Seismic Reservoir Modeling. Dario GranaЧитать онлайн книгу.
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Table of Contents
1 Cover
5 Preface
7 1 Review of Probability and Statistics 1.1 Introduction to Probability and Statistics 1.2 Probability 1.3 Statistics 1.4 Probability Distributions 1.5 Functions of Random Variable 1.6 Inverse Theory 1.7 Bayesian Inversion
8 2 Rock Physics Models 2.1 Rock Physics Relations 2.2 Effective Media 2.3 Critical Porosity Concept 2.4 Granular Media Models 2.5 Inclusion Models 2.6 Gassmann's Equations and Fluid Substitution 2.7 Other Rock Physics Relations 2.8 Application
9 3 Geostatistics for Continuous Properties 3.1 Introduction to Spatial Correlation 3.2 Spatial Correlation Functions 3.3 Spatial Interpolation 3.4 Kriging 3.5 Sequential Simulations 3.6 Other Simulation Methods 3.7 Application
10 4 Geostatistics for Discrete Properties 4.1 Indicator Kriging 4.2 Sequential Indicator Simulation 4.3 Truncated Gaussian Simulation 4.4 Markov Chain Models 4.5 Multiple‐Point Statistics 4.6 Application
11 5 Seismic and Petrophysical Inversion 5.1 Seismic Modeling 5.2 Bayesian Inversion 5.3 Bayesian Linearized AVO Inversion 5.4 Bayesian Rock Physics Inversion 5.5 Uncertainty Propagation 5.6 Geostatistical Inversion 5.7 Other Stochastic Methods
12 6 Seismic Facies Inversion 6.1 Bayesian Classification 6.2 Bayesian Markov Chain Gaussian Mixture Inversion 6.3 Multimodal Markov Chain Monte Carlo Inversion 6.4 Probability Perturbation Method 6.5 Other Stochastic Methods
13 7 Integrated Methods 7.1 Sources of Uncertainty 7.2 Time‐Lapse Seismic Inversion 7.3 Electromagnetic Inversion 7.4 History Matching 7.5 Value of Information
14 8 Case Studies 8.1 Hydrocarbon Reservoir Studies 8.2 CO2 Sequestration Study
15 Appendix: MATLAB Codes A.1 Rock Physics Modeling A.2 Geostatistical Modeling A.3 Inverse Modeling A.4 Facies Modeling
16 References
17 Index
List of Tables
1 Chapter