuit Power optimizer, working efficiency is greater than 98%, and combined with the whole battery to make smart component samples and shading. In the test, when a battery was 50% blocked, the power of the smart module is increased by 24.1% compared with the ordinary module. When the smart component was occluded, its power generation gain was greater than 20%. Qi Gao et al. studied, theoretically analyzed, and combined I-V characteristics of sub-string smart modules based on the whole cell using a Matlab/Simulink simulation model. The I-V characteristic output curve of the smart module was obtained, which serves as a foundation for smart module modeling and power testing. Chris D. et al. [29, 30] studied the power generation performance of smart components based on the whole battery. They studied the influence of module front and rear row spacing, module footprint ratio, and seasonal changes on the power generation of smart modules, performed the power generation simulation through the PVsyst software, and studied the phase of sub-string-level smart components under various artificially simulated occlusion conditions. For the power generation gain of ordinary components, the shading weakening factor of smart components can be calculated, which was used to study the power generation gain of smart components.
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In this research, Matlab/Simulink software was used to establish an electrical model of smart components based on half-cell batteries, and research on smart components was carried out. The I-V characteristic curves of the energy modules and arrays under various occlusion conditions were obtained. The model was used to obtain the simulation results under such various conditions.
2 Modeling Establishment and Discussion 2.1 PV Phenomenon Figure 1 depicts the output characteristic curve of PV modules under irradiance conditions of 200, 400, 600, 800, and 1000W/m2 . When the components are exposed to different irradiance levels, the intersection point of the I-V curve and the abscissa are not the same. When the irradiance falls below 1000 W/m2 , the open circuit voltage Voc of the component falls as well, but only slightly [31]. The short-circuit current Isc of the PV c cell is depicted in the figure as the PV module’s output characteristic curve and the ordinate axis. As the irradiance decreases from 1000 W/m2 at the intersection point, the maximum power point current Im of the PV module decreases proportionally.
Fig. 1. The I-V curve of the PV module output under different irradiance.
Figure 2 shows PV module P-V curves under irradiance conditions of 200, 400, 600, 800, and 1000W/m2 . The maximum power value changes when the irradiance changes, according to the curve’s trend, but there is only one maximum output power [32]. The open circuit voltage corresponding to each P-V curve, like the I-V curve, is inconsistent. A Fill Factor (FF) is introduced to represent the electrical performance of the module in order to evaluate the output index of the cell or module. FF is the product of the maximum power point voltage and current of the component to the product of the opencircuit voltage and short-circuit current, filled with a factor that is greatly affected by irradiance.
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Fig. 2. The P-V curve of PV module output under different irradiance.
2.2 Solar Cell Single Diode Model The single-diode model mainly consists of a photo-generated current source, a parallel diode, a series resistor, and a parallel resistor. Rs represents the series resistance as the voltage loss inside the battery, and Rsh in the model represents the parallel resistance. The leakage current is shown, so the smaller the Rs is better, and the larger the Rsh is better. These two parameters are variable and affect the pool’s PV power Maximum power and fill factor.
Fig. 3. Five-parameter model for a single diode.
According to Fig. 3, the I-V characteristic equation for the single diode model of the solar cell is: V + I · RS V + I · RS −1 − (1) I = Iph − IS exp n · VT RSh VT =
NS · k · T q
(2)
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In the formula, Iph is the photo-generated current, A; Is is the reverse saturation leakage current of the diode, A; n is the ideal factor of the diode sub; VT is the thermal voltage, V; Ns is the number of cells connected in series; k is the Boltzmann constant, 1.3806505 × 10−23 J/K; T is the temperature of the p-n junction, K; q is the electron charge, 1.60217662 × 10−19 C; Rs is the equivalent series resistance, ; Rsh is the equivalent parallel resistance, . The single-diode model contains five parameters Iph , Is , Rsh , Rs , and n, so it is often called the five-parameter model [34]. This model is not only suitable for simulating a single cell but also for assemblies and arrays composed of multiple cells. In not Under the same weather conditions, more accurate battery parameters can be output. 2.3 Solar Cell Dual Diode Model Sometimes a two-diode model is introduced to simulate the characteristics of PV cells more accurately. The cell’s double diode solar power equivalent circuit is mainly composed of a photo-generated current source, two diodes, series resistance, and a parallel resistance, as shown in Fig. 4.
Fig. 4. Two-diode model.
It can be seen from Fig. 4 that the I-V characteristic equation of the two-diode model of the solar cell can be V + I · Rs V + I · Rs V + I · Rs − 1 − Is2 exp −1 − I = Iph − Is1 exp n1 · VT n2 · VT Rsh (3) Among them, Is1 is the reverse saturation current generated by the diffusion of electron-hole pairs in the equivalent diode D1, Is2 is Due to the reverse saturation current generated by the recombination of electron-hole pairs in the equivalent diode D2, n1 is the diode ideality factor of D1 child, n2 is the diode ideality factor of D2. The formula includes Iph , Is1 , Is2 , Rsh , Rs , n1 , n2 , etc. Seven parameters can be defined as n1 = 1, n2 = 2 [35], then there are only five unknown parameters in the model, so the model is also called the double diode five-parameter model. Figure 5 shows the circuit diagram of the dual-diode model of the cell in Simulink.
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Fig. 5. The circuit diagram of the dual-diode model of the cell in Simulink.
Fig. 6. Simulink Model of Smart Half-cell module.
2.4 Modeling of Intelligent Half-Chip Components Based on Matlab/Simulink Figure 6 is the Simulink model of the intelligent half-cell module, which contains three independent substring circuits that can be calculated separately. The output current I and output voltage V of each substring under arbitrary irradiance, temperature and shading
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conditions, as the corresponding chip The input current Iin , and input voltage Vin , and then calculate the output current Iout , and output voltage of the chip through the transfer function Press Vout . Figure 7 is the simulated output characteristic curve of the smart half-cell module. The I-V curve of the intelligent half-cell module is from the short-circuit current to the open-circuit voltage direction, corresponding to the “current limiting working area”, “MPPT work area” and “fixed duty cycle work area”, the curve shape conforms to the theoretical analysis. It can also be seen that for a half-cell module, there is a peak in the P-V curve, which is the Pm of the half-cell module. However, for smart half-cell modules, the maximum short-circuit current Isc is 12A, and there is a maximum power point and a range interval in the P-V curve. However, from the simulation results, it is known that the Pm of the smart half-cell module is 375.3W, which is 1.2% lower than the 380W of the conventional half-cell module. This is consistent with the efficiency curve of the chip, indicating that the chip has a certain power loss, which reduces the power of the component output. However, the chip regulates the operating voltage and current values of smart components within their maximum power output range. There is no mismatch between substrings and components, allowing the array to produce its maximum power output.
Fig. 7. The I-V and P-V curves of conventional half-cell modules and smart half-cell modules.
2.5 Modeling of Intelligent Half-Cell Module Array Based on Matlab/Simulink Figure 8 Simulink model of a Smart Half-Cell Array; the array is made up of six smart half-cell modules connected in series. To facilitate the occlusion setting of one of the components, first construct a Simulink model of one smart component, then encapsulate five half-piece components as a whole, and construct five Simulink models of the block intelligent half-cell components. It is possible to obtain an array Simulink model with six smart half-cell components.
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Fig. 8. Simulink Model for Smart Half-Cell Component Array.
Figure 9 depicts the simulation results of the I-V and P-V curves of an array with six smart half-cell modules under STC, indicating that the above method can be used to create an intelligent half-cell module array model.
Fig. 9. Simulation results of I-V and P-V curves under STC for smart half-cell module array.
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2.6 Power Gain of a Single Smart Module In the single module mode, one cell is arbitrarily selected for occlusion, and the occlusion ratio is from 0% to 100%; and 10% is the interval. The I-V and P-V curves of the two components under each occlusion ratio are simulated, respectively, and the corresponding power loss and the power gain of smart components is calculated. Figure 10 shows the I-V and P-V curves when occluding the conventional half-cell module. It can be seen that the I-V curve has a typical “step”, the corresponding P-V curve has a typical “double peak”, when the occlusion ratio gradually increases, the “step” of the I-V curve. The “spike” on the right side of the P-V curve gradually decreases. When the occlusion ratio is increased from 10% to 80%, the group global maximum power point of the component is at the “peak” on the right side, and the maximum power value of the component gradually decreases, and the power loss gradually decreases. When the occlusion ratio is 90% and 100%, the global maximum power of the component is at the left “peak”, and the component maximum power remains unchanged, and the power
Fig. 10. The I-V and P-V curves when the conventional half-cell module is occluded.
Fig. 11. The I-V and P-V curves when the smart half-cell module is occluded.
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loss also remains unchanged, indicating that the diode corresponding to the shaded cell has been started up. Figure 11 shows the I-V and P-V curves when the smart half-cell module is occluded. It can be seen from the P-V curve that when the module is blocked occluded, the corresponding maximum power is still an interval. The high-power value also gradually decreases, and the power loss gradually increases.
