Uncertainty handling in wellbore trajectory design: a modified cellular spotted hyena optimizer-based approach

Abstract It is vital to optimize the drilling trajectory reduce possibility of accidents and boosting efficiency. Previously, wellbore was optimized using true measured depth well profile energy as objective functions without considering uncertainty between actual planned trajectories. Without an effective management associated with planning, process becomes more complex. Prior techniques have some drawbacks; for example, they could not find isolated minima a slow convergence rate when dealing high-dimensional problems. Consequently, novel approach termed “Modified Multi-Objective Cellular Spotted Hyena Optimizer” proposed address aforesaid concerns. Following that, mechanism eliminating outliers has been developed implemented in sorting minimize uncertainty. The algorithm outperformed standard methods like cellular spotted hyena optimizer, grey wolf optimizer terms non-dominated solution distribution, search capability, reduction, pareto optimal front. Numerous statistical analyses were undertaken determine significance algorithm. achieved lowest inverted generational distance, spacing metric, error ratio, while achieving highest maximum spread. Finally, adaptive neighbourhood presented, which fixed topologies such L5, L9, C9, C13, C21, C25. Afterwards, technique order preference by similarity ideal linear programming multidimensional analysis used provide best solution.