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Abstract Improving well cycle time efficiency involves automating the benchmarking and replication of top-performer activities across a fleet, enhancing safety, reducing learning curves, and enabling real-time well performance monitoring for consistent operational excellence beyond on-bottom activities. The process involves consuming data from any digital well program, automatically converting it into a Driller's Roadmap for the digital execution of well-defined sequence of activities to eliminate guesswork and delays, to help with knowledge sharing minimizing the learning curve. Efficiently disseminating and implementing best practices, lessons learned and operational procedures by activity backed by data driven insights. Sending timely notifications and alerts to drillers and preparing crews to transition seamlessly into the next operation. The rig execution engine includes optimizing various drilling activities through specific recipe parameters, which will enable automation within a rig operating system all while providing visibility for all stakeholders. As the industry progresses towards automating well design, a key innovation is the integration of these designs with a versatile rig execution engine, accessible at the edge and the cloud. An implementation conducted across 5 rigs working for a major operator in the Permian Basin demonstrated significant improvements in well cycle efficiency, highlighting the potential of this approach to transform well operations in the industry. The integration of a versatile rig execution engine with cloud-edge technology and enhanced crew dynamics resulted in observable well cycle time efficiencies, emphasizing the value of this innovative approach through flat time optimization. This integration between a rig plan and the rig execution engine increases procedural adherence through execution using a rig operating system that automates tasks according to the well program. Additionally, improves driller training and crew retention by providing timely, relevant information and resources, including multi-lingual support, thereby fostering greater inclusion in operations.
Zaraté et al. (Fri,) studied this question.