3 Results and Analysis of Hot Spot Experiments The results of the hot spot experiment are shown in Fig. 12. In the open circuit state, since no current loop is formed, the components are produced with no heat spots. In order to more accurately reflect the temperature difference of different components, the following equation is introduced: T = Tmax − Tave
(4)
where T represents the difference between the maximum temperature Tmax and the average temperature Tave in the monolithic component.
(a)
(c)
(b)
(d)
Fig. 12. Infrared Thermal Image of Component in Open Circuit.
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When the component’s positive and negative output terminals are short-circuited, the current is the largest at this time, which is Isc . Figure 13 shows the situation when there is no shielding. The temperature in the experimental group is very uniform, but some cells in the control group have hot spots, as seen in the infrared thermal image. The situation clearly contrasts with the surrounding cells.
Fig. 13. Infrared thermal image of the component when the short circuit is unobstructed.
4 Conclusion The software Matlab/Simulink is used to create a half-cell battery. The electrical model of the smart component simulates the output characteristic curve of the smart component and combines the measured values to verify the model’s accuracy. The Gain in outdoor power generation; smart module hot spot testing under indoor and outdoor conditions, and smart principle of component heat-spot prevention; were all carefully taken into account. The following are the main points and findings: 1 Using Matlab/Simulink software, a conventional half-cell module was established based on the double-diode model, and the model’s accuracy was verified under various irradiance, temperature, and shadow occlusion conditions. The group is constructed
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in the same manner as an equivalent circuit diagram, which is an advantage of this model. Parts or array models avoid many heavy mathematical calculations, improve model establishment efficiency, and have a high model Quasi-accuracy. The smart component’s Matlab/Simulink model is established, and the I-V and P-V of the smart half-cell module are drawn. The results show that the smart component’s maximum power is an interval. The real-time power of the intelligent half-cell module under no occlusion and occlusion are simulated, respectively. Based on the outdoor power generation test platform, the power generation gains of the two smart components were tested under unobstructed conditions. The cumulative power generation gains of the energy half-cell module and the intelligent smart halfcell module are -0.64% and 0.31%, respectively. The indoor hot spot test of the smart module shows that, the conventional half-cell module produces an obvious hot spot phenomenon when shading. The maximum temperature difference of the hot-spot cell is 72.4°C, while the smart half-cell module is only 4.2°C.
Acknowledgement. The authors would like to thank the professors and research colleagues at Southwest Jiaotong University’s School of Mechanical Engineering in Chengdu, China.
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13. Sharma, V., Chandel, S.S.: Performance and degradation analysis for long term reliability of solar photovoltaic systems: A review. Renew. Sustain. Energy Rev. 27, 753–767 (2013) 14. Guo, S., Singh, J.P., Peters, I.M.,et al.: A Quantitative Analysis of Photovoltaic Modules Using Halved Cells. Int. J. Photoenergy (2013) 15. Dandan, R., Jingna, J., Jianxiong, N., et al.: Application of half-cell technology in photovoltaic modules Progress in New Energy 5(4), 255–258 (2017) 16. Hamed, H., Jens, S., Joerg, B.: Reduced shading effect on half-cell modules-measurement and simulation. In: 31st European Photovoltaic Solar Energy Conference and Exhibition, pp. 2529–2533 (2015) 17. Ning, Y., Dai, Y., Wang, Z., et al.: Comparative study on power generation efficiency of photovoltaic systems with different MPPT architectures Chin. J. Electron. 44(9), 2134–2140 (2016) 18. Deline, C., Dobos, A., Janzou, S., et al.: A simplified model of uniform shading in large photovoltaic arrays. Sol. Energy 96(4), 274–282 (2013) 19. Matthias. K., et al.: Classification and comparative evaluation of PV panel integrated DC-DC converter concepts. In: 15th International Power Electronics and Motion Control Conference (2012) 20. Checco, P., Biey, M., Righero, M., et al.: A new control strategy for the optimization of Distributed MPPT in PV applications. Int. J. Electr. Power Energy Syst. 62(62), 763–773 (2014) 21. Olalla, C., Clement, D., Maksimovic, D., et al.: A cell-level photovoltaic model for highgranularity simulations. In: Proceedings of the IEEE European Conference on Power Electronics and Applications, pp. 1–10. IEEE (2013) 22. Liu, Y.: Research on series power optimizer in photovoltaic grid-connected system. Harbin University of Science and Technology (2018) 23. Gao, Z.: Research and design of photovoltaic system power optimizer. Anhui University (2016) 24. Zhu. T., Wang, F., Shi, S., et al.: Optimization of time-sharing output Maximum Current Tracking (MCT) strategy in subpanel level Distributed Maximum Power Point Tracking (DMPPT) application. In: IEEE, International Power Electronics and Motion Control Conference, pp. 3435–3440. IEEE (2016) 25. Hanson, A.J., Deline, C.A., Macalpine, S.M., et al.: Partial-shading assessment of photovoltaic installations via module-level monitoring. IEEE J. Photovoltaics 4(6), 1618–1624 (2014) 26. Doubleday, K., Choi, B., Maksimovic, D., et al.: Recovery of inter-row shading losses using differential power-processing submodule DC–DC converters. Sol. Energy 135, 512–517 (2016) 27. Robert, C.N., Pilawa, P.: Submodule integrated distributed maximum power point tracking for solar photovoltaic Applications IEEE. IEEE Trans. Power Electron. 28(6), 2957–2967 (2013) 28. Qi, G., Zhang, Y., Yu, Y., et al.: A direct current-voltage measurement method for smart photovoltaic modules with submodule level power optimizers. Sol. Energy 167, 52–60 (2018) 29. Chris, D., Bill, S., Josh, S., et al.: Evaluation of Maxim ModuleIntegrated Electronics at the DOE Regional Test Centers. NREL (2014) 30. Chris. D., Jenya, M., Matt, D.: Photovoltaic Shading Testbed for Module-Level Power Electronics:2016 Performance Data Update. NREL (2016) 31. Liu, Z.: Solar cell output characteristics and environmental monitoring. Hunan University (2013) 32. Feng, Z.: Research on the influencing factors of solar photovoltaic power generation performance. Inner Mongolia University of Technology (2013) 33. Xu, X.: Research on prediction model of grid-connected photovoltaic power generation based on hybrid method. Sensor World 22(11), 14–18 (2016)
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Finite Element Model for Prediction of Buckling Phenomenon in Oil and Gas Wells Yousif Eltahir Bagadi1(B) , Yasir M. F. Mukhtar1,2,3,4(B) , and Faleh H. M. Almahdawi5 1 College of Petroleum Engineering and Mining, University of Science and Technology,
Khartoum, Sudan [email protected], [email protected] 2 College of Engineering, Sudan University of Science and Technology, Khartoum PO Box 407, Sudan 3 College of Safety and Ocean Engineering, China University of Petroleum, Beijing 102249, China 4 UCSI University, 56000 Cheras, Kuala Lumpur, Malaysia 5 Petroleum Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq [email protected]
Abstract. Tubular buckling is caused by the axial compression load and is defined as a loss of the original rectilinear condition. Numerous studies have long been conducted to investigate the buckling of string in a borehole. Existing buckling theories, according to an increasing number of experts, need to be investigated because they are unable to accurately predict the buckling phenomenon. Indeed, current buckling theories frequently propose a flawless wellbore with a smooth trajectory profile. A pipe buckled in a deviated well trajectory can cause casing damage, decrease compression load to the bottom, drillpipe failure, trajectory change, severe catastrophic environmental problems, etc. As a result, it is critical to conduct research into the impact of tubular buckling inside horizontal wellbores to reduce or avoid the aforementioned issues. The Numerical Modeling Simulation was used in this study to forecast the critical buckling load for a pipe structure and how it will behave under different loads; these predictions were then confirmed by experimentation and a few analytical Copyright 2020, IPPTC Organizing Committee. This paper was prepared for presentation at International Petroleum and Petrochemical Technology Conference 2022 online between 12-13 October,2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Technical Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Technical Committee, its members. Papers presented at the Conference are subject to publication review by Professional Team of Petroleum Engineering of the IPPTC Technical Committee. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 607–621, 2023. https://doi.org/10.1007/978-981-99-2649-7_53
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Y. E. Bagadi et al. techniques. In terms of load transfer (helix prediction) and sinusoidal prediction, this paper presents experimental and theoretical findings for drill string and weight on bit (WOB). The findings of this study indicated a good Finite Element (FE) model which has been created and successfully validated using experimental data and an industry-standard simulator. Even though current models were unable to predict observed buckling behavior, the novel buckling model provided excellent forecasts for various drillstring configurations. Besides, the ability of this FE model to predict the onset and severity of buckling in a 3D trajectory has been successfully demonstrated. Keywords: Critical Buckling Prediction · Drillstring · FE Model · Bottom Hole Assembly (BHA) · Tubular Failure
