Geostatistical methods for reservoir geophysics / Leonardo Azevedo, AmÃlcar Soares.
This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers extensive geostatistical background information, including detailed descriptions of the main geostatistical tools traditionally used in Earth related sciences to infer the spatial distributio...
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Full Text (via Springer) |
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| Main Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2017]
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| Series: | Advances in oil and gas exploration & production.
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| Subjects: |
Table of Contents:
- Preface; Contents; List of Abbreviations and MathematicalSymbols; List of Figures; List of Tables; 1 Introduction-Geostatistical Methods for Integrating Seismic Reflection Data into Subsurface Earth Models; 1.1 Spatial Resolution Gap; 1.2 Seismic Inversion; 2 Fundamental Geostatistical Tools for Data Integration; 2.1 Spatial Continuity Patterns Analysis and Modeling; 2.1.1 Bi-point Statistics; 2.1.2 Complex Morphologic Patterns: Auxiliary and Reference Images; 2.1.3 Spatial Random Fields; 2.1.4 Variograms and Spatial Covariances; 2.1.5 Spatial Representativeness of the Variogram.
- 2.1.6 Spatial Continuity for Multivariate Systems2.1.7 Variogram Modeling Workflow; 2.1.8 Theoretical Variogram Models; 2.1.9 Linear Combinations of Variogram Models: Imbricated Structures; 2.1.10 Co-regionalized Models of Multivariate Systems; 2.2 Estimation Models; 2.2.1 Linear Estimation of Local Statistics; 2.2.2 Probabilistic Model of the Geostatistical Linear Estimator; 2.3 Kriging Estimate; 2.3.1 Kriging System Resolution; 2.4 Linear Estimation of Non-stationary Phenomena: Simple Kriging; 2.5 Co-kriging Estimate.
- 2.6 Co-estimation with a Secondary Variable in a Much Denser Sample Grid: Collocated Co-kriging2.7 Estimation of Local Probability Distribution Functions; 2.7.1 Gaussian Transform of the Experimental Data; 2.8 Estimation of Categorical Variables; 3 Simulation Models of Physical Phenomena in Earth Sciences; 3.1 Stochastic Simulation Models; 3.2 Sequential Simulation Models; 3.3 Sequential Gaussian Simulation; 3.4 Direct Sequential Simulation from Experimental Distributions; 3.4.1 Direct Sequential Simulation; 3.4.2 Direct Sequential Co-simulation.
- 3.4.3 Stochastic Sequential Co-simulation with Joint Probability Distributions3.4.4 Stochastic Simulation with Uncertain Data: DSS with Point Probability Distributions; 3.5 Simulation of Categorical Variables; 3.5.1 Indicator Simulation; 3.5.2 Alternative Simulation Methods for Categorical Variables; 3.5.3 High-Order Stochastic Simulation of Categorical Variables; 4 Integration of Geophysical Data for Reservoir Modeling and Characterization; 4.1 Seismic Inversion; 4.2 Bayesian Framework for Integrating Seismic Reflection Data into Subsurface Earth Models.
- 4.3 Iterative Geostatistical Seismic Inversion Methodologies4.3.1 Frequency Domain of Geostatistical Seismic Inversion; 4.3.2 Trace-by-Trace Geostatistical Seismic Inversion Methodologies; 4.3.3 Global Geostatistical Seismic Inversion Methodologies; 4.3.4 Global Geostatistical Acoustic Inversion; 4.3.5 Global Geostatistical Elastic Inversion; 4.3.6 Geostatistical Seismic AVA Inversion; 4.3.7 Application Example with Geostatistical Seismic AVA Inversion; 4.3.8 Seismic Inversion with Structural Local Models.