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For Authors
Submit a ProposalAdvanced Petroleum Reservoir Simulation
 | By M. Rafiqul Islam, S.H. Moussavizadegan, S. Mustafiz, and J.H. Abou-Kassem Copyright: 2010 | Expected Pub Date:March 2010// ISBN: 9780470625811 | Hardcover | 1 lb 486 pages | 159 illustrations Price: $225 216 USD  |
One Line Description
The most up-to-date practices, processes, and technologies for petroleum reservoir simulation.
Audience
Petroleum, drilling, and reservoir engineers, production engineers and geologists
Petroleum, drilling, and reservoir engineers, production engineers and geologists
Description
Petroleum forms in underground reservoirs, whether on land or offshore, and it is the job of the reservoir engineer, geologist, or petroleum engineer to figure out the best method for the drilling engineers to get the crude oil out of the ground in the most efficient way possible. Until reservoir simulation software came along, in the last several decades, the only way to do this was to drill multiple test wells where it was thought there was oil or gas and hope to hit the reservoir.
Now, simulation software is widely available, and, though simulation is much more accurate than it used to be, it is still a very difficult technology to master and navigate, and software packages are all different, with different shades of accuracy.
This book helps the engineer or geologist use the right engineering equations and scientific methods to cut down on mistakes and boost the accuracy of simulations. The authors clarify the underlying mathematics and physics behind reservoir simulation and makes it easy to have a range of simulation results along with their respective probability. This makes the risk analysis based on knowledge rather than guess work.
This new treatment on reservoir simulation is by far the strongest tool for engineers and managers to back up reservoir simulation predictions with real science, adding transparency and ease to the process of reservoir simulation in way never witnessed before. Finally, No other book provided readers complete access to the 3D, 3-phase reservoir simulation code, available for download from www.scrivenerpublishing.com.
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Back to TopPetroleum forms in underground reservoirs, whether on land or offshore, and it is the job of the reservoir engineer, geologist, or petroleum engineer to figure out the best method for the drilling engineers to get the crude oil out of the ground in the most efficient way possible. Until reservoir simulation software came along, in the last several decades, the only way to do this was to drill multiple test wells where it was thought there was oil or gas and hope to hit the reservoir.
Now, simulation software is widely available, and, though simulation is much more accurate than it used to be, it is still a very difficult technology to master and navigate, and software packages are all different, with different shades of accuracy.
This book helps the engineer or geologist use the right engineering equations and scientific methods to cut down on mistakes and boost the accuracy of simulations. The authors clarify the underlying mathematics and physics behind reservoir simulation and makes it easy to have a range of simulation results along with their respective probability. This makes the risk analysis based on knowledge rather than guess work.
This new treatment on reservoir simulation is by far the strongest tool for engineers and managers to back up reservoir simulation predictions with real science, adding transparency and ease to the process of reservoir simulation in way never witnessed before. Finally, No other book provided readers complete access to the 3D, 3-phase reservoir simulation code, available for download from www.scrivenerpublishing.com.
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Author / Editor Details
M. R. Islam is Professor of Petroleum Engineering at the Civil and Resource Engineering Department of Dalhousie University, Canada. He has over 700 publications to his credit, including 6 books. He is on the editorial boards of several scholarly journals, and, in addition to his teaching duties, he is also director of Emertec Research and Development Ltd. and has been on the boards of a number of companies in North America and overseas.
M. R. Islam is Professor of Petroleum Engineering at the Civil and Resource Engineering Department of Dalhousie University, Canada. He has over 700 publications to his credit, including 6 books. He is on the editorial boards of several scholarly journals, and, in addition to his teaching duties, he is also director of Emertec Research and Development Ltd. and has been on the boards of a number of companies in North America and overseas.
Dr. S. Hossein Mousavizadegan is currently on the faculty of marine technology at the Amirkabir University of Technology in Tehran as an assistant professor, specializing in mathematical and numerical modeling of fluid dynamics.
Dr. Shabbir Mustafiz is a research engineer with the Alberta Research Council in Edmonton, Canada. Shabbir has published over 25 journal papers and has a Ph.D. in Civil Engineering, on the topic of petroleum reservoir simulation, from Dalhousie University and he is the current SPE Scholarship Chair for the Edmonton Section.