1 Introduction 1.1 Recent Advancements in Drill String Mechanics Modelling The buckling of pipe within borehole has long been the focus of numerous studies [1]. Existing buckling theories need to be questioned because they can’t accurately anticipate the buckling phenomenon, according to many observations of buckling in the field. In fact, current buckling theories often presuppose that the wellbore is idealistically flawless and freed from any dog legs. Recent developments in drillstring mechanics modeling have shown that rotation, friction, and dog legs have a significant impact on the buckling phenomenon [2]. This study compares the results of buckling experiments with a newly created buckling model that accounts for the wellbore’s actual tortuosity Axial compression load causes a tube to buckle, losing its original rectilinear shape. Understanding the buckled tubular design is crucial to preventing failures and determining whether additional tool enforcement down the horizontal well is possible. Structures can fail in a variety of ways depending on the material, type of loads, and state of the supports. By carefully keeping their maximum stress and maximum deflections within allowable limits, most of these types of failures can be prevented. Buckling of a fatigue structure is a severe issue that has existed in oil and gas field drilling for decades. Because of that, it is important to continue studying this phenomenon. Additionally, the oil industry is aware of the significance of investigating buckling phenomena for well tubing and its impact on tools installation and selection. 1.2 Critical Load A tubular is submitted to a compression load and this load is steadily raised, the tubular will reach a condition known as neutral equilibrium, at which the tube will begin to bend. The equivalent load is also known as the Euler load and is referred to as the critical buckling load. Leonhard Euler (1707–1783) was the first person to study the bending up a slender column and determine its critical load (1744). The slender column theory for Euler’s Formula: π 2 (1) Fcrt = EI L
Finite Element Model for Prediction of Buckling
609
A series of lab tests for determining helical load for a vertical section was conducted, and the following formula was derived from experimental data [3]: Fhel = 2.8(EI )
0.504
0.496
(W )
sinα r
0.511 (2)
The previous findings result in the equation shown below [3]: Fhel = 2.93(EI )
0.479
(q)
0.522
sinα r
0.436 (3)
Also, an unstable inclined circular hole was studied [4, 5]. Solutions to the helical extended model were presented by using a hybrid solution (semi-analytical solution) [5– 8]. Other researchers studied buckling behaviors by use of both the virtual-work principle and the tubular-buckling equation. Their solution has been used vastly in petroleum industry [4 and 5]. The drag of helical pipes in directional wells was inspected [9, 10, 11, 12]. Also, an analytical solution was provided to foresee buckling performance in deviated section in which the torque reduced the critical buckling load which relies on torque, angle, and hole sizes [13]. Another work [14] developed an actual structural shape of helix of pipe by providing an theoretical approach based on equilibrium method. Gao et al. [15], and Huang and Gao [16] inspected the influence of connectors on buckling; also, Huang and Gao Deli [17] studied the boundary conditions as a key factor impacting tubular buckling. Huang and Gao [18] also investigated the buckling analysis of strings with connectors confined inside boreholes. Many studies pointed out that the models that they were using incapable to predict observed drill-string behavior. Therefore, instead of FE model, they utilized physical model based on the Cosserat rod theory [19], and to predict drill-string dynamics, it was advised that a novel procedure has to be applied to calibrate the model before guiding field decisions [20].
2 Methodology The numerical methods used here utilizes 3D beam elements to simulate the drillstring components. The model was presented by assuming that: a. b. c. d. e. f. g. h. i.
The drillstring as a beam consists of elastic material with Young’s modulus, E. Each beam has a circular hollow cross-section. The wellbore is as a rigid with a circular cross-section. Each element has its own weight, contact with the wellbore with external forces. The displacement of each beam is suitable to the hole clearance, The static of the beam whose coefficient of friction is affirmatively present, The trajectory is supposed to be a horizontal profile. The Wellbore was built by picking a tight explanatory item. The Drillstring model was a 3D beam.
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Basic equations of bottom hole assembly (BHA) geometrically nonlinear finite element analysis can be demonstrated as follows: The model element deformation vector is defined as T {e(t)} = u1 , v1 , w1 , θy1 , θz1 , ϕ1 , u2 , v2 , w2 , θy2 , θz2 , ϕ2 (4) Utilizing the assumed displacement fields, the transverse and axial deformation of an element is represented in terms of shape functions as: ⎧ ⎫ ⎡ ⎤ ⎪ 0 0 0 Nu1 0 0 0 0 0 Nu2 0 0 ⎨ u(x, t) ⎪ ⎬ ⎥ ⎢ 0 Nv4 0 ⎦ v(x, t) = ⎣ 0 Nv1 0 0 Nv2 0 0 Nv3 0 ⎪ ⎩ w(x, t) ⎪ ⎭ 0 0 Nv1 Nv2 0 0 0 0 Nv3 −Nv4 0 0 ⎡ ⎤ Nu ⎢ ⎥ {e(t)} = [Nv (x)]{e(t)} = ⎣ Nv ⎦{e(t)} Nw
(5)
2.1 Finite Element Model Input The running of the FE formulation to analyze the drillstring model involves the following input: (1) (2) (3) (4) (5)
The data for geometry, control parameters, meshing, boundary conditions; The mechanical loads for each stage; The material properties; The matrices in the integration points of the elements; The element stiffness matrices and global stiffness matrices;
In model analysis the drillstring performance was subjected to axial forces inside a borehoe. 2.2 Model Property A steel of elastic properties with mass density = 7800 kg/m3 ; Young’s modulus = 209 × 109 ; Poisson’s ratio = 0.3. For plastic properties: for Yield Stress = 168.72 MPa the Plastic Strain is 0. 2.3 FE Large Deformation Geometrical effects, material, and boundary were the sources of the nonlinearities. Thus, friction and contact have been considered. This general static analysis will consider the clearance to allow the drillstring deformed shape inside the wellbore curvature; the stiffness tubular was used in this analysis.
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2.4 Steps, Increments, and Iterations Abaqus Dynamic Explicit Step was used with the time step. The define steps, that involve the analysis step, that is by connecting the analysis with the output deformation of Linear Buckling. Each step involved the application of loads, model parameters, and output queries. 2.5 Contact Interaction Surface to node contact was used to model the contact that occurs between outer structure surface and the drillstring nodes. The tangential and contact property behavior considering friction was utilized (friction coefficient 0.0, and 0.3). At the beginning of the operation, no contact is supposed, and contact location and points are then determined. Hence this method is an appropriation for drillstring responses, the output results presents some focus into the complex performance which imposed from the interaction between the tubular and the wellbore. 2.6 FE Analysis 1. Displacement for String (Uy = Uz = 0). 2. Displacement at bit bottom (Uy = URy = 0). 3. For rig body, it is Encastre (Ux = Uy = Uz = URx = URy = URz = 0). 2.7 BHA and Rock Brick The mesh of the drillstring was done via using beam elements type (B33). For the formation, it is useful to select C3D10M element type. 2.8 Post Buckling “Abaqus Static Riks Step” with the “Linear Buckling imperfection Step” for simulation of “Post buckling” is utilized here. Th steps are generally consisting of an analysis procedure, that is by connecting the analysis with the output deformation of “Linear Buckling” (see flow chart Fig. 10 for the whole process).
3 The Experimental Procedure A steel tube that was confined inside of a glass tube was used as a borehole in an experiment that aimed to model and assess buckling phenomena, drag, and torque. An factory pc can be used to record the test’s outcomes (Fig. 1). A linear displacement transmitter was used to measure the results of the laboratory tests (LVDT). To record the data, the sensors are wired to a PC. The pipe has two diameters (OD = 32 mm and 27 mm; ID = 25 mm and 21 mm, respectively), and the glass tube has a diameter of 149 mm (Fig. 1).
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Fig. 1. Schematic Diagram of Buckling Laborator
In Fig. 1, which depicts the correlation between deformations and shear force, the outcomes were plotted. Point A suggests that the pipe buckled into a sinusoidal mode, while Point B depicts the beginning of a helix, Point C the development of a helix, and Point D the disappearance of the helix. The offloading path was guaranteed to represent the friction - free state, and since this situation was supposed in all numerical solution, this route will be used as the actual lab results to verify the model. Comparisons of the lab Results and the analytical approaches: utilizing the theoretical methods when compared with lab results Fig. 2. Beginning with 1D models, it is important to show that FEM results matches the known analytical solutions very closely, and then transition to 3D and present the drill-ahead model. Figure 3, shows an example problem is to be used here: a 500 ft drillstring composed of tubular with an outside diameter(OD) of 8.25 in. And an inside diameter (ID) of 3 in. The drillstring has a density of 0.000741 lb-s2/in4, and a modulus of elasticity of 30,000,000 psi.
