Intelligent Systems in Oil Field Development under Uncertainty

Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been...

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Bibliographic Details
Other Authors: Pacheco, Marco A. C. (Editor), Vellasco, Marley M. B. R. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2009, 2009
Edition:1st ed. 2009
Series:Studies in Computational Intelligence
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Intelligent Systems in Oil Field Development under Uncertainty  |h Elektronische Ressource  |c edited by Marco A. C. Pacheco, Marley M. B. R. Vellasco 
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260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 2009, 2009 
300 |a XX, 288 p  |b online resource 
505 0 |a ANEPI: Economic Analysis of Oil Field Development Projects under Uncertainty -- Real Options Theory -- Decision Support Methods -- Intelligent Optimization System for Selecting Alternatives for Oil Field Exploration by Means of Evolutionary Computation -- Real Option Value Calculation by Monte Carlo Simulation and Approximation by Fuzzy Numbers and Genetic Algorithms -- Analysis of Alternatives for Oil Field Development under Uncertainty -- High-Performance Processing for E&P -- Appendix A – Types of Uncertainty in Investment Projects -- Appendix B – Variance Reduction Techniques -- Appendix C – Stochastic Processes -- Appendix D – Grant, Vora and Weeks Algorithm for Determining the Value of an American Option -- Appendix E – Calculation of the Mean Value and Variance of Fuzzy Numbers -- Appendix F – Real Options Valuation Methods -- Appendix G – Analytical Model of the Expansion Option Problem -- Appendix H – CORBA Architecture 
653 |a Industrial Management 
653 |a Environmental Economics 
653 |a Environmental economics 
653 |a Engineering mathematics 
653 |a Artificial Intelligence 
653 |a Chemistry, Technical 
653 |a Artificial intelligence 
653 |a Engineering / Data processing 
653 |a Industrial Chemistry 
653 |a Mathematical and Computational Engineering Applications 
700 1 |a Vellasco, Marley M. B. R.  |e [editor] 
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520 |a Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been used with success by companies and organizations that are looking for competitive advantages whenever the issues on forecast, optimization, risks analysis, fraud detection, and decision under uncertainties are presented. Intelligent Systems (IS) offer to managers and decision makers the best solutions for complex applications, normally considered difficult, very restrictive or even impossible. The use of such techniques leads to a revolutionary process which has a significant impact in the business management strategy, by providing on time, correct information, ready to use. Computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy as well as modern finance theories, such as real options theory, are here presented and exemplified in oil and gas exploitation and production. This book is addressed to executives and students, directly involved or interested in intelligent management in different fields