Multi-objective drilling trajectory optimization using decomposition method with minimum fuzzy entropy-based comprehensive evaluation

This paper is concerned with the optimization problem of drilling trajectory design, which plays a vital role in ensuring the safety and enhancing the efficiency of an industrial drilling process. Due to complex geological environment and limited capacity of equipment, the problem to be addressed features multi-objective and multi-constraint, and consists of two challenges: (1) how to formulate a proper optimization scheme and efficiently solve it for a group of solutions; and (2) how to pick out a desired result from the obtained Pareto solutions according to certain requirements. In this paper, to meet drilling practice, three objective functions are introduced regarding trajectory length, well-profile energy, and target error, respectively. Constraints are the range of decision parameters, non-negative constraints and bound of the target area. As a result, a comprehensive optimization model for the design of drilling trajectory is established. A novel optimization algorithm is devised to deal with the contradictory objectives and multiple nonlinear constraints, which combines an adaptive penalty function with multi-objective evolutionary algorithm based on decomposition. A fuzzy-entropy-based evaluation approach is further employed to determine a satisfactory solution from the group of obtained ones. A case study illustrates that (1) our optimization solution is indeed beneficial to the optimization of drilling trajectory; and (2) the optimization algorithm and the decision method therein outperform some existing ones, which shows both practical and theoretical significance. (C) 2021 Elsevier B.V. All rights reserved.