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3.1 Drag-Buckling Relationship Frictional Contact forces between two tubes (one constraint by the other) can be predicted using FE model Fig. 2. This contact force exerted is important factor affect buckling phenomenon due to the constraining boundary condition. Finite Element (FE) Model using dynamic Explicit where the beam element makes contact with analytical rigid parts, the FE output shown in Fig. 5 and Fig. 6 is quite acceptable for predicting Sinusoidal and Helical Buckling.
Axial Force; KN
10 8 6 4
Experiment Results
2
FE Results
0 0
5
10
15
Axial Displacement ; m Fig. 2. Axial Force vs. Displacement for Lab and FE Results
Fig. 3. Comparison between Inman Solution and FE Method
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a
b
Fig. 4. a) Frictional Contact forces using FE model b) Frictional Contact forces and Contact Pressure using FE model
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Fig. 5. Predicting Sinusoidal and Helical Buckling and Van Mises Stress
3.2 Case Study The data of a directional well has been provided as follows: A hole of inclination angle of 23 ° Drilling in a formation hardness of 30; WOB at 155 kN; TOB of 1355 N-m; rotation speed at 100 RPM; drill ahead 1.5 m using PDC bit; drilling fluid weight of 1078 kg/m3; The wellbore, drillstring information and survey data are in Tables 1 and 2: In Fig. 6 and 7 show a quite match of numerical model results with results obtained from a commercial software, and close results from our FE Model are obtained. This is concerning the relation of maximum stress, Momentum, Side Force, and displacements.
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S/N
Section type
Depth; m
1
Riser
152.4
2
Casing
1706.88
3
Open Hole
2286
Length; m
ID; mm
Effective Hole Diameter; mm
Friction factor
152.4
482.6
609.6
0.2
1554.48
258.88
311.15
0.2
579.12
253.37
253.36
0.3
Catalog Summary
CAS 10 3/4in, 32.75 ppf, H40, STC
4 Results and Discussions A comparison was made between the numerical model and lab results for buckling of a tube contained in a glass tube subjected to axial force as shown in Fig. 1 of FE simulation is consistent with the laboratory results. The BHA restricted in casing, the interaction between the two tubulars (Fig. 4a and 4b), the axial forces, and the displacement were all modeled using our simulation analysis. Figure 2 showing that FE model output results has a good match with lab results. Figure (4a and 4b) for contact force results between tubular can be exercised in predicting tubular failure/damage or fatigue and where it may take place. Figure 4 (a and b) shows the clear effect of the normal contact force on tubular due to accounting for friction and hardness (12 KN). From Fig. 9 and Fig. 10 show the general static step of the experiment and the critical buckling load can be calculated from the product of load proportionality Factor (LPF) by the axial applied load: Critical Buckling Load (Pcr ) = 0.8612*12000 = 10334N. FE model was used to analyze and predict the effect of friction force on transferring the required axial force to the bottom and the possible failure in drillstring that caused by high bending moment force (Fig. 6 and 7). Figure 5 shows the Van Mises stresses possible failure magnitude and position along the string. The results obtain by using Abaqus Explicit and Standard Static General match the unloading result provided by the experiment (Fig. 2, 4b and 9). On the other hand, in addition to the steady state of the tube buckling, highly complex nonlinear dynamic processes also take place, which are followed by stable and unstable changes in the drillstring’s rotation. Axial load, rotational torque force, and bending moment are three of them. Each is inextricably linked to a decline in drilling performance. (Fig. 6, 7 and 8).
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Table 2. Drillstring and Drillbit Data S/N
Section type
Length; m
Depth; m
OD; mm
ID; mm
Weight; kg/m
Catalog Description
1
Drill pipe
1878.178
1878.18
127
108.61
31.09
DP 5in, 20.89ppf, E75, NC50(XH)
2
HWDP
283.464
2161.64
127
76.2
73.37
HW 5in, 49.3ppf
3
Jar
4
Drill Collar
5
9.144
2170.79
196.85
63.5
214.04
JHM 7 3/4in
82.296
2253.08
196.85
63.5
214.05
DC 7 3/4in, 2 1/2in, 6 5/8 REG
Stabilizer
1.524
2254.61
203.2
63.5
229.71
IBS 8in, 2 1/2in, 6 5/8 REG
6
Drill Collar
9.449
2264.05
196.85
63.5
214.05
DC 7 3/4in, 2 1/2in, 6 5/8 REG
7
Stabilizer
1.524
2265.58
107.95
63.5
55.94
ECC 7 13/16 in Blade, 41/4x2in
8
Drill Collar
9.449
2275.03
196.85
63.5
214.05
DC 7 3/4in, 2 1/2in, 6 5/8REG
9
Mud Motor
9.144
2284.17
203.2
63.5
229.71
BHM 8,8x2 1/2in
10
Stabilizer
1.524
2285.7
203.2
63.5
229.71
IBS 8in, 2 ½ in, 6 5/8 REG
11
Bit
0.305
2286
250.83
38731
BIT 9.875 in
Fig. 6. Transverse Moment along Distance from Bit
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Fig. 7. Vertical Moment along Distance from Bit
Fig. 8. Comparison of FEM with Landmark for Side Forces at Bit
Finite Element Model for Prediction of Buckling
Fig. 9. Post-Buckling (helical) Behavior inside a constraint tube
Fig. 10. Flow chart of Abaqus static General step program
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5 Conclusion The predictions of the Finite Element (FE) model in addressing the contact interaction of the bottom hole assembly (BHA), and casing may be deemed highly accurate according to a thorough investigation of the FE model and the comparativeness of experimental findings. Hence, the following points can be drawn: 1. The results of the experiment validated the FE model output data, demonstrating its ability to predict contact locations, contact force, and failure and damage. 2. The developed FE model was validated using the Inman analytical solution method. 3. A computer simulation was created to predict axial forces, contact forces, stresses, and other variables. 4. The Abaqus/Explicit FE Model employs beam elements, which produce an acceptable compromise between accuracy and solution time. 5. The FE Model resolved the contact problem specification for beam components and drillstring instabilities completely. 6. General Static Riks Step Analysis can be used to forecast critical buckling load and post-buckling. 7. The FE model was used to analyze and predict the possibility of drillstring failure due to contact force. The magnitude of Von Mises stress and its location along the BHA were modeled. 8. A new formulation of the problem of critical buckling of drill strings in 3D curvilinear bore holes was developed and solved (Sinusoidal or Helical).
6 Recommendation This study demonstrates the importance of considering the rotation effect on the behavior of tubulars. Consequently, considering rotation speed (RPM) when investigating the buckling of tubular inside a tube experimentally and theoretically is strongly advised.
