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El. knyga: Shale Gas and Tight Oil Reservoir Simulation

(Professor, Hildebrand Department of Petroleum an), (Chief Technology Officer, Sim Tech LLC, Houston, Texas, USA
Research Associate, Hildebrand Department of Petroleum and Geosystems Engineering, University of Texas at Austin, TX, USA)
  • Formatas: EPUB+DRM
  • Išleidimo metai: 29-Jul-2018
  • Leidėjas: Gulf Professional Publishing
  • Kalba: eng
  • ISBN-13: 9780128138694
Kitos knygos pagal šią temą:
Shale Gas and Tight Oil Reservoir SimulationDidesnis paveikslėlis
  • Formatas: EPUB+DRM
  • Išleidimo metai: 29-Jul-2018
  • Leidėjas: Gulf Professional Publishing
  • Kalba: eng
  • ISBN-13: 9780128138694
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Shale Gas and Tight Oil Reservoir Simulation delivers the latest research and applications used to better manage and interpret simulating production from shale gas and tight oil reservoirs. Starting with basic fundamentals, the book then includes real field data that will not only generate reliable reserve estimation, but also predict the effective range of reservoir and fracture properties through multiple history matching solutions. Also included are new insights into the numerical modelling of CO2 injection for enhanced oil recovery in tight oil reservoirs. This information is critical for a better understanding of the impacts of key reservoir properties and complex fractures.

  • Models the well performance of shale gas and tight oil reservoirs with complex fracture geometries
  • Teaches how to perform sensitivity studies, history matching, production forecasts, and economic optimization for shale-gas and tight-oil reservoirs
  • Helps readers investigate data mining techniques, including the introduction of nonparametric smoothing models
Preface xiii
1 Introduction of Shale Gas and Tight Oil Reservoirs
1(10)
1.1 Introduction
1(10)
References
9(2)
2 Numerical Model for Shale Gas and Tight Oil Simulation
11(60)
2.1 Introduction
11(3)
2.2 Non-Darcy Flow Effect
14(3)
2.3 Gas Desorption Effect
17(7)
2.3.1 Langmuir Isotherm
17(2)
2.3.2 Comparison of Black-Oil Model and Compositional Model
19(1)
2.3.3 Evaluation of Gas Desorption Effect for Five Shale Formations
19(5)
2.4 Geomechanics Effect
24(12)
2.4.1 Pressure-Dependent Fracture Conductivity
24(1)
2.4.2 Geomechanics Modeling
24(1)
2.4.3 Sensitivity Study Based on a Field Well From Barnett Shale
25(11)
2.5 History Matching With Gas Desorption and Geomechanics Effects
36(5)
2.5.1 Barnett Shale
36(1)
2.5.2 Marcellus Shale
37(4)
2.6 Uncertain Hydraulic Fractures Pattern
41(7)
2.6.1 Base Case
41(3)
2.6.2 Sensitivity Study
44(4)
2.7 Uneven Proppant Distribution
48(4)
2.7.1 Base Case
49(3)
2.7.2 Sensitivity Study
52(1)
2.8 Comparison Biwing Fracture Model With Fracture Network Model
52(3)
2.9 Multiple Horizontal Wells Modeling
55(3)
2.10 Reservoir Simulation for Tight Oil Reservoirs
58(13)
2.10.1 Effect of Fracture Conductivity
60(1)
2.10.2 Effect of Geomechanics
60(3)
2.10.3 Effect of Fracture Network
63(5)
References
68(3)
3 Semianalytical Model for Shale Gas and Tight Oil Simulation
71(58)
3.1 Introduction
71(4)
3.2 Model Assumption and Fracture Discretization
75(1)
3.3 Model Development for Shale Gas Simulation
75(18)
3.3.1 Continuity Equation for Conventional Gas Reservoirs
76(2)
3.3.2 Continuity Equation for Shale Gas Reservoirs
78(9)
3.3.3 Gas Flow From Fractures to Wellbore
87(2)
3.3.4 Fracture Width and Fracture Permeability Calculations
89(1)
3.3.5 Pressure-Dependent Fracture Conductivity
90(1)
3.3.6 Real Gas Properties
91(2)
3.4 Model Development for Tight Oil Simulation
93(1)
3.5 Semianalytical Model Unknowns and Governing Equations
93(3)
3.6 Semianalytical Model Solution
96(1)
3.7 Semianalytical Model Verification
96(10)
3.7.1 Shale Gas Reservoirs
97(6)
3.7.2 Tight Oil Reservoirs
103(3)
3.8 Shale Gas Simulation
106(9)
3.8.1 Synthetic Case Study
106(4)
3.8.2 Field Case Study
