Comparative evaluation of back-propagation neural network learning algorithms and empirical correlations for prediction of oil PVT properties in Iran oilfields

Journal of Petroleum Science and Engineering

Volumn 78, Issue 2, 2011, Pages 464-475

  Asadisaghandi, Jalil ^a   Tahmasebi, Pejman ^b  

^a NATIONAL IRANIAN SOUTH OIL COMPANY NISOC   (Iran)

^b AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Back propagation; Empirical correlations; Estimation; Iran; Optimum neural network; PVT

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION NEURAL NETWORKS; BACKPROPAGATION LEARNING ALGORITHM; BUBBLE POINT PRESSURE; BUBBLE POINTS; COMMON PROBLEMS; COMPARATIVE EVALUATIONS; CONTINENTAL SHELVES; DATA SETS; ELEMENTS SELECTION; EMPIRICAL CORRELATIONS; HYDROCARBON PROPERTIES; HYDROCARBON SYSTEMS; IMPROVED METHODS; IRAN; NETWORK STRUCTURES; NEURAL NETWORK DESIGNS; NEURAL NETWORK METHOD; NEW MODEL; OIL FORMATION; OPTIMUM NEURAL NETWORK; PARAMETER VALUES; PERFORMANCE COMPARISON; PETROLEUM APPLICATIONS; PROPERTIES PREDICTION; PVT; PVT PROPERTIES;

BACKPROPAGATION ALGORITHMS; BOTTOM HOLE PRESSURE; CRUDE OIL; DESIGN; FORECASTING; HYDROCARBONS; INVESTMENTS; LEARNING ALGORITHMS; OIL FIELDS; PETROLEUM ANALYSIS; PETROLEUM INDUSTRY; STATISTICAL TESTS; TOPOLOGY;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; COMPARATIVE STUDY; CONTINENTAL SHELF; CORRELATION; HYDROCARBON TECHNOLOGY; OIL FIELD; PETROLEUM ENGINEERING; PREDICTION; PRESSURE; TEMPERATURE;

IRAN;

EID: 80052683685     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.petrol.2011.06.024     Document Type: Article

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