Jamal H. Abou-Kassem is Professor of Petroleum Engineering at the UAE U. in the United Arab Emirates, where he has taught since 1993. Abou-Kassem is a coauthor of two textbooks on reservoir simulation and an author or coauthor of numerous technical articles in the areas of reservoir simulation and other petroleum and natural gas-related topics.
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Table of Contents
Foreword xiii
Introduction xv
1. Reservoir Simulation Background 1
1.1 Essence of Reservoir Simulation 1
1.2 Assumptions Behind Various Modeling Approaches 5
1.3 Material Balance Equation 5
1.3.1 Decline Curve 6
1.3.2 Statistical Method 6
1.3.3 Analytical Methods 7
1.3.4 Finite Difference Methods 8
1.3.5 Darcy's Law 11
1.4 Recent Advances in Reservoir Simulation 12
1.4.1 Speed and Accuracy 12
1.4.2 New Fluid Flow Equations 13
1.4.3 Coupled Fluid Flow and Geo-mechanical
Stress Model 16
1.4.4 Fluid Flow Modeling Under Thermal Stress 17
1.5 Future Challenges in Reservoir Simulation 18
1.5.1 Experimental Challenges 18
1.5.2 Numerical Challenges 20
1.5.2.1 Theory of Onset and Propagation of
Fractures Due to Thermal Stress 20
1.5.2.2 2-D and 3-D Solutions of the Governing
Equations 20
1.5.2.3 Viscous Fingering During Miscible
Displacement 20
1.5.2.4 Improvement in Remote Sensing
and Monitoring Ability 21
v
Contents vi
1.5.2.5 Improvement in Data Processing
Techniques 21
1.5.3 Remote Sensing and Real-time
Monitoring 22
1.5.3.1 Monitoring Offshore Structures 23
1.5.3.2 Development of a Dynamic
Characterization Tool (Based on
Seismic-while-drilling Data) 24
1.5.3.3 Use of 3-D Sonogram 24
1.5.3.4 Virtual Reality (VR) Applications 25
1.5.3.5 Intelligent Reservoir Management 26
1.6 Economic Models Based on Futuristic
Energy Pricing Policies 27
1.7 Integrated System of Monitoring, Environmental
Impact and Economics 29
2. Reservoir Simulator-input/output 31
2.1 Input and Output Data 32
2.2 Geological and Geophysical Modeling 34
2.3 Reservoir Characterization 37
2.3.1 Representative Elementary Volume, REV 38
2.3.2 Fluid and Rock Properties 41
2.3.2.1 Fluid Properties 42
2.3.2.1.1 Crude Oil Properties 43
2.3.2.1.2 Natural Gas Properties 45
2.3.2.1.3 Water Content Properties 46
2.3.3 Rock Properties 47
2.4 Upscaling 52
2.4.1 Power Law Averaging Method 53
2.4.2 Pressure-solver Method 54
2.4.3 Renormalization Technique 56
2.4.4 Multiphase Flow Upscaling 57
2.5 Pressure/Production data 60
2.5.1 Phase Saturations Distribution 61
2.6 Reservoir Simulator Output 62
2.7 History-matching 65
2.7.1 History-matching Formulation 68
2.7.2 Uncertainty Analysis 71
vii Contents
2.7.2.1 Measurement Uncertainty 71
2.7.2.2 Upscaling Uncertainty 74
2.7.2.3 Model Error 75
2.7.2.4 The Prediction Uncertainty 76
2.8 Real-time Monitoring 77
3. Reservoir Simulators: Problems, Shortcomings,
and Some Solution Techniques 83
3.1 Multiple Solutions in Natural Phenomena 85
3.1.1 Knowledge Dimension 88
3.2 Adomian Decomposition 103
3.2.1 Governing Equations 105
3.2.2 Adomian Decomposition of Buckley -- Leverett
Equation 108
3.2.3 Results and Discussions 110
3.3 Some Remarks on Multiple Solutions 113
4. Mathematical Formulation of Reservoir
Simulation Problems 115
4.1 Black Oil Model and Compositional Model 116
4.2 General Purpose Compositional Model 118
