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000726670 020__ $$a9783319165318$$qelectronic book
000726670 020__ $$a3319165313$$qelectronic book
000726670 020__ $$z9783319165301
000726670 0247_ $$a10.1007/978-3-319-16531-8$$2doi
000726670 035__ $$aSP(OCoLC)ocn907947183
000726670 035__ $$aSP(OCoLC)907947183
000726670 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dN$T$$dE7B$$dYDXCP$$dIDEBK$$dCOO$$dUPM$$dOCLCO$$dUWO$$dEBLCP$$dDEBSZ
000726670 049__ $$aISEA
000726670 050_4 $$aTN870.5
000726670 08204 $$a662.60285/63$$223
000726670 24500 $$aArtificial intelligent approaches in petroleum geosciences$$h[electronic resource] /$$cConstantin Cranganu, Henri Luchian, Mihaela Elena Breaban, editors.
000726670 264_1 $$aCham :$$bSpringer,$$c2015.
000726670 300__ $$a1 online resource (xii, 290 pages) :$$billustrations.
000726670 336__ $$atext$$btxt$$2rdacontent
000726670 337__ $$acomputer$$bc$$2rdamedia
000726670 338__ $$aonline resource$$bcr$$2rdacarrier
000726670 500__ $$aIncludes index.
000726670 504__ $$aIncludes bibliographical references and index.
000726670 5050_ $$aIntelligent Data Analysis Techniques {u2013} 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{u2019}s Ratio and Young{u2019}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.
000726670 506__ $$aAccess limited to authorized users.
000726670 520__ $$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.
000726670 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 24, 2015).
000726670 650_0 $$aPetroleum$$xGeology$$xData processing.
000726670 650_0 $$aArtificial intelligence$$xGeophysical applications.
000726670 7001_ $$aCranganu, Constantin,$$eeditor.
000726670 7001_ $$aLuchian, Henri,$$eeditor.
000726670 7001_ $$aBreaban, Mihaela Elena,$$eeditor.
000726670 77608 $$iPrint version:$$z9783319165301
000726670 852__ $$bebk
000726670 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-16531-8$$zOnline Access$$91397441.1
000726670 909CO $$ooai:library.usi.edu:726670$$pGLOBAL_SET
000726670 980__ $$aEBOOK
000726670 980__ $$aBIB
000726670 982__ $$aEbook
000726670 983__ $$aOnline
000726670 994__ $$a92$$bISE