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Book Cover
E-book
Author Deutsch, Clayton V

Title Geostatistical reservoir modeling / Clayton Deutsch, Michael Pyrcz
Edition 2nd edition
Published Oxford : Oxford University Press, [2014]

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Description 1 online resource
Contents Machine generated contents note: 1. Introduction -- 1.1. Comments on Second Edition -- 1.2. Plan for the Book -- 1.3. Key Concepts -- 1.4. Motivation for Reservoir Models -- 1.5. Data for Reservoir Modeling -- 1.6. The Common Work Flow -- 1.7. An Introductory Example -- 1.8. Work Flow Diagrams -- 2. Modeling Principles -- 2.1. Preliminary Geological Modeling Concepts -- 2.1.1. The Story -- 2.1.2. Geological Models -- 2.1.3. Geological Model Overview -- 2.1.4. Basin Formation and Filling -- 2.1.5. Reservoir Architecture -- 2.1.6. Example Stories and Reservoir Modeling Significance -- 2.1.7. Section Summary -- 2.2. Preliminary Statistical Concepts -- 2.2.1. Geological Populations and Stationarity -- 2.2.2. Notation and Definitions -- 2.2.3. Bivariate Distributions -- 2.2.4. Q -- Q Plots and Data Transformation -- 2.2.5. Data Transformation -- 2.2.6. Declustering and Debiasing
2.2.7. Histogram and Cross-Plot Smoothing -- 2.2.8. Monte Carlo Simulation -- 2.2.9. Parameter Uncertainty -- 2.2.10. Bayesian Statistics -- 2.2.11. Work Flow -- 2.2.12. Section Summary -- 2.3. Quantifying Spatial Correlation -- 2.3.1. The Random Function Concept -- 2.3.2. Calculating Experimental Variograms -- 2.3.3. Interpreting Experimental Variograms -- 2.3.4. Horizontal Variograms -- 2.3.5. Variogram Modeling -- 2.3.6. Cross Variograms -- 2.3.7. Multiple-Point Statistics -- 2.3.8. Volume Variance Relations -- 2.3.9. Work Flow -- 2.3.10. Section Summary -- 2.4. Preliminary Mapping Concepts -- 2.4.1. Kriging and Cokriging -- 2.4.2. Sequential Gaussian Simulation -- 2.4.3. Indicator Formalism -- 2.4.4. P-Field Methods -- 2.4.5. Multiple-Point Simulation -- 2.4.6. Object-Based Simulation -- 2.4.7. Optimization Algorithms for Modeling -- 2.4.8. Accounting for Trends -- 2.4.9. Alternatives for Secondary Data Integration
2.4.10. Work Flow -- 2.4.11. Section Summary -- 3. Modeling Prerequisites -- 3.1. Data Inventory -- 3.1.1. Data Events -- 3.1.2. Well Data -- 3.1.3. Seismic Data -- 3.1.4. Dynamic Data -- 3.1.5. Analog Data -- 3.1.6. Data Considerations -- 3.1.7. Section Summary -- 3.2. Conceptual Model -- 3.2.1. Conceptual Geological Model -- 3.2.2. Model Framework -- 3.2.3. Modeling Method Choice -- 3.2.4. Statistical Inputs and Geological Rules -- 3.2.5. Work Flow -- 3.2.6. Section Summary -- 3.3. Problem Formulation -- 3.3.1. Goal and Purpose Definition -- 3.3.2. Modeling Work Constraints -- 3.3.3. Synthetic Paleo-basin -- 3.3.4. Modeling Work Flows -- 3.3.5. Reporting and Documentation -- 3.3.6. Work Flow -- 3.3.7. Section Summary -- 4. Modeling Methods -- 4.1. Large-Scale Modeling -- 4.1.1. Structure and Bounding Surfaces -- 4.1.2. Identification of Regions -- 4.1.3. Trend Model Construction -- 4.1.4. Multivariate Mapping