4.2.1 Basic Defi nitions 118
4.2.2 Primary and Secondary Parameters and
Model Variables 120
4.2.3 Mass Conservation Equation 123
4.2.4 Energy Balance Equation 126
4.2.5 Volume Balance Equation 132
4.2.6 The Motion Equation in Porous Medium 133
4.2.7 The Compositional System of Equations
and Model Variables 138
4.3 Simplifi cation of the General Compositional
Model 141
4.3.1 The Black Oil Model 141
4.3.2 The Water Oil Model 143
4.4 Some Examples in Application of the
General Compositional Model 146
4.4.1 Isothermal Volatile Oil Reservoir 146
4.4.2 Steam Injection Inside a Dead Oil Reservoir 149
Contents viii
4.4.3 Steam Injection in Presence of Distillation
and Solution Gas 150
5. The Compositional Simulator Using the
Engineering Approach 155
5.1 Finite Control Volume Method 156
5.1.1 Reservoir Discretization in Rectangular
Coordinates 157
5.1.2 Discretization of Governing Equations 158
5.1.2.1 Components Mass Conservation
Equation 159
5.1.2.2 Energy Balance Equation 167
5.1.3 Discretization of Motion Equation 170
5.2 Uniform Temperature Reservoir Compositional
Flow Equations in a 1-D Domain 172
5.3 Compositional Mass Balance Equation in a
Multidimensional Domain 178
5.3.1 Implicit Formulation of Compositional
Model in Multi-Dimensional Domain 180
5.3.2 Reduced Equations of Implicit Compositional
Model in Multidimensional Domain 183
5.3.3 Well Production and Injection Rate Terms 186
5.3.3.1 Production Wells 186
5.3.3.2 Injection Wells 188
5.3.4 Fictitious Well Rate Terms (Treatment
of Boundary Conditions) 189
5.4 Variable Temperature Reservoir Compositional
Flow Equations 193
5.4.1 Energy Balance Equation 193
5.4.2 Implicit Formulation of Variable Temperature
Reservoir Compositional Flow Equations 197
5.5 Solution Method 201
5.5.1 Solution of Model Equations Using
Newton's Iteration 202
5.6 The Effects of Linearization 207
5.6.1 Case I: Single Phase Flow of a
Natural Gas 208
ix Contents
5.6.2 Effect of Interpolation Functions
and Formulation 214
5.6.3 Effect of Time Interval 215
5.6.4 Effect of Permeability 217
5.6.5 Effect of Number of Gridblocks 217
5.6.6 Spatial and Transient Pressure Distribution
Using Different Iinterpolation Functions 219
5.6.7 CPU Time 222
5.6.8 Case II: An Oil/Water Reservoir 224
6. A Comprehensive Material Balance Equation for
Oil Recovery 245
6.1 Background 245
6.2 Permeability Alteration 248
6.3 Porosity Alteration 249
6.4 Pore Volume Change 251
6.5 A Comprehensive MBE with Memory for
Cumulative Oil Recovery 252
6.6 Numerical Simulation 255
6.6.1 Effects of Compressibilities on Dimensionless
Parameters 257
6.6.2 Comparison of Dimensionless Parameters
Based on Compressibility Factor 258
6.6.3 Effects of M on Dimensionless Parameter 259
6.6.4 Effects of Compressibility Factor with
M Values 259
6.6.5 Comparison of Models Based on RF 260
6.6.6 Effects of M on MBE 262
6.7 Appendix 6A: Development of an MBE for a
Compressible Undersaturated Oil Reservoir 264
6.7.1 Development of a New MBE 265
6.7.2 Conventional MBE 272
6.7.3 Signifi cance of Cepm 274
6.7.4 Water Drive Mechanism with
Water Production 275
6.7.5 Depletion Drive Mechanism with
No Water Production 276
Contents x
7. Modeling Viscous Fingering During Miscible
Displacement in a Reservoir 277
7.1 Improvement of the Numerical Scheme 277
