Optimization Design Method for Wellbore Trajectory of Cluster Well Infill Drilling Based on Multi-Objective Genetic Algorithm

Abstract

Cluster well infill drilling faces challenges such as limited space for wellbore passage, high collision risks with existing underground production wells, and difficulties in wellbore trajectory design. To improve the efficiency of wellbore trajectory design, reduce collision risks, and enhance control, this study proposes an intelligent optimization method for wellbore trajectory design parameters using a multi-objective genetic algorithm. Based on the analysis of geometric parameter relationships in wellbore trajectories, a multi-parameter model for wellbore trajectory design and a distance calculation model between the designed trajectory and adjacent well trajectories were established. With the objectives of minimizing well depth and reducing friction, a fitness function was constructed, an individual selection strategy was formulated, and a hierarchical iterative calculation process for optimizing wellbore trajectory design parameters was designed. A case study of infill drilling on an artificial island compared single-objective and multi-objective optimizations, demonstrating that the multi-objective optimized trajectory outperformed the single-objective optimized trajectory.