The Applications of BP Neural Network Based on MIV in Hydraulic Fracturing

Abstract

As a effective stimulation, hydraulic fracturing was commonly used in the mining process of complicated low permeability reservoirs, especially in horizontal shale gas wells more widely. In this paper, we establish the BP (Back Propagation) neural network based on MIV (Mean Impact Value) which is different from traditional BP neural network. We choose the independent variables of training set, plus or minus a certain percentages. Measured by the absolute size of MIV value and analyze the changes of MIV value, we identify the main factors in hydraulic fracturing. Combined qualitative analysis with quantitative calculation, the hydraulic fracturing evaluation model was established. Compared with the traditional BP neural network, the evaluation model shows a high precision, and good stability. Above all, we succeed in achieving a rapid, objective and impartial productivity prediction after hydraulic fracturing in complicated low permeability reservoirs. So in the future, this new hydraulic fracturing evaluation model is about to having abroad applications in the field of hydraulic fracturing.