7.1.1 The Governing Equation 279
7.1.2 Finite Difference Approximations 281
7.1.2.1 Barakat -- Clark FTD Scheme 281
7.1.2.2 DuFort -- Frankel Scheme 283
7.1.3 Proposed Barakat -- Clark CTD Scheme 284
7.1.3.1 Boundary Conditions 285
7.1.4 Accuracy and Truncation Errors 285
7.1.5 Some Results and Discussion 286
7.1.6 Infl uence of Boundary Conditions 293
7.2 Application of the New Numerical Scheme to
Viscous Fingering 295
7.2.1 Stability Criterion and Onset of Fingering 295
7.2.2 Base Stable Case 296
7.2.3 Base Unstable Case 302
7.2.4 Parametric Study 309
7.2.4.1 Effect of Injection Pressure 309
7.2.4.2 Effect of Overall Porosity 314
7.2.4.3 Effect of Mobility Ratio 317
7.2.4.4 Effect of Longitudinal Dispersion 320
7.2.4.5 Effect of Transverse Dispersion 324
7.2.4.6 Effect of Aspect Ratio 327
7.2.5 Comparison of Numerical Modeling Results
with Experimental Results 330
7.2.5.1 Selected Experimental Model 330
7.2.5.2 Physical Model Parameters 331
7.2.5.3 Comparative Study 332
7.2.5.4 Concluding Remarks 336
8. Towards Modeling Knowledge and Sustainable
Petroleum Production 339
8.1 Essence of Knowledge, Science, and Emulation 339
8.1.1 Simulation vs. Emulation 340
8.1.2 Importance of the First Premise and Scientifi c
Pathway 342
8.1.3 Mathematical Requirements of Nature Science 344
8.1.4 The Meaningful Addition 348
xi Contents
8.1.5 Natural -- Numbers and the Mathematical
Content of Nature 350
8.2 The Knowledge Dimension 354
8.2.1 The Importance of Time as the Fourth
Dimension 354
8.2.2 Towards Modeling Truth and Knowledge 362
8.3 Examples of Linearization and Linear Thinking 363
8.4 The Single-Parameter Criterion 365
Back to Top
Foreword xiii
Introduction xv
1. Reservoir Simulation Background 1
1.1 Essence of Reservoir Simulation 1
1.2 Assumptions Behind Various Modeling Approaches 5
1.3 Material Balance Equation 5
1.3.1 Decline Curve 6
1.3.2 Statistical Method 6
1.3.3 Analytical Methods 7
1.3.4 Finite Difference Methods 8
1.3.5 Darcy's Law 11
1.4 Recent Advances in Reservoir Simulation 12
1.4.1 Speed and Accuracy 12
1.4.2 New Fluid Flow Equations 13
1.4.3 Coupled Fluid Flow and Geo-mechanical
Stress Model 16
1.4.4 Fluid Flow Modeling Under Thermal Stress 17
1.5 Future Challenges in Reservoir Simulation 18
1.5.1 Experimental Challenges 18
1.5.2 Numerical Challenges 20
1.5.2.1 Theory of Onset and Propagation of
Fractures Due to Thermal Stress 20
1.5.2.2 2-D and 3-D Solutions of the Governing
Equations 20
1.5.2.3 Viscous Fingering During Miscible
Displacement 20
1.5.2.4 Improvement in Remote Sensing
and Monitoring Ability 21
v
Contents vi
1.5.2.5 Improvement in Data Processing
Techniques 21
1.5.3 Remote Sensing and Real-time
Monitoring 22
1.5.3.1 Monitoring Offshore Structures 23
1.5.3.2 Development of a Dynamic
Characterization Tool (Based on
Seismic-while-drilling Data) 24
1.5.3.3 Use of 3-D Sonogram 24
1.5.3.4 Virtual Reality (VR) Applications 25
1.5.3.5 Intelligent Reservoir Management 26
1.6 Economic Models Based on Futuristic
Energy Pricing Policies 27
1.7 Integrated System of Monitoring, Environmental
Impact and Economics 29
2. Reservoir Simulator-input/output 31
2.1 Input and Output Data 32
2.2 Geological and Geophysical Modeling 34
2.3 Reservoir Characterization 37
2.3.1 Representative Elementary Volume, REV 38
