An Application of RBF Neural Networks for Petroleum Reservoir Characterization

The parameter calculation relating to petroleum reservoir characterization and lithologic identification based on RBF neural networks is studied in this paper. Two models for reservoir permeability prediction and litho logic identification have been constructed and are applied to predict the unknown samples. The prediction result of reservoir permeability has a higher consistency with the practical cases. The parameter prediction and litho logic identification precision have been greatly improved compared to the traditional BP neural networks. The results show that the RBF neural network is very promising for the application of petroleum reservoir characterization.