关键词: 预弯 BHA, 钻头合导向力, 参数优化, 粒子群优化, 支持向量回归

Abstract: The combined guiding force of pre-bent bottom hole assembly (BHA) bit is of paramount significance for well trajectory control, but the traditional calculation method is time-consuming and labor-intensive. A method based on particle swarm optimization and support vector regression is proposed to quickly predict the combined guiding force of prebent BHA bit. Firstly, the weighted margin method is used to solve the three-dimensional small deflection mechanical model of the BHA, and the bit combined guiding force is obtained, and the sample space of support vector regression is formed. Secondly, particle swarm optimization is used to optimize the support vector regression parameters, and the optimal values of penalty factor, kernel function parameters and insensitivity coefficient are obtained. Finally, combined with an example, particle swarm optimization is used to predict the bit combined guiding force, and the accuracy of the prediction results is analyzed and evaluated. The results show that the prediction accuracy of the combined guiding force of pre-bent BHA bit is high, and the coefficient of determination R 2 is 0.956 8.

Key words: pre-bent BHA, bit combined guiding force, parameter optimization, particle swarm optimization, support vector regression