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Soft Computing for Reservoir Characterization and Modeling

  • Book
  • © 2002

Overview

Editors:
  1. Patrick Wong

    1. School of Petroleum Engineering, University of New South Wales, Sydney, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Fred Aminzadeh

    1. Sugar Land, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Masoud Nikravesh

    1. Computer Science Division, Department of EECS, University of California, Berkeley, USA

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    You can also search for this editor in PubMed   Google Scholar

  • General overview of soft computing techniques and their application in reservoir modeling practices
  • First specialized book on the topic
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 80)

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Table of contents (22 chapters)

  1. Front Matter

    Pages I-XVII
    Download chapter PDF

  2. Intelligent Reservoir Characterization

    1. Intelligent Reservoir Characterization

      • P. M. Wong, F. Aminzadeh, M. Nikravesh
      Pages 3-12

  3. Seismic Characterization

    1. Front Matter

      Pages 13-13
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    2. Prediction of Reservoir Properties by Monte Carlo Simulation and Artificial Neural Network in the Exploration Stage

      • Kazuo Nakayama, Jianyong Hou
      Pages 15-33

    3. Application of Neural Networks in Determining Petrophysical Properties from Seismic Survey

      • Bambang Widarsono, Suprajitno Munadi, Fakhriyadi Saptono
      Pages 35-55

    4. Mapping the Gas Column in an Aquifer Gas Storage with Neural Network Techniques

      • H. Trappe, C. Hellmich, J. Knudsen, H. Baartman
      Pages 57-71

    5. Interval and Fuzzy Kriging Techniques Applied to Geological and Geophysical Variables

      • Alberto Consonni, Raffaella Iantosca, Paolo Ruffo
      Pages 73-103

    6. Application of Self-Organizing Feature Maps to Reservoir Characterization

      • C. A. Link, J. Conaway
      Pages 105-126

  4. Well Logging

    1. Front Matter

      Pages 127-127
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    2. Taking One Step Forward in Reservoir Characterization Using Artificial Neural Networks

      • Shahab Mohaghegh
      Pages 129-160

    3. Inverting SP Logs Using Artificial Neural Networks and the Application in Reservoir Characterisation

      • Rudolf Ramberger, Jirapa Skolnakorn
      Pages 161-181

    4. Predicting Petrophysical Parameters in a Fuzzy Environment

      • Jose Finol, X. D. Jing
      Pages 183-217

    5. The Application of Fuzzy Logic and Genetic Algorithms to Reservoir Characterization and Modeling

      • S. J. Cuddy, P. W. J. Glover
      Pages 219-241

    6. The Use of Soft Computing Techniques as Data Preprocessing and Postprocessing in Permeability Determination from Well Log Data

      • K. W. Wong, T. D. Gedeon, C. C. Fung
      Pages 243-271

    7. A New Technique to Estimate the Hydrocarbon Saturation in Shaly Formations: A Field Example in the Bahariya Formation, Egypt

      • Ahmed M. Dawood, Adel A. Ibrahim, El-Sayed A. El-Tayeb
      Pages 273-309

  5. Numerical Geology

    1. Front Matter

      Pages 311-311
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    2. Automated Reconstruction of a Basin Thermal History with Integrated Paleothermometry and Genetic Algorithm

      • Chul-Sung Kim
      Pages 313-329

    3. An Automatic Geophysical Inversion Procedure Using a Genetic Algorithm

      • F. Mansanné, M. Schoenauer
      Pages 331-353

    4. Statistical Pattern Recognition and Geostatistical Data Integration

      • Jef Caers, Sanjay Srinivasan
      Pages 355-386

    5. How to Improve Reservoir Characterization Models Using Intelligent Systems

      • Soto B. Rodolfo, Fredy Torres, Sandro Arango, Gloria Cobaleda, Stephen Holditch, Ching Wu
      Pages 387-417
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Keywords

About this book

In the middle of the 20th century, Genrich Altshuller, a Russian engineer, analysed hundreds of thousands of patents and scientific publications. From this analysis, he developed TRIZ (G. Altshuller, "40 Principles: TRIZ Keys to Technical Innovation. TRIZ Tools," Volume 1, First Edition, Technical Innovation Center, Inc. , Worcester, MA, January 1998; Y. Salamatov, "TRIZ: The Right Solution at the Right Time. A Guide to Innovative Problem Solving. " Insytec B. V. , 1999), the theory of inventive problem solving, together with a series of practical tools for helping engineers solving technical problems. Among these tools and theories, the substance-field theory gives a structured way of representing problems, the patterns of evolution show the lifecycle of technical systems, the contradiction matrix tells you how to resolve technical contradictions, using the forty principles that describe common ways of improving technical systems. For example, if you want to increase the strength of a device, without adding too much extra weight to it, the contradiction matrix tells you that you can use "Principle 1: Segmentation," or "Principle 8: Counterweight," or "Principle 15: Dynamicity," or "Principle 40: Composite Materials. " I really like two particular ones: "Principle 1: Segmentation," and Principle 15: Dynamicity. " "Segmentation" shows how systems evolve from an initial monolithic form into a set of independent parts, then eventually increasing the number of parts until each part becomes small enough that it cannot be identified anymore.

Editors and Affiliations

  • School of Petroleum Engineering, University of New South Wales, Sydney, Australia

    Patrick Wong

  • Sugar Land, USA

    Fred Aminzadeh

  • Computer Science Division, Department of EECS, University of California, Berkeley, USA

    Masoud Nikravesh

Bibliographic Information

  • Book Title: Soft Computing for Reservoir Characterization and Modeling

  • Editors: Patrick Wong, Fred Aminzadeh, Masoud Nikravesh

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-7908-1807-9

  • Publisher: Physica Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2002

  • Hardcover ISBN: 978-3-7908-1421-7Published: 04 December 2001

  • Softcover ISBN: 978-3-7908-2495-7Published: 29 January 2011

  • eBook ISBN: 978-3-7908-1807-9Published: 11 November 2013

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: XV, 586

  • Topics: Geology, Geophysics/Geodesy, Artificial Intelligence, Earth Sciences, general

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