Using platform-target matching deviation, anti-collision difficulty, trajectory complexity, and total drilling footage as objective functions, and comprehensively considering constraints such as platform layout area, drilling extension limits, underground target distribution and trajectory collision risks, a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed. A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm (ISSA) for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm (DABC) for optimizing trajectory parameters in the inner layer. The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem. The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs. The ISSA-DABC has a strong global search capability, fast convergence and good robustness, and can simultaneously satisfy multiple engineering constraints on drilling footage, trajectory complexity and collision risk, and enables automated, workflow-wide generation of constraint-compliant, near-globally optimal platform-trajectory configurations. Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk, yielding more rational platform layouts and well factory design parameters.
Wang et al. (Sun,) studied this question.