110(5)
3.9 Tight Oil Simulation
115(14)
3.9.1 Two Fractures With Different Fracture Geometries
115(3)
3.9.2 Well Interference Through Complex Fracture Hits
118(4)
References
122(7)
4 Modeling Gas Adsorption in Marcellus Shale Using Langmuir and BET Isotherms
129(26)
4.1 Introduction
129(2)
4.2 Adsorption Model for Shale Gas Reservoirs
131(3)
4.3 Gas Flow Model in Shale
134(3)
4.4 Methane Adsorption Measurements in Marcellus Shale
137(3)
4.5 Comparison of Free Gas and Adsorbed Gas
140(1)
4.6 Calculation of Original Gas in Place
140(4)
4.7 Numerical Simulation Methods
144(4)
4.8 Summary
148(7)
References
152(3)
5 Embedded Discrete Fracture Model (EDFM) for Complex Fracture Geometry
155(52)
5.1 Introduction
155(4)
5.2 Numerical Model for Shale Gas Two-Phase Flow
159(5)
5.2.1 Gas Desorption Effect
160(1)
5.2.2 Adsorbed Gas Porosity
161(1)
5.2.3 Gas Slippage and Diffusion Effect
162(1)
5.2.4 Non-Darcy Flow Effect
163(1)
5.2.5 Pressure-Dependent Matrix Permeability
163(1)
5.2.6 Pressure-Dependent Fracture Permeability
164(1)
5.3 Numerical Model for Tight-Oil Three-Phase Flow
164(2)
5.4 Embedded Discrete Fracture Model
166(2)
5.5 Model Verification
168(7)
5.5.1 Shale Gas Simulation
168(3)
5.5.2 Tight-Oil Simulation
171(4)
5.6 Case Studies for Well Performance in Shale Gas Reservoirs
175(10)
5.6.1 Complex Gas Transport Mechanisms
175(2)
5.6.2 Complex Natural Fracture Geometry
177(2)
5.6.3 Complex Hydraulic Fracture Geometry
179(6)
5.7 Case Studies for Well Interference in Tight-Oil Reservoirs
185(3)
5.8 Sensitivity Analysis
188(5)
5.8.1 Effect of Connecting Fracture Conductivity
188(1)
5.8.2 Effect of Number of Connecting Hydraulic Fractures
188(2)
5.8.3 Effect of Number of Natural Fractures
190(3)
5.9 Well Shut-in Test Simulation
193(1)
5.10 Well Spacing Effects
194(4)
5.10.1 All Wells Open
194(1)
5.10.2 Production With Some Wells Shut-in
195(3)
5.11 Discussion About Well Interference
198(9)
References
200(7)
6 An Integrated Framework for Sensitivity Analysis and Economic Optimization in Shale Reservoirs
207(70)
6.1 Introduction
207(1)
6.2 Design of Experiment
208(1)
6.3 Response Surface Methodology
209(1)
6.4 Economic Model
210(1)
6.5 Integrated Reservoir Simulation Framework
210(2)
6.5.1 Reservoir Modeling Including Multiple Fractures
210(1)
6.5.2 Sensitivity Study and Economic Optimization
211(1)
6.6 Integrated Simulation Platform for Unconventional Reservoirs
212(4)
6.6.1 Integration of Reservoir Simulators
213(1)
6.6.2 Base Case
214(1)
6.6.3 Multiple Cases
214(1)
6.6.4 Simulation Running Mode
214(1)
6.6.5 Postprocessing
215(1)
6.6.6 Flowchart for Sensitivity Study and Economic Optimization
215(1)
6.7 Application of Framework in Marcellus Shale Gas Reservoirs
216(29)
6.7.1 Sensitivity Study
218(7)
6.7.2 History Matching and Production Forecasting
225(4)
6.7.3 Fracture Treatment Cost
229(9)
6.7.4 Economic Optimization
238(7)
6.8 Application of Framework in Bakken Tight Oil Reservoirs
245(32)
6.8.1 Numerical Modeling for Tight Oil Reservoirs
248(5)
6.8.2 Sensitivity Study
253(7)
6.8.3 History Matching and Production Forecasting
260(3)
6.8.4 Economic Optimization of Multiple Well Placement
263(10)
References
273(4)
7 An Assisted History-Matching Workflow Using a Proxy-Based Approach for Shale Reservoirs
277(56)
7.1 Introduction
277(3)
7.2 Methodology
280(1)
7.3 An Assisted History-Matching Workflow
281(10)
7.3.1 Workflow With MC Sampling Algorithm
284(6)
7.3.2 Workflow With MCMC Sampling Algorithm
290(1)
7.4 Field Application in Marcellus Shale Gas Reservoir
291(21)
7.4.1 Basic Reservoir Model
292(2)
7.4.2 Parameter Identification and Screening
294(1)
7.4.3 Two-Level Full Factorial Design
295(1)
7.4.4 History-Matching Results From Iterative Proxy Model
295(13)
7.4.5 History-Matching Results From Direct MCMC Method
308(3)
7.4.6 Discussions About Overfitting Issue
311(1)
7.5 Field Application in Bakken Tight Oil Reservoir
312(21)
7.5.1 Reservoir Model
313(2)
7.5.2 Parameter Identification and Screening
315(6)
