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Soft Computing for Reservoir Characterization and Modeling 2002 ed. [Kõva köide]

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  • Formaat: Hardback, 586 pages, kõrgus x laius: 235x155 mm, kaal: 1175 g, XV, 586 p., 1 Hardback
  • Sari: Studies in Fuzziness and Soft Computing 80
  • Ilmumisaeg: 04-Dec-2001
  • Kirjastus: Physica-Verlag GmbH & Co
  • ISBN-10: 3790814210
  • ISBN-13: 9783790814217
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  • Formaat: Hardback, 586 pages, kõrgus x laius: 235x155 mm, kaal: 1175 g, XV, 586 p., 1 Hardback
  • Sari: Studies in Fuzziness and Soft Computing 80
  • Ilmumisaeg: 04-Dec-2001
  • Kirjastus: Physica-Verlag GmbH & Co
  • ISBN-10: 3790814210
  • ISBN-13: 9783790814217
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.
Foreword vii B. Braunschweig Preface xi P.M. Wong F. Aminzadeh M. Nikravesh Intelligent Reservoir Characterization 3(12) P.M. Wong F. Aminzadeh M. Nikravesh Part
1. Seismic Characterization Prediction of Reservoir Properties by Monte Carlo Simulation and Artificial Neural Network in the Exploration Stage 15(20) K Nakayama J. Hou Application of Neural Networks in Determining Petrophysical Properties from Seismic Survey 35(22) B. Widarsono S. Munadi F. Saptono Mapping the Gas Column in an Aquifer Gas Storage with Neural Network Techniques 57(16) H. Trappe C. Hellmich J. Knudsen H. Baartman Interval and Fuzzy Kriging Techniques Applied to Geological and Geophysical Variables 73(32) A. Consonni R. Iantosca P. Ruffo Application of Self-Organizing Feature Maps to Reservoir Characterization 105(24) C.A. Link J. Conaway Part
2. Well Logging Taking One Step Forward to Reservoir Characterization Using Artificial 129(32) S. Mohaghegh Inverting SP Logs Using Artificial Neural Networks and the Application in Reservoir Characterization 161(22) R. Ramberger J. Skolnakorn Predicting Petrophysical Parameters in a Fuzzy Environment 183(36) J. Finol X.D. Jing The Application of Fuzzy Logic and Genetic Algorithms to Reservoir Characterization and Modeling 219(24) S.J. Cuddy P. W.J. Glover The Use of Soft Computing Techniques as Data Preprocessing and Postprocessing in Permeability Determination from Well Log Data 243(30) K.W. Wong T.D. Gedeon C.C. Fung A New Technique to Estimate the Hydrocarbon Saturation in Shaly Formations: A Field Example in the Bahariya Formation, Egypt 273(40) A.M. Dawood A.A. Ibrahim S. A. Et-Tayeb Part
3. Numerical Geology Automated Reconstruction of a Basin Thermal History with Integrated Paleothermometry and Genetic Algorithm 313(18) C.-S. Kim An Automatic Geophysical Inversion Procedure Using a Genetic Algorithm 331(24) F. Mansanne M. Schoenauer Statistical Pattern Recognition and Geostatistical Data Integration 355(32) J. Caers S. Srinivasan How to Improve Reservoir Characterization Models Using Intelligent Systems 387(32) R. Soto B. F. Torres A. Arango G. Cobaleda S. Holditch C. Wu Regional Upscaling: A New Method to Upscale Heterogeneous Reservoirs for a Range of Force Regimes 419(46) C. Coll A. Muggeridge X.D. Jing Part
4. Advanced Algorithms New Uncertainty Measures for Predicted Geological Properties from Seismic Attribute Calibration 465(16) C.-S. Kim Rule Induction Algorithm for Application to Geological and Petrophysical Data 481(30) C. V. Deutsch Y.L. Xie A.S. Cullick Joint Lithologic Inversion 511(20) L.-Y. Fu Support Vector Machines for Classification and Mapping of Reservoir Data 531(28) M. Kanevski A. Pozdnukhov S. Canu M. Maignan P.M. Wong S.A.R. Shibli Non-parametric Covariance Modeling Using Fast Fourier Transform 559(28) T.-T. Yao About the Editors 587