启动压力梯度预测的人工神经网络方法

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. Start-up 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 BP neural network systems. Based on above thought, authors of this paper predict the TPG using BP neural network. This approach has further tested and verified by actual determining results .The experimental results show that the BP 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.