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oil-gas-reservoir-characterization
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Lithological facies identification in Iranian largest gas field: A comparative study of neural network methods
, Article Journal of the Geological Society of India ; Vol. 84, issue. 3 , Sep , 2014 , p. 326-334 ; ISSN: 00167622 ; Masihi, M ; Sola, B. S ; Biniaz, E ; Sharif University of Technology
Abstract
Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),...
Lithological facies identification in Iranian largest gas field: A comparative study of neural network methods
, Article Journal of the Geological Society of India ; Vol. 84, issue. 3 , September , 2014 , PP. 326-334 ; ISSN: 00167622 ; Masihi, M ; Sola, B. S ; Biniaz, E ; Sharif University of Technology
Abstract
Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),...