References 1. Cunha, J.C.: Buckling of Tubulars Inside Wellbores: A review on Recent Theoretical and Experimental works. SPE (87895) (2004) 2. Mehdi Hajian malekin, Jeremy S. Daily: Advances in critical buckling load assessment for tubulars inside wellbores. 0920–4105, Elsevier B.V. (2014) 3. Lubinski, A., Woods, H.B.: Factors affecting the angle of Inclination and Dog-Legging in Rotary Bore Holes. Drill and Prod. Prac., API 222 (1953) 4. Paslay, P.R., Bogy, D.B.: The stability of a circular rod laterally constrained to be in contact with an inclined circular rod laterally constrained to be in contact with an inclined circular cylinder. Trans. ASME, J. Appl. Mech. 31, 605–610 (1964) 5. Paslay, P.R.: Stress Analysis of Drillstring. SPE27976 (1994) 6. Mitchell, R.F.: A Buckling Criterion for Constant Curvature Wellbores. SPE J., 4(4) (1999) 7. Mitchell, R.F.: Effects of Well Deviation on Helical Buckling. SPE29462 (1995) 8. Mitchell, R.F.: Numerical Analysis of Helical Buckling. SPE 14981, Presented at the 1986 Deep Drilling and Production Symposium of SPE Engineers of AIME, (1986)
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9. Mitchell, R.F.: Buckling Behavior of Well Tubing: the Packer Effect. SPE 9264, 1982, Society Petroleum Eng. J. 22(05), 616–624 (1982) 10. Jiang, W.: Torsion Load Effect on Drillstring Buckling. SPE37477 (1997) 11. Jiang, W., Juvkam-Wold, H.C.: Coiled Tubing Buckling Implication in Drilling and Completing Horizontal Wells. SPE Drilling & Completion, pp. 16–21 (1995) 12. Jiang, W., Juvkam-Wold, H.C.: Discussion of Tubing and Casing Buckling in Horizontal Wells. JPT (1990) 13. Jiang, W., Juvkam-Wold, H.C.: Study of Helical Buckling of pipes in Horizontal Wells. SPE25503, March 13–21 (1993) 14. Miska, S., Cunha, J.C.S.: Helical Buckling of Long Weightless Strings Subjected to Axial and Torsion Loads. PD-Vol. 65, Drilling Technology ASME (1995) 15. Gao, D., Liu, F., Xu, B.: An Analysis of Helical Buckling of Long Tubulars in Horizontal Wells. SPE50931. In: International Oil and Gas Conference and Exhibition in China, pp. 2–6 (1998) 16. Huang, W. and Gao, Deli. 2014b: Sinusoidal buckling of a thin rod with connectors constrained in a cylinder. J. Natural Gas Sci. Eng. 18, 237–246, (2014) 17. Huang, W., Gao, D.: Boundary conditions as a key factor affecting tubular-string buckling. Society of Petroleum Engineers SPE (174087) (2015) 18. Huang, W., Gao, D.: Buckling Analysis of Tubular Strings with connectors constrained in vertical and inclined wellbores. Society of Petroleum Engineers, SPE (180613) (2018) 19. Goicoechea, H.E., Lima, R., Sampaio, R., Rosales, M.B., Buezas, F.S.: A Stochastic Approach for a Cosserat Rod Drill-String Model with Stick-Slip Motion. In: De Cursi, J.E.S. (ed.) Uncertainties 2020. LNME, pp. 103–110. Springer, Cham (2021). https://doi.org/10.1007/ 978-3-030-53669-5_8 20. Lobo, D., Ritto, T., Castello, D., de Souza, M.: On the calibration of drill-string models based on hysteresis cycles data. Int. J. Mech. Sci. 177, 105578 (2020). https://doi.org/10.1016/j.ijm ecsci.2020.105578
The Impact of Acid Fracking Injection Pressure on the Carbonate-Mishrif Reservoir: A Field Investigation Faleh H. Almahdawi1 , Usama Alameedy1(B) , Ahmed Almomen1 , Ayad A. Al-Haleem1 , Ali Saadi2 , and Yasir M. F. Mukhtar3,4 1 Petroleum Engineering Department, College of Engineering, University of Baghdad,
Baghdad, Iraq [email protected] 2 Midland Oil Company, Ministry of Oil, Baghdad, Iraq 3 China University of Petroleum- Beijing, Beijing, China 4 Sudan University of Science and Technology, Khartoum, Sudan
Abstract. In Ahdeb oil wells, several unsuccessful acid-fracturing stimulation operations have been recorded (conducted). Strong variability in the Mishrif Formation results in a poor and rapidly declining single-well production rate following conventional acidizing. The optimal oil-field development strategy for such a reservoir will be suggested with the aid of treatment design and formation evaluations. After a well has been fractured, experts need to understand the treatment design and the formation to make accurate predictions of production or productivity-index ratio. The G-function and its diagnostic derivatives, the square root of time and its derivatives, and the log-log plot of pressure change after shut-in, will all be used to present the analysis. By examining the unique shapes of the derivative curves, leakoff processes and fracture closure locations may be identified. In the case of a typical leakoff, a fracture closes when the derivative curve of the g-function deviates from its tangent line (the best possible scenario). Both the pressure against the G versus time curve and its semilog derivative are shown in the G-function diagram.
Copyright 2020, IPPTC Organizing Committee. This paper was prepared for presentation at International Petroleum and Petrochemical Technology Conference 2022 online between 12-13 October,2022. This paper was selected for presentation by the IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IPPTC Technical Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IPPTC Technical Committee, its members. Papers presented at the Conference are subject to publication review by Professional Team of Petroleum Engineering of the IPPTC Technical Committee. Elec-tronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IPPTC. Contact email: [email protected]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 622–641, 2023. https://doi.org/10.1007/978-981-99-2649-7_54
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Keywords: Acid Fracturing · Carbonate Reservoir · Productivity Index (PI) · Well Testing · Mini Frac Analysis · G-function Analysis · Log-log Plot
1 Introduction Nearly one-third of the world’s hydrocarbon reserves are trapped in carbonate reservoirs [1]. This composition of carbonate reservoirs is quite complex due to the high reactivity of its carbonate minerals (chalk, dolomite, and limestone) and their high tendency to go through multiple stages of dissolution, as well as recrystallization. The oil industry has regularly employed acid fracturing as one of its popular stimulation strategies to improve (enhance) well productivity in acid-soluble formations. Acid fracturing operations (stimulation) can be conducted in two ways: either through fracture acidizing or matrix acidizing stimulation [2]. Fracture acidizing involves hydraulic fracturing treatment of carbonate formations by acid fluid injection to create very high conductive acid etched channels across the fracture face, whereas matrix acidizing involves the injection of acidic fluid into the formation through a wellbore to penetrate the pores in the rock at pressures below fracture pressure [3]. The matrix acidizing stimulation enhances the fluids flow in the well or removes the formation damage by dissolving the mud and sediments within the pores that reduced the rock permeability [4]. Results of previous research have shown that the dissolution of carbonate minerals by acid fluid injection normally results in the creation of a cylindrical shape dominant route within the pores known as wormhole formations [5, 6]. During acid fracturing process, the acid etching is used to create conductivity rather than the placement of proppant in fractures (hydraulic fracturing) [7]. A fluid system that is both efficient and non-damaging is often sought when using acid-based fluids for long-penetrating fractures. There are several ways to evaluate the candidate zone’s leak-off behavior; one of the most typical methods involves conducting a mini-frac assessment using the actual pad fluid system recommended for treatment [8]. The well is shut off after the injection to allow the closure of the fracture by formation stresses. A post-flush job is conducted to assist in further transportation of the acid into the fracture, hereby increasing the acid permeation distance. The quantity of conductivity formed following the closure of the fracture and etched fracture length determine the effectiveness of the fracturing procedure [7]. The face of the fracture dissolves as the acid runs through it. It is possible that if the acid erodes fracture faces unevenly, it will cause a conductor fracture [9, 10]. Acid reaction rate, acid fluid loss rate, and acid volume all affect the effective fracture’s entire width. Additionally, the fracture’s etching influences the existence of low stress or high stress in the fracture. When using etched acid-based or proppant fluids to create long penetrating cracks, it is necessary to have an efficient yet safe fluid system. Testing the candidate zone’s leak off performance, fracture shape, and fracture closure pressure with the actual pad fluid system that will be used in treatment is the most typical approach [8]. Numerous studies have been conducted to identify the governing mechanisms of acid-carbonate minerals reactions/interactions, mechanisms of acid flow-back, leak-off,
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as well as acidizing fluid models ([11]–[14]). Alterations of rock mechanical structure by acid stimulation treatment, as well as rock mineralogy’s impact on the effectiveness of acidizing jobs have also been studied. A number of laboratory experiments and fieldscale trials have been conducted evaluate the effectiveness of different acidizing fluids such as viscoelastic surfactant acid, self-diverting acid fluids, chelating agents, and gelled acid stimulation. However, hydraulic fracturing (should be acid fracture) stimulation implementations in carbonate reservoirs faced a number of challenges and uncertainty due to the complex nature of the carbonate reservoirs. Preferential flow of stimulation fluids into thief zones occurs frequently in highly permeable fractured and layered reservoirs, due to high permeability contrast (difference). The dissolution of carbonate minerals in carbonate formations by acids may result in changes to the structure, mineralogy, and mechanical characteristics of the rock around the wormhole, which either improve or harm the rock in the form of rock weakening or loosening. The hydrocarbon displacing fluid could preferentially flow through the wormholes, consequently bypassing the trapped oil in the pore spaces of the rock [15]. The Mishrif formation comprises multistory dense carbonates deposits on an expansive leveled shelf, and is regarded as the most prominent of reservoir formations in southern Iraq due to its geographical coverage, as well as the high original oil in place. This study took the Ahdeb oil field – Mishrif formation this field located about 160 km south of Baghdad discovered during the 70th century. The carbonate reservoir rocks of the Mishrif formation in the Ahdeb oil field are of high interest to commercial oil production in Iraq. The difficulties faced during the acidizing stimulation of the Ahdeb oil field, especially for optimizing hydrocarbon production in the Mishrif reservoir, have been widely reported in the literature. [16]. Acid fluid injection into this Mishrif reservoir formation has been highly demanding, because of high injection pressures, thus, not many successful acidizing stimulation operations have been reported (conducted) in Ahdeb oil wells. Accurate assessment of acid fracturing treatment and post-fractured well output of complex carbonate-Mishrif reservoir will play a prominent role in proposing the ideal oil-field development plan for a such reservoir. However, post-fractured well output or productivity-index ratio can only be reliably predicted with a thorough knowledge of treatment design and formation. Thus, the ultimate study was conducted to propose a model that can be utilized as guidelines for evaluating a complicated acid-fracturing stimulation of a low-productive well in the Ahdeb field.
