Research on the prediction of drag and torque based on BP algorithm

In the current oil fields in China, the horizontal well technology with a long horizontal interval has gradually become the core technology to develop conventional oil and gas reservoirs, and the accurate determination of the drag and torque of the drill string is the key. However, the determination of the friction coefficient is affected by many factors, and it is difficult to describe it clearly by mathematical formulas. According to the characteristics of friction factors, the method of calculating the friction coefficient of drill string is studied, and a prediction model of friction coefficient based on BP algorithm is established. Based on the predicted friction coefficient, the calculation method of drag and torque is analyzed, and a drag and torque prediction model based on BP algorithm is established. The experimental results show that the use of BP neural network can accurately predict the friction coefficient and torque, and the prediction of the friction coefficient can characterize the risk of sticking of the drill string to a certain extent, which facilitates the adjustment of drilling parameters on site to improve the safety during drilling.