Abstract: Based on the data from a series of petroleum migration and accumulation units, the major geologic factors for controlling oil migration and accumulation coefficient are selected. The forecast model for oil migration and accumulation coefficient based on BP neural network is developed by taking the major geologic factors as the input vectors and the oil migration and accumulation coefficients as output vectors. It is indicated that the applied result of this model is in good agreement with the observed data with average relative error of 10.89% and the corresponding agreement index is about 92.51%. Moreover, the prediction precision by using this model is much higher than that by using multi-element nonlinear regression model.

Key words: migration and accumulation coefficient, BP neural network, model, forecast, prediction