Soft computing and intelligent data analysis in oil exploration
著者
書誌事項
Soft computing and intelligent data analysis in oil exploration
(Developments in petroleum science, 51)
Elsevier, 2003
大学図書館所蔵 全1件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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. Landro, L.K. Stronen 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. Chawathe, 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.
「Nielsen BookData」 より