Research on Intelligent Control Algorithm of Complex Borehole Trajectory Based on Multi-objective Optimization

Effective wellbore trajectory control is essential in complex drilling environments, where precision and operational efficiency are critical to reducing costs and improving safety. Traditional trajectory control methods often face limitations in addressing multiple conflicting objectives, such as minimizing trajectory deviation while maximizing drilling efficiency. Traditional trajectory control methods often face limitations in addressing multiple conflicting objectives, such as minimizing trajectory deviation while maximizing drilling efficiency. This study presents an intelligent control approach utilizing the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) for multi-objective optimization in complex wellbore trajectory control. designing and implementing a set of objective functions tailored to trajectory control requirements, this approach leverages NSGA-III' s ability to handle high-dimensional trajectories. s ability to handle high-dimensional objective spaces, achieving a balanced optimization across diverse performance metrics. Experimental results Experimental results verify the effectiveness of this approach, with Matlab simulations demonstrating significant improvements in trajectory accuracy and computational efficiency. This research provides a robust framework for multi-objective trajectory control and highlights the potential of NSGA-III in enhancing decision-making for complex drilling applications. decision-making for complex drilling applications.