Abstract This paper details the first offshore deployment of an artificial intelligence (AI)-powered drilling automation system on a jackup rig in the UAE by ADNOC Offshore. The project marks a significant step in the digital transformation of offshore drilling, integrating both automated surface equipment control and AI-driven rate of penetration (ROP) optimization into the full drill-a-stand process (Noshi and Schuber, 2018; Bello et at., 2016). Two development wells were drilled using the system, which not only improved operational efficiency but also established a new performance benchmark for future operations. The study involved benchmarking against offset wells, applying performance diagnostics, and documenting technical and operational lessons learned. By demonstrating measurable performance improvements in ROP and connection time reductions, this paper supports the viability of full-cycle drilling automation in offshore environments. The trial validates the role of intelligent automation in ADNOC's digital roadmap and offers a replicable blueprint for broader fleet-wide implementation. The results also underscore the importance of cross-functional collaboration and proactive crew engagement in realizing technology benefits. This work contributes new data and practical insights to the body of knowledge surrounding automation and AI in drilling operations, particularly in complex offshore settings where real-time decision-making and execution consistency are critical to success.
Zhao et al. (Mon,) studied this question.
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