Well Trajectory Design Based on Constrained Many-Objective Optimization Algorithms

In the field of drilling engineering, the design and optimization of well trajectories are crucial. This study focuses on optimizing key aspects such as the length of the well trajectory, drill string torque, the energy of the well-profile, and accuracy in reaching the target. This problem encompasses eleven complex nonlinear constraints and four conflicting objectives, presenting challenges for traditional mathematical programming methods. To tackle this problem, we introduce a novel constrained many-objective optimization algorithm, named PPS-NSGA-III. The proposed algorithm partitions the objective space into subspaces, using NSGA-III to find Pareto optimal solutions in each, enhancing diversity. The push-and-pull search framework is employed to overcome local optima in each subproblem, accelerating overall convergence. Through a comparative analysis with some evolutionary algorithms, PPS-NSGA-III has shown superior performance. It delivers more effective design solutions with lower risk, reduced cost, and a higher drilling encounter rate in the proposed well trajectory optimization model.