Calculation for Angle Error of Rotary Steerable Drilling Bit Based on Improved Differential Contour Method

Abstract

Rotary steerable drilling rigs are common equipment in the field of oil exploration and production. Precisely controlling the posture and rotation direction of the drill bit is crucial for improving drilling efficiency and ensuring drilling safety. Deep learning technology, known for its powerful learning capabilities, has been widely applied in various fields. Applying deep learning techniques to rotary steerable drilling rigs holds significant importance in enhancing drilling quality and efficiency. In this paper, we propose a deep learning-based method for calculating angle errors. By using the improved differential contour method to calculate the rotational angle error of the rotary steerable drill bit, automatic control of borehole direction and depth can be achieved. This approach improves drilling quality and efficiency while reducing drilling safety risks.