LEADER 05549nam 22008055 450 001 9910299608103321 005 20230417143744.0 010 $a3-319-16531-3 024 7 $a10.1007/978-3-319-16531-8 035 $a(CKB)3710000000402735 035 $a(EBL)2094542 035 $a(SSID)ssj0001501341 035 $a(PQKBManifestationID)11803533 035 $a(PQKBTitleCode)TC0001501341 035 $a(PQKBWorkID)11522547 035 $a(PQKB)10253877 035 $a(DE-He213)978-3-319-16531-8 035 $a(MiAaPQ)EBC2094542 035 $a(PPN)185485898 035 $a(EXLCZ)993710000000402735 100 $a20150418d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aArtificial Intelligent Approaches in Petroleum Geosciences$b[electronic resource] /$fedited by Constantin Cranganu, Henri Luchian, Mihaela Elena Breaban 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (298 p.) 300 $aDescription based upon print version of record. 311 $a3-319-16530-5 320 $aIncludes bibliographical references and index. 327 $aIntelligent Data Analysis Techniques ? Machine Learning and Data Mining -- On meta-heuristics in optimization and data analysis. Application to geosciences -- Genetic Programming Techniques with Applications in the Oil and Gas Industry -- Application of Artificial Neural Networks in Geoscience and Petroleum Industry -- On Support Vector Regression to Predict Poisson?s Ratio and Young?s Modulus of Reservoir Rock -- Use of Active Learning Method to determine the presence and estimate the magnitude of abnormally pressured fluid zones: A case study from the Anadarko Basin, Oklahoma -- Active Learning Method for estimating missing logs in hydrocarbon reservoirs -- Improving the accuracy of Active Learning Method via noise injection for estimating hydraulic flow units: An example from a heterogeneous carbonate reservoir -- Well log analysis by global optimization-based interval inversion method -- Permeability estimation in petroleum reservoir by artificial intelligent methods: An overview. 330 $aThis book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions, and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics, and geochemistry), data fusion, risk reduction, and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry. 606 $aCogeneration of electric power and heat 606 $aFossil fuels 606 $aArtificial intelligence 606 $aGeotechnical engineering 606 $aMathematical models 606 $aMineralogy 606 $aFossil Fuel 606 $aArtificial Intelligence 606 $aGeotechnical Engineering and Applied Earth Sciences 606 $aMathematical Modeling and Industrial Mathematics 606 $aMineralogy 615 0$aCogeneration of electric power and heat. 615 0$aFossil fuels. 615 0$aArtificial intelligence. 615 0$aGeotechnical engineering. 615 0$aMathematical models. 615 0$aMineralogy. 615 14$aFossil Fuel. 615 24$aArtificial Intelligence. 615 24$aGeotechnical Engineering and Applied Earth Sciences. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aMineralogy. 676 $a003.3 676 $a006.3 676 $a553 676 $a621.042 676 $a624.151 676 $a662.6 702 $aCranganu$b Constantin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLuchian$b Henri$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBreaban$b Mihaela Elena$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299608103321 996 $aArtificial Intelligent Approaches in Petroleum Geosciences$92165790 997 $aUNINA