Abstract: Transient surge/swab pressure during tripping in drilling and completion is a core factor triggering safety risks in deep wells with narrow safe mud weight windows. Based on unsteady flow theory, a transient surge/swab pressure calculation model during tripping was established and solved using the method of characteristics. The model was validated against field-measured data. Furthermore, constrained by the formation pressure profile, a tripping speed decision-making model was constructed based on the penalty function method, integrating such three swarm intelligence optimization algorithms as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), and Grey Wolf Optimizer(GWO) to formulate an intelligent decision-making method for critical tripping speed. The results demonstrate that the simulated transient surge pressure aligns well with measured data in overall trends, indicating the model’s effectiveness in capturing downhole pressure dynamics and its strong predictive capability. All three algorithms (GA, PSO, and GWO) maintained Equivalent Circulating Density (ECD) within the safe mud weight window, satisfying the constraints of the safe mud weight window. Statistical metrics from 50 repeated experiments, including mean, range, standard deviation, and confidence intervals, consistently identified GWO as the top-performing algorithm in terms of solution quality and safety, followed by PSO, while GA exhibited the poorest performance and lowest stability. The developed intelligent decision-making method for critical tripping speed provides scientific guidance for tripping operations, ensuring safety and enhancing operational efficiency.