7.5.3 History Matching and Probabilistic Forecasting
321(9)
References
330(3)
8 CO2 Injection for Enhanced Oil Recovery in Tight Oil Reservoirs
333(44)
8.1 Introduction
333(3)
8.2 Methodology
336(3)
8.2.1 Reservoir Simulation Model
336(2)
8.2.2 Reservoir Model Including Multiple Hydraulic Fractures
338(1)
8.3 Fluid Characterization of Bakken
339(1)
8.4 Simulation of CO2 Huff-n-Puff
339(11)
8.4.1 Base Case
339(7)
8.4.2 Effect of CO2 Diffusion Coefficient
346(1)
8.4.3 Effect of Number of Cycle
346(1)
8.4.4 Effect of Fracture Half-Length
346(2)
8.4.5 Effect of Reservoir Permeability
348(1)
8.4.6 Effect of Reservoir Heterogeneity
348(2)
8.5 Comparison of CO2 Huff-n-Puff and CO2 Flooding
350(12)
8.6 Impacts of Complex Fracture Geometries Using EDFM
362(15)
References
374(3)
9 Phase Behavior Modeling by Considering Nanopore Confinement
377(32)
9.1 Introduction
377(3)
9.2 Methodology
380(5)
9.2.1 Phase Equilibrium Calculation Considering Nanopore Confinement
380(4)
9.2.2 Black-Oil Properties Calculation
384(1)
9.3 Validation for Phase Equilibrium Calculation
385(2)
9.3.1 K-Values for Bulk Fluid
385(1)
9.3.2 Binary Mixture of CO2/C10
386(1)
9.3.3 Binary Mixture of C1/C6
386(1)
9.4 Effect of Nanopores on Phase Behavior of Bakken Shale Oil
387(1)
9.5 Effect of Nanopores on Phase Behavior of Eagle Ford Shale Oil
387(2)
9.6 Case Studies
389(20)
9.6.1 Middle Bakken Shale Oil
389(8)
9.6.2 Eagle Ford Shale Oil
397(8)
References
405(4)
Index 409
Dr. Wei Yu is the chief technology officer for Sim Tech LLC and a research associate in the Hildebrand Department of Petroleum and Geosystems Engineering at The University of Texas at Austin. He is an Associate Editor for the SPE Journal and the Journal of Petroleum Science and Engineering. His research interests include EDFM (Embedded Discrete Fracture Model) technology for modeling any complex fractures, shale gas and tight oil reservoir simulation, EDFM-AI for automatic history matching and complex fracture characterization. Yu has authored or coauthored more than 200 technical papers and two books (Shale Gas and Tight Oil Reservoir Simulation and Embedded Discrete Fracture Modeling and Application in Reservoir Simulation), and holds five patents. He holds a PhD degree in petroleum engineering from The University of Texas at Austin. Dr. Kamy Sepehrnoori is a professor in the Hildebrand Department of Petroleum and Geosystems Engineering at The University of Texas at Austin, where he holds the Texaco Centennial Chair in Petroleum Engineering. His research interest and teaching include computational methods, reservoir simulation, simulation of unconventional reservoirs, enhanced oil recovery modeling, flow assurance modeling, naturally fractured reservoirs, high-performance computing, and CO2 sequestration. He has been teaching at The University of Texas for over 35 years and has graduated more than 230 MS and PhD students under his supervision working mainly in the areas of reservoir simulation and enhanced oil recovery modeling. For the last several years, he has been supervising a research group in simulation of unconventional reservoirs (shale gas and tight oil reservoirs). Sepehrnooris research team along with his colleagues have been in charge of development of several compositional reservoir simulators (i.e., UTCOMPRS, UTCHEMRS, and UTGEL). Also, more recently, he supervised the development of a software package for embedded discrete fracture modeling for application in naturally and hydraulically fractured reservoirs. He has published more than 650 articles in journals and conference proceedings in his research areas. He has also coauthored three books, which have been published by Elsevier. Sepehrnoori is the director of the Reservoir Simulation Joint Industry Project in the Center for Subsurface Energy and the Environment. He holds a PhD degree in petroleum engineering from The University of Texas at Austin.
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