Managed pressure drilling and automated well killing based on African vulture optimization-proportional integral derivative controller

Both managed pressure drilling (MPD) and kill procedures depend on the rapid and precise control of the choke under varying conditions. To enhance drilling safety and automate MPD and well kill operations, we employed the African vulture optimization algorithm, a proportional integral derivative controller, and an automated choke control panel for automated choke management. Laboratory and offshore platform experiments were conducted to simulate MPD and kill procedures under single-phase and two-phase flow conditions. Additionally, a reliability analysis was performed using fault tree analysis and dynamic Bayesian network to ensure system safety during long-term operations. Experimental results indicate that during the simulated MPD process, the automated system improved choke adjustment efficiency by 19.6% compared to manual control and reduced pressure fluctuations post-stabilization by 60.0%. In the simulated kill procedure, the system effectively tracked the planned pressure curve and exhibited strong anti-interference capabilities. Offshore platform experiments demonstrated a 25.5% increase in choke adjustment efficiency over engineer-operated controls. Pressure fluctuations in simulated MPD and well kill experiments were reduced by 90.7% and 87.0%, respectively, compared to manual operations. Reliability analysis revealed that after one year of continuous operation, the system's failure probability was 22.9%. However, with timely maintenance, the failure probability initially increased but eventually stabilized at 2.8%. In conclusion, the automated choke control system effectively and safely executes MPD and kill procedures, supports engineers in their operations, and significantly enhances drilling safety.