Cooperative Optimization Design Method of Multitrajectory Profile in “Well Factory” for Oil and Gas Development

Summary A “well factory” refers to the arrangement of multiple or even a large number of similar wells on the same platform and the drilling and completion of these wells with standardized equipment and a similar operational approach. The well factory mode can effectively handle the challenges posed by complex terrains in oceans and mountainous areas and achieve economical and efficient development of oil and gas resources. Conventional studies mainly focus on the optimization of a single trajectory or the sequential optimization of multiple trajectories. However, there is a lack of cooperative optimization of multiple trajectories, making it difficult to obtain better design results for well trajectories of the well factory mode. Owing to the complicated interdependencies among the design variables of each trajectory (such as the kickoff point, target section length, well inclination, azimuth, and buildup rate), traditional methods struggle to directly address the cooperative optimization problem. This problem involves collaboration and interaction between different trajectories to achieve common objectives and enhance the overall optimization effectiveness. This study established a multitrajectory profile cooperative optimization design model with the objective of minimizing the overall drilling footage, trajectory complexity, trajectory similarity, and collision risk. Next, a cooperative coevolution (CC) approach was introduced and combined with a directed artificial bee colony (DABC) algorithm to develop a collaborative update strategy for multitrajectory optimization. Finally, the CC-DABC algorithm was tested, and a case study was conducted using the new design method. The results indicated that the new method could effectively handle multitrajectory profile cooperative optimization design for various well layouts, including single-layer, multilayer, and extremely small well-spacing scenarios. The CC-DABC algorithm significantly outperformed other combined algorithms in terms of optimization effectiveness, robustness, and overall search efficiency and exhibited excellent performance under small well spacing conditions. In the case study, the trajectories optimized with the new method had less drilling footage and smaller trajectory complexity than the original designs. Additionally, the anticollision risk and staggered arrangement of the kickoff points between adjacent wells effectively met the engineering requirements, demonstrating the application potential of this new method.