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Exebenus showcases breakthrough in real-time, context-aware AI at SPE ATCE 2025

by Anne Siw Uberg | Oct 23, 2025 | News

Home News Exebenus showcases breakthrough in real-time, context-aware AI at SPE ATCE 2025 At SPE Annual Technical Conference and Exhibition (ATCE) 2025 in Houston, TX, Exebenus presented a groundbreaking paper, SPE-MS-227906, introducing a new framework that connects...

53 hours too late: How early warnings could have prevented stuck pipe and three days of NPT

by Anne Siw Uberg | Jun 23, 2025 | Case Studies

Home Case studies Case study 53 hours too late: How early warnings could have prevented stuck pipe and three days of NPT  Published: May 16, 2025  Location: Onshore, Oman  Products used: Exebenus Spotter, Stuck Pipe Agent " Download case study & Share: The...

Exebenus and Petrolink partner to deliver AI-powered real-time insights for smarter well delivery

by Anne Siw Uberg | May 5, 2025 | News

Home News Exebenus and Petrolink partner to deliver AI-powered real-time insights for smarter well delivery As energy operators face growing pressure to enhance drilling performance, minimize operational risk, and reduce overall well delivery costs, Exebenus and...

Dragon Oil and Exebenus sign MoU to advance AI in drilling operations

by Anne Siw Uberg | Apr 24, 2025 | News

Home News Dragon Oil and Exebenus sign MoU to advance AI in drilling operations Dragon Oil and Exebenus signs a Memorandum of Understanding (MoU) to advance AI in drilling operations Exebenus is honored to have been invited by Dragon Oil to enter into a Memorandum of...

Application of Predictive Machine-Learning Optimisation Enables Successful Delivery of Highly Challenging Wells

by Anne Siw Uberg | Apr 22, 2025 | Technical Papers

Home Technical Papers Application of Predictive Machine-Learning Optimisation Enables Successful Delivery of Highly Challenging Wells SPE-224618-MS: O. Al-Farisi, I. Guenaga, R. Singhal, M. Hayes, Dragon Oil; M. Regan, Exebenus Abstract: In this paper a case...

Recent Posts

  • Exebenus showcases breakthrough in real-time, context-aware AI at SPE ATCE 2025
  • Modular framework integrating large language models with drilling hazard detection systems to provide operational context-informed interpretations and recommended actions
  • 53 hours too late: How early warnings could have prevented stuck pipe and three days of NPT
  • System for Real-Time Rate of Penetration Optimization Using Machine Learning with Integrated Preventive Safeguards Against Hole Cleaning Issues and Stick-Slip
  • Predictive ML insights helps avoid stuck pipe by guiding real-time rig actions

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