Intelligent Systems in Oil Field Development under Uncertainty
Pacheco, Marco A. C.
Intelligent Systems in Oil Field Development under Uncertainty [electronic resource] / edited by Marco A. C. Pacheco, Marley M. B. R. Vellasco. - XX, 288 p. online resource. - Studies in Computational Intelligence, 183 1860-949X ; . - Studies in Computational Intelligence, 183 .
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.
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.
9783540930006
10.1007/978-3-540-93000-6 doi
Engineering.
Chemical engineering.
Artificial intelligence.
Engineering mathematics.
Engineering economy.
Environmental economics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Engineering Economics, Organization, Logistics, Marketing.
Artificial Intelligence (incl. Robotics).
Industrial Chemistry/Chemical Engineering.
Environmental Economics.
TA329-348 TA640-643
519
Intelligent Systems in Oil Field Development under Uncertainty [electronic resource] / edited by Marco A. C. Pacheco, Marley M. B. R. Vellasco. - XX, 288 p. online resource. - Studies in Computational Intelligence, 183 1860-949X ; . - Studies in Computational Intelligence, 183 .
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.
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.
9783540930006
10.1007/978-3-540-93000-6 doi
Engineering.
Chemical engineering.
Artificial intelligence.
Engineering mathematics.
Engineering economy.
Environmental economics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Engineering Economics, Organization, Logistics, Marketing.
Artificial Intelligence (incl. Robotics).
Industrial Chemistry/Chemical Engineering.
Environmental Economics.
TA329-348 TA640-643
519