Chaotic Neural Network Model for Output Prediction of Polymer Flooding

In order to predict the dynamic targets of water ratio and oil output in situation of polymer flooding accurately, chaotic neural network (CNN) prediction model on output varied rules of polymer flooding was established, the method of predict water cut and oil output is found, and the prediction results are analyzed. The results show that the prediction relative error of accumulative oil output on polymer flooding is 3.25 percent, which is much lower than the required prediction error.