2 Methodology Acid fracturing is required in the carbonate-Mishrif reservoir because some wells have stopped producing because of poor productivity index (PI), most often on the flanks after an aquifer influx. Whether the pressure in the reservoir is high enough, this might be a good first opportunity to see if acid fracking works. This is accomplished by developing well ADM7-X, specifically for Mi4 and Ru1 reservoirs, and then developing Ru2a, Ru2b, Ru3, and Kh2 reservoirs in the future well pattern rearrangement (no need to expand this technique in Khasib or Rumaila because it has good petrophysics). From a resource perspective, construct a qualified development well with the ultimate goal of economically
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extracting the greatest quantity of hydrocarbon from the reservoir. Depleted reservoir production flow profiles must be optimized to achieve this [17]. For optimal flow, a well completion plan must be established. It is essential to understand the variation in rock type from layer to layer and well to well via the use of geological characterization. Completion and stimulation design takes into account the distribution of rock types, the magnitude and distribution of permeability/porosity, and reservoir pressures [18]. 2.1 Analysis of Fracture Pressure Accurately predicting the performance of acid fracturing treatment wells, as well as ensuring the validity of the fracking process. Figure 1 by [19] illustrates a method for analyzing such a complicated process. There are three processes shown in each of the three boxes: completion assessment, acid fracturing simulation, and production forecast.
Fig. 1. Workflow for the multi-stage treatment assessment of acid fracturing [19]
Stage isolation techniques and friction prediction and bottom-hole pressure computation are all considered in the well-completion design presented in Fig. 1. The acid
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fracking results in fractures and the quantity and locations of those fractures are determined by the examination of stage isolation. Identification of the failure of fracture start is necessary to establish the real placement of fluid throughout the treatment. Either known fluid characteristics or friction gradients produced from surface pressure recordings may be used to estimate frictional pressure decreases. Bottomhole processing pressure may be determined using surface pressure measurements, tubing friction, and perforation pressure loss during pumping. Crack propagation models, in conjunction with well completion assessment and treatment schedule fluid placement data, can mimic fracture geometry. To ensure that the simulation findings are compatible with the treatment data, a pressure history match will be done Acid transport and reaction models are generated using the output fracture geometry. To establish the model boundaries, the fracture dimensions are discretized into a three-dimensional grid. The length and height of each grid are the same, but the width might change. The acid fracture conductivity profile may be generated by using an acid fracture conductivity correlation after the acid-etched grid widths at the fracture surface have been computed. Post-treatment production prediction is based on the predicted fracture diameters and conductivity of vertically fractured wells. 2.2 Basic Performance of Gelled Acid Acid diversion is crucial in carbonates for enhancing vertical wells with expanded target zones or horizontal wells [20]. In-situ gelled acids improve treatment efficiency by raising the viscosity of the injected acid and stopping its contact with the formation. Furthermore, the gel should degrade fast as the acid is depleted, making cleanup easier when the acid treatment is done [21]. 2.3 Mini Frac Analysis Significant input data for fracture design models and reservoir characterization data required to anticipate post-fracture production is provided by pre-frac diagnostic injection test analysis. The economic optimization of the fracture treatment design requires an accurate post-stimulation production expectation. The test data must be interpreted consistently and correctly to get reliable outcomes. The closure is often incorrectly determined when one or more analytical approaches are misapplied. In each case, the analysis will be presented by the use of the G-function and its diagnostic derivatives, the sqrt(time) and its derivatives, and the log-log plot of pressure change after shut-in and its respective derivatives [22–24]. The study of G-functions is one approach for reducing uncertainty and providing valuable information on stress and leakoff in the field. The G-function is a time function that connects shut-in time to total pumping time in a dimensionless manner. Derivative curves are used to determine leakoff processes and fracture closure points by analyzing the distinctive forms of the curves [25]. In the G-function graphic, a pressure vs. Gtime curve and a semilog derivative of the pressure vs. G-time curve are shown. In many circumstances, the semilog curve’s predicted signature is a straight line that passes through the origin. Fracture closure occurs when the G-function derivative curve diverges from its straight tangent line in the event of a normal leakoff (the best possible scenario).
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2.4 G Function Analysis During the pressure falloff phase, the pressure differential between two separate shut-in periods may be stated as follows, according to [23]. √ K · C · fp · tp · G(tD, fD), At > At ∗ (1) AF Ar∗ , At = 2 · cf After the match pressure P* is introduced, it is comparable to: √ K · C · fp · tp ∗ P = 2 · cf
(2)
In addition, using Castillo’s definition (1987), Eq. 1 may be revised to read as follows: P(At) = P ∗ · G(tD, 0) + P At ∗ = 0 (3) Linear expression in Eq. 3 is y = ax + b. Conventional G-function analysis results in a Cartesian plot that shows linearity during closure, whereas divergence from linearity indicates the closing pressure. The G-function graphic may be improved further by changing Eq. 3 to produce. dP = p∗ dG
(4)
The derivative of this technique has a constant value plateau, and the instant it deviates from the plateau is an indicator of closing time [22]. Typically, this is the only point of pressure that is taken into account when interpreting the data. 2.5 Log–log Diagnostic Graph A pressure buildup test is the most typical pressure transient testing approach. The downhole pressure increases when a producing well is shut in, as seen in Fig. 2. When the flow is stopped, pressure data can be collected. Permanent downhole pressure gauges, on the other hand, can provide a long-term continuous pressure record. Otherwise, when a pressure transient test is planned, those gauges on the wireline or slick line may temporarily drop. On a log–log diagnostic graph, transient well analyses are the easiest. It’s possible to see patterns that may be directly linked to the reservoir’s flow shape by looking at this graph. Transient data shows that each flow regime is moving away from the well as time goes on. Production engineers may use flow regime trends to calculate important parameters. Figure 3 shows the log–log diagnostic diagram for the accumulation data from Fig. 1. For each elapsed time Δt = t – t p , the pressure change Δpws(Δt) in Fig. 3 is computed as: pws (t) = p(t) − pwf tp
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Fig. 2. Data on pressure buildup in Cartesian coordinates graphed [26].
where t p refers to the time the well is shut-in. The derivative of the pressure change determined as indicated in Fig. 3 is the bottom curve. p =
dp dp = τ d lnτ dτ
where τ, time of superposition can be expressed as: t lnτ = ln te + t
2.6 Acid Frac Analysis During the stimulation of very thick reservoirs, the capabilities of the equipment (rates, volumes, horsepower, and so on) are often pushed to their limits. Mechanical separation may give further assurance that particular zones are stimulated; nevertheless, the use of mechanical isolation may be prohibitive due to the increased operating risks and expenses. The success of the stimulation treatment and the capacity of the well to reach the reservoir goals must be evaluated immediately after the completion of the treatment. Analyzing the therapy’s efficacy is vital after the stimulation treatment is completed. Well-designed testing is effective. The success of therapy cannot be assessed just by the results of well tests. With production logging, you can see the flow distribution as well as the completion, and when combined with single well and reservoir modeling, you can have a better idea of how successful the stimulation has been.
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Fig. 3. Diagnostic graphic of buildup data in log–log format [27].
2.7 Acid Penetration in Fractures The distribution of rock dissolution along the fracture is essential to anticipate the distance to which acid creates fracture conductivity and the ultimate distribution of conductivity. This necessitates predicting the acid content along the fracture. An acid balancing equation and proper boundary conditions are used to determine the acid dispersion along the fracture. Such linear flow equations can express fracture with fluid leakage and acid diffusion into the fracture walls: ∂(ux C) ∂ uy C ∂ ∂C ∂C + − − Deff =0 ∂t ∂x ∂y ∂y ∂y C(x, y, t = 0) = 0 C(x = 0, y, t) = C i (t) Cuy − CL qL − Deff
∂C = Ef C n (1 − φ) ∂y
where Deff is the effective diffusion coefficient, Ci is the injected acid concentration, Ef is the reaction rate constant, n is the order of the reaction, uy is the transverse flux due to fluid loss, and φ is the rock porosity, and C is the concentration of acid.
