A ROP prediction method based on neutral network for the deep layers

As Bohai Oilfield steps to the development of medium and deep layers, it is necessary to predict the rate of penetration(ROP) in deep layers accurately.We firstly analyzed all factors which influence the ROP in deep layers and established a neural network model for predicting the ROP in deep layers in Bozhong area.Then, the ROP prediction model was verified based on the case of exploratory well BZ19-6-X.It is practically proved that the prediction result of the neural network is better accordant with the actual ROP.Finally, the tools for improving the ROP in deep layers were optimized based on the neural network model.The research results can be used as the guidance for development cost estimate and ROP and efficiency improvement of Bozhong area.