2.3.2 Fluid and Rock Properties 41
2.3.2.1 Fluid Properties 42
2.3.2.1.1 Crude Oil Properties 43
2.3.2.1.2 Natural Gas Properties 45
2.3.2.1.3 Water Content Properties 46
2.3.3 Rock Properties 47
2.4 Upscaling 52
2.4.1 Power Law Averaging Method 53
2.4.2 Pressure-solver Method 54
2.4.3 Renormalization Technique 56
2.4.4 Multiphase Flow Upscaling 57
2.5 Pressure/Production data 60
2.5.1 Phase Saturations Distribution 61
2.6 Reservoir Simulator Output 62
2.7 History-matching 65
2.7.1 History-matching Formulation 68
2.7.2 Uncertainty Analysis 71
vii Contents
2.7.2.1 Measurement Uncertainty 71
2.7.2.2 Upscaling Uncertainty 74
2.7.2.3 Model Error 75
2.7.2.4 The Prediction Uncertainty 76
2.8 Real-time Monitoring 77
3. Reservoir Simulators: Problems, Shortcomings,
and Some Solution Techniques 83
3.1 Multiple Solutions in Natural Phenomena 85
3.1.1 Knowledge Dimension 88
3.2 Adomian Decomposition 103
3.2.1 Governing Equations 105
3.2.2 Adomian Decomposition of Buckley -- Leverett
Equation 108
3.2.3 Results and Discussions 110
3.3 Some Remarks on Multiple Solutions 113
4. Mathematical Formulation of Reservoir
Simulation Problems 115
4.1 Black Oil Model and Compositional Model 116
4.2 General Purpose Compositional Model 118
4.2.1 Basic Defi nitions 118
4.2.2 Primary and Secondary Parameters and
Model Variables 120
4.2.3 Mass Conservation Equation 123
4.2.4 Energy Balance Equation 126
4.2.5 Volume Balance Equation 132
4.2.6 The Motion Equation in Porous Medium 133
4.2.7 The Compositional System of Equations
and Model Variables 138
4.3 Simplifi cation of the General Compositional
Model 141
4.3.1 The Black Oil Model 141
4.3.2 The Water Oil Model 143
4.4 Some Examples in Application of the
General Compositional Model 146
4.4.1 Isothermal Volatile Oil Reservoir 146
4.4.2 Steam Injection Inside a Dead Oil Reservoir 149
Contents viii
4.4.3 Steam Injection in Presence of Distillation
and Solution Gas 150
5. The Compositional Simulator Using the
Engineering Approach 155
5.1 Finite Control Volume Method 156
5.1.1 Reservoir Discretization in Rectangular
Coordinates 157
5.1.2 Discretization of Governing Equations 158
5.1.2.1 Components Mass Conservation
Equation 159
5.1.2.2 Energy Balance Equation 167
5.1.3 Discretization of Motion Equation 170
5.2 Uniform Temperature Reservoir Compositional
Flow Equations in a 1-D Domain 172
5.3 Compositional Mass Balance Equation in a
Multidimensional Domain 178
5.3.1 Implicit Formulation of Compositional
Model in Multi-Dimensional Domain 180
5.3.2 Reduced Equations of Implicit Compositional
Model in Multidimensional Domain 183
5.3.3 Well Production and Injection Rate Terms 186
5.3.3.1 Production Wells 186
5.3.3.2 Injection Wells 188
5.3.4 Fictitious Well Rate Terms (Treatment
of Boundary Conditions) 189
5.4 Variable Temperature Reservoir Compositional
Flow Equations 193
5.4.1 Energy Balance Equation 193
5.4.2 Implicit Formulation of Variable Temperature
Reservoir Compositional Flow Equations 197
5.5 Solution Method 201
5.5.1 Solution of Model Equations Using
Newton's Iteration 202
5.6 The Effects of Linearization 207
5.6.1 Case I: Single Phase Flow of a
Natural Gas 208
ix Contents
5.6.2 Effect of Interpolation Functions
and Formulation 214
5.6.3 Effect of Time Interval 215
5.6.4 Effect of Permeability 217