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2.8 Conductivity of Acid Fracture Because it is dependent on a stochastic process, it is not easy to predict the conductivity (k fw ) of an acid fracture: As a result, an empirical method has been used to estimate acid fracture conductivity. The amount of rock dissolved as a function of position along the fracture is first determined based on the acid distribution in the fracture. Then, depending on the quantity of rock dissolved, fracture conductivity is determined using an empirical correlation. Finally, an average conductivity for the whole fracture is obtained using some sort of averaging process because the conductivity typically varies greatly throughout the fracture. It is not reasonable to anticipate that the methods for forecasting the fracture conductivity of an acid fracture will be highly accurate. These methods can be “field calibrated” by determining the effective conductivity of acid cracks using pressure transient testing. The ideal width, wi , which is defined as the width of the fracture produced by acid dissolution before fracture closure, is a parameter used to describe the quantity of rock dissolved in an acid fracture. The fracture is complete when all of the acids injected into it dissolve the rock on the fracture face, then the average ideal width is calculated by dividing the total volume of rock dissolved by the fracture area, or wi =
χV 2(1 − φ)hf xf
where hf is the height of the fracture, xf is the length of the fracture half, and X is the acid’s volumetric dissolving capacity. The conductivity of an acid fracture can be calculated using the correlation [28]. According to experimental y observations, this correlation links conductivity with optimum width, closure stress, c, and rock embedment strength, S rock . The relationship between Nierode and Kruk is kf w = C1 e−C2 σc where C1 = 1.47 × 107 wi2.47 and C2 = (13.9 − 1.3lnSk ) × 10−3 2.9 Buildup Test Analysis ISIP (Instantaneous Shut-In Pressure) The instantaneous shut-in pressure, also known as the final injection pressure, can be used to distinguish between the pressure drop and the final injection pressure (ISIP). It is important because it allows for the calculation of fracture net pressure, a crucial component of any fracture model [29]. One current method to calculate ISIP is by-hand determination. Another method includes subtracting the friction component from the bottom hole pressure if they are available. However, these methods are prone to estimation errors. [29] implemented a method that used the main treatment pressure falloff to estimate ISIP. This technique also includes the Wellbore storage effect and friction dissipation. The completion design can be improved by automating the determination of ISIP.
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3 Results and Discussion 3.1 Properties of Geology and Petrophysics of Well ADM7-X Figure 4 and Table 1 illustrates the wireline logging interpretation for well ADM7-X. The lithology includes a diverse spectrum of limestone. The lithology on the bottom does not indicate light grey limestone separated with oil underneath Rumaila. This well interprets 34 zones. The total thickness of the 19 oil and bad oil zones is 135.8 m, whereas the total thickness is 57.2 m, with seven transition zones. The overall thickness of the water is 150.8m and there are 8 water zones [30]. It is vital to differentiate between oil-rich and oil-poor areas. The resistivity of these zones is higher, the oil saturation is
Fig. 4. Wireline log for well ADM7-X.
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greater than 47%, the effective porosity is greater than 15%, and the shale volume of most oil zones is often less than 10%. Mishrif Zone is an oil layer, the effective porosity is around 22%, the oil saturation is about 73%. In certain cases, acid fracturing in a deep, high-temperature carbonate reservoir may be the best option. Drilling activities or non-Darcy flow effects may harm highpermeability carbonate reservoirs; hence a treatment might be done to increase productivity. The pressure loss produced by the skin and/or non-Darcy flow may be reduced by introducing acid at fracturing rates, which improves the permeability around the wellbore [31]. The petrophysics of the well ADM7-X, mapping the porosity and mobility of the well, shown in Fig. 5, indicated that an acid frac was the best method for achieving a highly conductive fracture, Fig. 5.
Fig. 5. The petrophysics of the well ADM7-X.
3.2 Basic Performance of Gelled Acid Since Table 1 of the experimental findings of gelled acid, shows that the viscosity of reacted acid is only 3 mPa.s (equal to water), it can be assumed that the fracture and formation were not harmed after the acid frac operation. Table 1. Wireline logging interpretation for well ADM7-X. Well
Formation Interval (MD) Thickness (m) Net_Pay POR (m) (m) (%)
ADM7-X MI4
2797.1–2821.9 24.8
22.6
PERM SW (mD) (%)
19.535 9.748
31.676
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Table 2. Basic Performance of Gelled Acid Items
Test result
Appearance
Red-brown viscous uniform liquid
Viscosity,170S-1,25 °C, mPa·s
45
Viscosity,170S-1,90 °C,60 min, mPa·s
30
Static Corrosion Rate, 90 °C, g/m2·h
4.79
Surface tension, mN/m
23.75
Capability of Stabilizing Ferric ion, mg/mL
> 100
The viscosity of reacted acid, mPa.s
3
Table 3. Acid frac analysis results for the well ADM7-X. Parameters
Hydraulic fracture length (m)
Etched fracture length (m)
Fracture height (m)
Conductivity (mD.m)
Designed
74
65.8
2785.8-2823.1(37.3)
349.6
Simulated after acid frac
69.6
60.51
2786.4-2824.5(38.1)
304.7
3.3 Mini Frac Analysis The G-function curve analysis indicates that the bottom hole closure pressure is 5217 psi (35.97 MPa), the gradient is 1.856 psi/m (0.0128 MPa/m), and the closure time is 9.7 min. (Fig. 6). As shown in Figs. 7 and 8, further analysis is performed using the mini frac curve as well as pump rate with bottom hole pressure. Based on these results, we can conclude that: formation breakdown pressure is 45.8 MPa and the gradient is 0.0163 MPa/m; formation extension pressure is 44 MPa and the gradient is 0.0157 MPa/m. The friction was calculated using software, and it should be adjusted to account for actual B.H. pressure. The isostatic pressure in the bottom hole is 42.35 MPa, the isostatic pressure gradient is 0.0151 MPa/m, and hence the fluid efficiency is 22.86%. 3.4 Acid Frac Analysis On the basis of the net pressure fitting and the G function analysis (Figs. 9 & 10), we can see from Table 3 that the fractures were propagating constantly. In this particular situation, the simulated fracture length and conductivity are pretty similar to the expected properties (Fig. 11).
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Fig. 6. G-function curve analysis for the well ADM7-X.
Fig. 7. Pump rate VS B.H. Pressure for the well ADM7-X.
3.5 Buildup Test Analysis ISIP (Instantaneous Shut-In Pressure) Well, testing history demonstrating (Fig. 12) that the flowing pressure increased rather than decreased over the production period suggests that there is pressure support in place.
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Fig. 8. Mini-frac curve for the well ADM7-X.
Fig. 9. Net pressure fitting for the well ADM7-X.
3.6 Log-Log Plot Analysis During a falloff test that follows injection at fracture rate, many transient flow regimes may occur. A famous article by Cinco-Ley & Samaniego-V., 1981 visually illustrates the different flow regimes. The log-log plot, as shown in Fig. 13, reveals a distinct fracture characteristic, with area 1 indicating wellbore storage and region 2 exhibiting anomalous accumulation, which modifies the look of wellbore storage and is thought to be caused by dual linear
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Fig. 10. G-function curve for the well ADM7-X.
Fig. 11. Simulated fracture length after acid frac
flow. However, a pseudo-radial flow may be found in region 4, which has a typical fracture feature and linear flow. The advancing derivative plot reveals that the outer boundary has reduced permeability in region 5, which is linked to boundary response. An ideal mobility ratio for a composite reservoir is larger than one. After doing an analysis, the
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Fig. 12. Well, testing history for the well ADM7-X.
following are the findings: (K: 32.41, S: 6.18, Investigation Radius: 469m, SP 3117psi, Pressure Coefficient:0.791).
Fig. 13. Log-log plot shows a clear fracturing feature.
Using the Horner plot (Semi-log plot) and comparing it to the log-log plot, we can verify the conclusions (Fig. 14). The final results are summarized in Table 4 below, which demonstrates a good match.
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Pressure [psi]
2950
2910
1
2
3
4
5
Superposition Time Function
Fig. 14. Horner plot for the well ADM7-X.
Table 4. Acid frac analysis results for the well ADM7-X. Item
Log-Log plot Analysis
Semi-Log plot Analysis
Unit
Flow Coefficient, kh/u
264.52
265.68
mD.m/cP
Permeability-Thickness, kh
307.87
309.22
mD.m
Permeability, k
32.41*
32.55*
mD
Skin Factor, St
-6.18
-6.43
Investigation Radius, Rinv
469
/
m
3.7 Productivity Assessment After acid fracturing, production continues for 18 days until a buildup occurs (Fig. 15). It takes 208 barrels of oil per day (bbl/d) to be produced when the pressure falls below P 181psi. Its productivity indicator is PI: 1.15 barrels per day per pound of pressure reduction. In unit Mi4 of the Mishrif reservoir, the productivity index of well AD_x improved 6.4 times, which is a reasonable increase for vertical wells. Acid fracturing has been shown to have a significant increase.
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Fig. 15. Well AD_x Production after acid fracturing
4 Conclusions • According to the simulated results, artificial fractures occurred in the formation after fracture closure due to the acid’s corrosive action. The length of the etched fracture in the simulation is 60.5m, which is consistent with the specified values. • The log-log plots demonstrated typical fracturing characteristics, indicating that fracture occurred in the formation throughout the entire test period. • The input parameters, interpretation result range, and curve matching are crucial for build-up analysis. The AD_x result demonstrates that acid fracturing has a beneficial effect on reservoir and productivity indexes. • The productivity index PI of the AD_x is 1.15 bbl/d/psi after acid fracturing, which is 6.4 times that of vertical wells in unit Mi4. Acid fracturing significantly increases vertical well productivity. • Following acid fracturing, the AD_x is likely to sustain low productivity for an extended period. It is proposed to produce ESP for the AD_x and convert to nearby wells.
