Search for a command to run...
Abstract Directional drilling automation has advanced significantly in recent years; however, many deployments remain limited to advisory automation, where systems generate recommendations while execution relies on manual intervention. This paper presents the evolution from advisory automation to a fully closed-loop autonomous directional drilling workflow, integrated with a goal-based drilling advisory system, and deployed during offshore operations in Southeast Asia. In advisory automation, trajectory recommendations are generated based on downhole measurements and presented to the driller for acceptance and execution. In the closed-loop workflow described in this paper, the process is extended to include autonomous execution of steering commands. The system integrates a directional drilling advisory engine, an autonomous downlink execution workflow, a downhole steerable drilling system, and a surface-based goal-driven drilling advisory layer. Real-time operational data are continuously evaluated to determine bottomhole assembly response, trajectory deviation, and drilling performance. Steering recommendations are generated, accepted by the driller, autonomously converted into downlink commands, executed downhole, and subsequently assessed using updated measurements, thereby closing the directional control loop. In parallel, the goal-based drilling advisory system maintains continuous awareness of the real-time drilling state and recommends optimized drilling parameters aligned with user-defined objectives. These objectives include rate of penetration optimization, mitigation of drilling dysfunctions such as stick-slip and shock and vibration, and adherence to operational safety limits. The advisory outputs support consistent execution while reducing variability associated with manual parameter tuning. The integrated workflow was applied in offshore drilling environments characterized by extended-reach objectives and managed pressure constraints. Results demonstrate reduced reaction time to trajectory deviations, improved well placement consistency, mitigation of drilling dysfunctions, and reduced non-productive time. By combining closed-loop directional execution with goal-based drilling advisory, the system enabled the driller to focus on higher-value operational priorities while delivering consistent and repeatable performance. This paper discusses system architecture, workflow integration, operational performance, and lessons learned from implementing a multi-layer autonomous drilling framework. The results highlight autonomous execution and goal-based decision support as key enablers for scalable, reliable, and future-ready automated well construction.