4.1.5. Summarization and Visualization -- 4.1.6. Section Summary -- 4.2. Variogram-Based Facies Modeling -- 4.2.1. Comments on Facies Modeling -- 4.2.2. Sequential Indicator Simulation -- 4.2.3. Truncated Gaussian Simulation -- 4.2.4. Cleaning Cell-Based Facies Realizations -- 4.2.5. Work Flow -- 4.2.6. Section Summary -- 4.3. Multiple-Point Facies Modeling -- 4.3.1. Multiple-Point Simulation -- 4.3.2. Sequential Simulation with MPS -- 4.3.3. Input Statistics -- 4.3.4. Implementation Details -- 4.3.5. Work Flow -- 4.3.6. Section Summary -- 4.4. Object-Based Facies Modeling -- 4.4.1. Background -- 4.4.2. Stochastic Shales -- 4.4.3. Fluvial Modeling -- 4.4.4. Nonfluvial Depositional Systems -- 4.4.5. Work Flow -- 4.4.6. Section Summary -- 4.5. Process-Mimicking Facies Modeling -- 4.5.1. Background -- 4.5.2. Process-Mimicking Modeling -- 4.5.3. Work Flow -- 4.5.4. Section Summary -- 4.6. Porosity and Permeability Modeling
4.6.1. Background -- 4.6.2. Gaussian Techniques for Porosity -- 4.6.3. Seismic Data in SGS for Porosity -- 4.6.4. Porosity/Permeability Transforms -- 4.6.5. Gaussian Techniques for Permeability -- 4.6.6. Indicator Technique for Permeability -- 4.6.7. Work Flow -- 4.6.8. Section Summary -- 4.7. Optimization for Model Construction -- 4.7.1. Background -- 4.7.2. Simulated Annealing -- 4.7.3. Perturbation Mechanism -- 4.7.4. Update Objective Function -- 4.7.5. Decision Rule -- 4.7.6. Problem Areas -- 4.7.7. Other Methods -- 4.7.8. Work Flow -- 4.7.9. Section Summary -- 5. Model Applications -- 5.1. Model Checking -- 5.1.1. Background -- 5.1.2. Minimum Acceptance Checks -- 5.1.3. High-Order Checks -- 5.1.4. Cross Validation and the Jackknife -- 5.1.5. Checking Distributions of Uncertainty -- 5.1.6. Work Flow -- 5.1.7. Section Summary -- 5.2. Model Post-processing -- 5.2.1. Background -- 5.2.2. Model Modification
5.2.3. Model Scaling -- 5.2.4. Pointwise Summary Models -- 5.2.5. Joint Summary Models -- 5.2.6. Work Flow -- 5.2.7. Section Summary -- 5.3. Uncertainty Management -- 5.3.1. Background -- 5.3.2. Uncertainty Considerations -- 5.3.3. How Many Realizations? -- 5.3.4. Summarizing Uncertainty -- 5.3.5. Uncertainty Versus Well Spacing -- 5.3.6. Case for Geometric Criteria -- 5.3.7. Ranking Realizations -- 5.3.8. Decision Making with Uncertainty -- 5.3.9. Work Flow -- 5.3.10. Section Summary -- 6. Special Topics -- 6.1. Unstructured Grids -- 6.2. Continuous Variable Heterogeneity -- 6.3. More Estimation Methods -- 6.4. Spectral Methods -- 6.5. Surface-Based Modeling -- 6.6. Ensemble Kalman Filtering -- 6.7. Advanced Geological Characterization -- 6.8. Other Emerging Techniques -- 6.9. Final Thoughts -- A. Glossary and Notation -- A.1. Glossary -- A.2. Notation
Bibliography Includes bibliographical references and index
Notes Print version record
Subject Hydrocarbon reservoirs -- Mathematical models
Petroleum -- Geology -- Statistical methods
NATURE -- Natural Resources.
NATURE -- Rocks & Minerals.
Hydrocarbon reservoirs -- Mathematical models
Petroleum -- Geology -- Statistical methods
Form Electronic book
Author Pyrcz, Michael
ISBN 9780199358830
0199358834