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24. Barree, R.D.: Applications of Pre-Frac Injection/Falloff Tests in fissured Reservoirs - Field Examples (1998) https://doi.org/10.2118/39932-MS 25. Yuen-Lee, V.: MINI-FRAC ANALYSIS REPORT (2013) 26. Economides, M.J., Hill, A.D., Ehlig-and Economides, C., Zhu, D.: Petroleum Production Systems, SECODN EDI. PENTICE HALL (2013) 27. M. J. Economides, A. D. Hill, and C. Ehlig-and Economides, Petroleum Production Systems. 1994 28. Nierode, D.E., Kruk, K.F.: An evaluation of acid fluid loss additives retarded acids, and acidized fracture conductivity (1973) https://doi.org/10.2118/4549-MS 29. Menouar, N., Liu, G., Ehlig-Economides, C.: A Quick Look Approach for Determining Instantaneous Shut-in Pressure ISIP and Friction Losses from Hydraulic Fracture Treatment Falloff Data (2018) https://doi.org/10.2118/191465-18IHFT-MS 30. Alameedy, U.: Experimental Study and Analysis of Matrix Acidizing for Mishrif FormationAhdeb Oil Field. University of Baghdad (2022) 31. Pathak, P., Fidra, Y., Avida, H., Kahar, Z., Agnew, M., Hidayat, D.: The arun gas field in indonesia: resource management of a mature field (2004) https://doi.org/10.2118/87042-MS 32. Cinco-Ley, H., Samaniego-V., F.: Transient pressure analysis for fractured wells. J. Pet. Technol. 33(9), 1749–1766 (1981) https://doi.org/10.2118/7490-PA
Author Index
A Abdallah, Elhassan Mostafa 106, 120 Ai, Weiping 1 Al, Ke-Baijiang 215 Alameedy, Usama 622 Al-Haleem, Ayad A. 622 Ali, Jafar A. 147 Almahdawi, Faleh H. 622 Almahdawi, Faleh H. M. 607 Almomen, Ahmed 622 Alsofi, Abdulkareem 248, 298 B Bagadi, Yousif Eltahir Ban, Li 404 Bi, Jian 427
607
C Cai, Meng 281, 404 Chang, Jin-yu 200 Chang, Peng-Xu 530 Chang, Xin 545 Chen, Bing 427 Chen, Guo-zhu 477 Chen, Jia-yu 200 Chen, Jun-bin 333 Chen, Shen-gen 14 Chen, Shi-tang 545 Chen, Wenyi 1 Chen, Xiu-hong 404 Chen, Yu-Ping 530 Cheng, Lei-ming 14, 287 Cui, Ming-yue 545 D Da, Chang 248 Deng, Hu 73 Deng, Ze-Kun 530 Deng, Zheng-qiang 521 Ding, Xue-yin 215 Dong, Chen-xi 392, 509
Dong, Yi-long 281 Dou, Xiurong 1 Du, Jin-ling 206 Du, Zheng-xue 308 Duan, Jun-rui 90 E El Daly, Salma Osama Taha Taha 106 Eyvazov, Jabrayil 133, 141 F Fan, Ke-ming 268 Fan, Li-hong 261 Feng, Chao 206 G Gan, Qing-Ming 530 Gao, Hui-ying 383 Gao, Min 96 Geng, Xiao-yan 261 Guliyev, Urfan 133, 141 Guliyeva, Mehri 133, 141 Guo, Jing 530 Guo, Jin-rui 155 Guo, Jin-tang 366 H Han, Hai-ying 96 Han, Jin-xin 186 Han, Ming 248, 298 Han, Xiong 73 Han, Yi-feng 487 He, Ju-tao 441 He, Qiu-yun 73 He, Si-yuan 509 Hong-Yan, Zhao 555 Hou, Jian 298 Hou, Lei 509 Hu, Bao-wen 487 Hu, Gui 308, 545
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 J. Lin (Ed.): IPPTC 2022, Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference, pp. 643–645, 2023. https://doi.org/10.1007/978-981-99-2649-7
644
Author Index
Hu, Ji-li 377 Hu, Miao-miao 366 Hu, Tao-yong 487 Huang, Hua 412 Huang, Jun-hong 169 Huang, Xue-qin 308, 545 I Ibrahim, Khalaf Osamah Ingenhoff, Jan 567 J Jia, Hengtian 1 Jia, Jiang-fen 377 Jiang, Fan 169 Jiang, Guan-cheng 521 Jiang, Xu 333 Jin, Qi-hu 206 K Kang, Qing-hua 427 Ke, Wang 392 Kong, Li-hong 404 Kou, Yuan-yuan 333 L Li, Bao 215 Li, Fu-li 579 Li, Hui 321 Li, Jian 261 Li, Jian-min 287 Li, Jian-qi 383 Li, Ming 567 Li, Na 206 Li, Qing-song 268 Li, Xue-ying 412 Li, Yan 39 Li, Yan-rong 60 Li, Yun-bo 261 Li, Zhi-lin 73 Liang, Huan 347 Liao, Xin-wei 27 Lin, He 206 Liu, Chong-jiang 281 Liu, De-fang 200 Liu, Jian 261 Liu, Jing 90 Liu, Ming 366 Liu, Shang-qi 261
591
Liu, Wen 567 Liu, Wen-jun 567 Liu, Wen-xin 333 Liu, Xin-liang 567 Liu, Xue-qi 261 Liu, Yang 261, 567 Liu, Zi-ping 215 Long, Chang-jun 377 Luo, Lan 200 Lv, Ming 287 M Ma, Jun-xiu 14 Ma, Li 39 Ma, Tian-qi 321, 392, 509 Ma, Zhen-peng 321, 392 Ma, Zhong-zhen 261 Malek, Nada Ahmed Abbas Ahmed 120 Mao, Weimin 1 Meng, Hao-jie 347 Miswan, Mohd Azraai 120 Mukhta, Yasir M. F. 120 Mukhtar, Yasir 106 Mukhtar, Yasir M. F. 458, 567, 591, 607, 622 N Na, Wei-hong 39 Nie, Zhen 308 Ning, Meng-meng 412 O Oloruntoba, Adefarati 458 Omer, Altyeb Ali Abaker 567 P Peng, Dong 555 Pang, Dong-xiao 73 Peng, Liexin 1 Q Qi, Mei 261, 521 Qiu, Jie 60 Qiu, Lin-hao 477 R Ran, Jing 155 Ren, Guo-qi 441 Ren, Tao 487
Author Index
S Saadi, Ali 622 Sai, Yun-xiu 477 Shao, Guan-ming 96 Shao, Lei 96 Sheng, Limin 1 Sheng, Shan-bo 215 Si, Qi-fan 412 Song, Xing-liang 281 Sun, Chen 333 Sun, Xiao-wei 96
T Tairab, Alaeldin M. 591 Tang, Jinshu 215 Tang, Kang 27 Tao, Ye 545 Tian, Jian-chao 377 Tian, Na-xin 155
W Wang, Ben 39 Wang, Chun-peng 308 Wang, Gao-feng 441 Wang, Heng-yang 82 Wang, Jian-zhong 228 Wang, Kai 90 Wang, Li 268 Wang, Qing-guo 268 Wang, Xiang-zeng 427 Wang, Xian-jun 268 Wang, Xiao-chen 27 Wang, Xi-cheng 441 Wang, Ying 248 Wang, Yong-chang 268 Wang, Yu 477 Wang, Zhichao 347 Wang, Zhi-rui 281 We, Mei-ji 60 Wei, Bo-yao 287 Wu, Jin-jun 90 Wu, Yi-fang 39
645
X Xiang, Yuan-kai 14, 287 Xiao, Feng-feng 521 Xiao-Yan, Wang 555 Xie, Xian-tao 521 Xin-Wei, Liao 555 Xu, Gang 206 Xu, Li-kun 261 Xu, Min 60 Xu, Qing-fa 228 Xu, Xiao-yu 281 Xu, Zheng-dong 377 Y Yan, Ju 169 Yan, Ping 200 Yang, Quan-zhi 357 Yang, Shu 545 Yang, Tian-qi 509 Yang, Zhi-gang 321, 392 Yao-Zhou, 50 Ye, Xiao-chuang 60 Yin, Weili 347 Yu, Dezhou 1 Z Zhang, Chao-qian 261 Zhang, Fu-tian 215 Zhang, Jiayi 347 Zhang, Jin-yuan 333 Zhang, Ke-xin 261 Zhang, Peng 60 Zhang, Ren-jie 90 Zhang, Rui 60 Zhang, Xiao-chuan 404 Zhang, Yong-min 458 Zhao, Tao 347 Zhong, Wei-xiang 215 Zhong, Xin-xin 39 Zhou, Lihao 347 Zhou, Rui 155 Zhou, Yu-bing 261 Zhou, Zhi-Ping 530 Zhu, Shi-jia 261 Zhu, Ye-sen 487