A Model for Predicting Formation Drillability Based on Optimized BP Neural Network

Abstract:

A new method for predicting formation drillablity was proposed according to the theory of BP networks based on PSO. The use of PSO optimizing the parameters of BP networks is to improve the convergence speed and precision of BP neural networks. Combining with the examples of drilling and based on the relationship of log information formation drillability grade, a real-time formation drillability grade model was established. The results show that the model is superior to BP network with higher accuracy and faster convergence rate and it is an effective way to predict formation drillablity.