A new approach to improve neural networks' algorithm in permeability prediction of petroleum reservoirs using supervised committee machine neural network (SCMNN)

Journal of Petroleum Science and Engineering

Volumn 73, Issue 3-4, 2010, Pages 227-232

  Karimpouli, Sadegh ^a   Fathianpour, Nader ^a   Roohi, Jaber ^a  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Committee machine; Neural network; Permeability prediction; Petroleum reservoir; SCMNN

Indexed keywords

COMMITTEE MACHINES; CORRELATION COEFFICIENT; CRITICAL PARAMETER; HIGH CLASS; HIGH PERMEABILITY; HIGH-POWER; HYDROCARBON RESERVOIR; INPUT DATAS; NEW APPROACHES; PERMEABILITY PREDICTION; RESERVOIR PERMEABILITY; SCMNN; SIMPLE NETWORKS; STATISTICAL STUDY; TESTING DATA; TRAINING DATA; WELL LOG DATA;

FORECASTING; HYDROCARBONS; NEURAL NETWORKS; PETROLEUM RESERVOIRS; POPULATION STATISTICS; WELL LOGGING;

PETROLEUM RESERVOIR ENGINEERING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; GEOSTATISTICS; HYDROCARBON RESERVOIR; PERMEABILITY; PETROLEUM ENGINEERING; PREDICTION; STATISTICAL DATA;

IRAN;

EID: 78649976856     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.petrol.2010.07.003     Document Type: Article

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