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E-raamat: Soft Computing and Intelligent Data Analysis in Oil Exploration

Edited by (BISC Program, Electrical Engineering and Computer Sciences Department, University of California, Berkeley, CA, USA), Edited by , Edited by (BISC Program, Electrical Engineering and Computer Sciences Department, University of California, Berkeley, CA, USA)
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This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.



It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.



There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.


This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.



It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.



There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

Arvustused

from:P.H.H. Nelson "...I heartily congratulate them on the outstanding job they have done in putting this book together. ...of great value to all those in the petroleum industry who would advance oil- and gas-finding, and production, into the twenty-first century." --Petroleum Geoscience

Foreword. Preface. About the Editors. List of Contributors. Part
1.
Introduction: Fundamentals of Soft Computing.
1. Soft computing for
intelligent reservoir characterization and modeling (M. Nikravesh, F.
Aminzadeh).
2. Fuzzy logic (G.J.Klir).
3. Introduction to using genetic
algorithms (J.N. Carter).
4. Heuristic approaches to combinatorial
optimazation (V.M. Johnson).
5. Introduction to geostatistics (R.J. Pawar).
6. Geostatistics: From pattern recognition to pattern reproduction (J.
Caers). Part
2. Geophysical Analysis and Interpretation.
7. Mining and fusion
of petroleum date with fuzzy logic and neural network agents (M. Nikravesh,
F.Aminzadeh).
8. Time lapse seismic as a complementary tool for in-fill
drilling (M. Landrø, L.K. Strønen et al.).
9. Improving seismic chimney
detection using directional attributes (K.M. Tingdahl).
10. Modeling a
fluvial reservoir with multipoint statistics and principal components
(P.M.Wong, S.A.R. Shibli). Part
3. Computational Geology.
11. The role of
fuzzy logic in sedimentology and stratigraphic models (R.V. Demicco,
G.J.Klir, R. Belohlavek).
12. Spatial contiguity analysis. A method for
describing spatial structures of seismic data (A. Faraj, F. Cailly).
13.
Litho-seismic data handling for hydrocarbon reservoir estimate: Fuzzy system
modeling approach (E.A. Shyllon).
14. Neural vector quantization for geobody
detection and static multivariate upscaling (A. Chawathé, M. Ye).
15. High
resolution reservoir heterogeneity characterization using recognition
technology (M. Hassibi, I. Ershaghi, F. Aminzadeh).
16. Extending the use of
linguistic petrographical descriptions to characterise core porosity (T.D.
Gedeon, P.M. Wong et al.). Part
4. Reservoir and Production Engineering.
17.
Using genetic algorithms for reservoir characterisation (C. Romero, J.N.
Carter).
18. Applying soft computing methods to improve the computational
tractability of a subsurface simulation-optimization problem (V.M. Johnson,
L.L. Rogers).
19. Neural network prediction of permeability in the El Garia
formation, Ashtart oilfield, offshore Tunisia (J.H. Ligtenberg, A.G.
Wansink).
20. Using RBF network to model the reservoir fluid behavior of
black oil systems (A.M. Elsharkawy).
21. Enhancing gas storage wells
deliverability using intelligent systems (S.D. Mohaghegh). Part
5. Integrated
field studies.
22. Soft computing: Tools for intelligent reservoir
characterization and optimum well placement (M. Nikravesh, R.D. Adams, R.A.
Levey).
23. Combining geological information with seismic and production data
(J. Caers, S. Srinivasan).
24. Interpreting biostratigraphical data using
fuzzy logic: The identification of regional mudstones within the Fleming
field, UK North Sea (M.I. Wakefield, R.J. Cook et al.).
25. Geostatistical
characterization of the Carpinteria field, California (R.J. Pawar, E.B.
Edwards, E.M. Whitney).
26. Integrated fractured reservoir characterization
using neural networks and fuzzy logic: Three case studies (A.M. Zellou, A.
Quenes). Part
6. General Applications.
27. Virtual magnetic resonance logs, a
low cost reservoir description tool (S.D. Mohaghegh).
28. Artificial neural
networks linked to GIS (Y. Yang, M.S. Rosenbaum).
29. Intelligent computing
techniques for complex systems (M. Nikravesh).
30. Multivariate statistical
techniques including PCA and rule based systems for well log correlation
(J.-S Lim). Author Index. Subject Index.
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