5.6.5 Effect of Number of Gridblocks 217
5.6.6 Spatial and Transient Pressure Distribution
Using Different Iinterpolation Functions 219
5.6.7 CPU Time 222
5.6.8 Case II: An Oil/Water Reservoir 224
6. A Comprehensive Material Balance Equation for
Oil Recovery 245
6.1 Background 245
6.2 Permeability Alteration 248
6.3 Porosity Alteration 249
6.4 Pore Volume Change 251
6.5 A Comprehensive MBE with Memory for
Cumulative Oil Recovery 252
6.6 Numerical Simulation 255
6.6.1 Effects of Compressibilities on Dimensionless
Parameters 257
6.6.2 Comparison of Dimensionless Parameters
Based on Compressibility Factor 258
6.6.3 Effects of M on Dimensionless Parameter 259
6.6.4 Effects of Compressibility Factor with
M Values 259
6.6.5 Comparison of Models Based on RF 260
6.6.6 Effects of M on MBE 262
6.7 Appendix 6A: Development of an MBE for a
Compressible Undersaturated Oil Reservoir 264
6.7.1 Development of a New MBE 265
6.7.2 Conventional MBE 272
6.7.3 Signifi cance of Cepm 274
6.7.4 Water Drive Mechanism with
Water Production 275
6.7.5 Depletion Drive Mechanism with
No Water Production 276
Contents x
7. Modeling Viscous Fingering During Miscible
Displacement in a Reservoir 277
7.1 Improvement of the Numerical Scheme 277
7.1.1 The Governing Equation 279
7.1.2 Finite Difference Approximations 281
7.1.2.1 Barakat -- Clark FTD Scheme 281
7.1.2.2 DuFort -- Frankel Scheme 283
7.1.3 Proposed Barakat -- Clark CTD Scheme 284
7.1.3.1 Boundary Conditions 285
7.1.4 Accuracy and Truncation Errors 285
7.1.5 Some Results and Discussion 286
7.1.6 Infl uence of Boundary Conditions 293
7.2 Application of the New Numerical Scheme to
Viscous Fingering 295
7.2.1 Stability Criterion and Onset of Fingering 295
7.2.2 Base Stable Case 296
7.2.3 Base Unstable Case 302
7.2.4 Parametric Study 309
7.2.4.1 Effect of Injection Pressure 309
7.2.4.2 Effect of Overall Porosity 314
7.2.4.3 Effect of Mobility Ratio 317
7.2.4.4 Effect of Longitudinal Dispersion 320
7.2.4.5 Effect of Transverse Dispersion 324
7.2.4.6 Effect of Aspect Ratio 327
7.2.5 Comparison of Numerical Modeling Results
with Experimental Results 330
7.2.5.1 Selected Experimental Model 330
7.2.5.2 Physical Model Parameters 331
7.2.5.3 Comparative Study 332
7.2.5.4 Concluding Remarks 336
8. Towards Modeling Knowledge and Sustainable
Petroleum Production 339
8.1 Essence of Knowledge, Science, and Emulation 339
8.1.1 Simulation vs. Emulation 340
8.1.2 Importance of the First Premise and Scientifi c
Pathway 342
8.1.3 Mathematical Requirements of Nature Science 344
8.1.4 The Meaningful Addition 348
xi Contents
8.1.5 Natural -- Numbers and the Mathematical
Content of Nature 350
8.2 The Knowledge Dimension 354
8.2.1 The Importance of Time as the Fourth
Dimension 354
8.2.2 Towards Modeling Truth and Knowledge 362
8.3 Examples of Linearization and Linear Thinking 363
8.4 The Single-Parameter Criterion 365
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BISAC SUBJECT HEADINGS
TEC047000: TECHNOLOGY & ENGINEERING / Petroleum
TEC031031: TECHNOLOGY & ENGINEERING / Power Resources / Fossil Fuels
TEC036000: TECHNOLOGY & ENGINEERING / Remote Sensing and Geographic Information Systems
BIC CODES
THF: Fossil Fuel Technologies
THFP: Petroleum Technology
THFG: Gas Technology
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