Application of RBF Algorithm in Prediction of Threshold Pressure Gradient

It is well known that it plays an important role to determine threshold pressure gradient (TPG) in developing the low permeability oil field, and it directly influences the accuracy of reservoir pressure and developing amount. Threshold pressure gradient becomes nonlinear relation with such factors that may influence accuracy as permeability, viscosity and density of fluid and porosity and so on. Such a problem of nonlinear nature can be solved by RBF neural network systems. Based on above thought, authors of this paper predict the TPG using RBF neural network. This approach has further been tested and verified by actual determining results .The experimental results show that RBF neural network is an effective method for TPG prediction with good precision. The application of this approach can supply basic data for developing oil field so as to save cost and labor.