Empowering Drillers with AI to Deliver Better Wells and Optimize Performance
Abstract AI has revolutionized the tech world with its innovative capabilities. Its ability to accelerate processes has had a profound impact across industries. Historically, Oil and Gas has been resistant to embrace the unknown and AI is no exception. As an industry we've been cautious in leveraging AI to harness data, enhance our process, and drive actionable insights. This can be contributed to both business and people related concerns. From a Drilling Contractors perspective, every technology shift presents challenges – from automating and sequencing machines, integrating robotics, and now AI. In order to effectively identify the right opportunities for AI, we have followed a few guiding principles – enhance the drillers workflow, improve well outcomes, and strengthen remote operability. With such a strong industry focus in on bottom performance, it's critical to have accurate and consistent Weight on Bit (WOB) Zeroing points to optimize Rate of Penetration (ROP) effectively and ensure you're not unknowingly introducing dysfunction. Building a model to seamlessly work with the driller that identifies appropriate zeroing points is a simple way to enhance his workflow and influence operator outcomes. Zeroing points are dependent a multitude of factors, including the off-bottom procedure and the drillers decision making. Even when automating the procedure, there are still dependencies that require human decision making. In partnership with operations, we have implemented a solution that combines an AI model that has learnt from historical well data and design of intuitive and user-friendly HMI screen additions to the driller workflow. Initial feedback with both in place has been tremendously positive.
Authors
- S. A. R. Avilala
- R. Lakkaraju
- B. Farrow
- R. Welch
Institutions
- Nabors Industries (United States) (US)
Publication Details
- Journal
- SPE/IADC Middle East Drilling Technology Conference and Exhibition
- Published
- 2025-05-27
- DOI
- https://doi.org/10.2118/225768-ms
- Primary Topic
- Drilling and Well Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00