Exebenus
  • Home
  • Products
    • Exebenus Spotter
      • Stuck Pipe Agent
      • ROP Agent
      • Vibration Agent
    • Exebenus Pulse
      • Build
      • Run
  • Resources
  • News & Insights
  • About us
Select Page

Modular framework integrating large language models with drilling hazard detection systems to provide operational context-informed interpretations and recommended actions

by Anne Siw Uberg | Oct 17, 2025 | Technical Papers

Home Technical Papers Modular framework integrating large language models with drilling hazard detection systems to provide operational context-informed interpretations and recommended actions SPE-227906-MS: S. Suhail, T.S Robinson, O. E. Revheim, P. Bekkeheien,...

System for Real-Time Rate of Penetration Optimization Using Machine Learning with Integrated Preventive Safeguards Against Hole Cleaning Issues and Stick-Slip

by Anne Siw Uberg | May 20, 2025 | Technical Papers

Home Technical Papers System for Real-Time Rate of Penetration Optimization Using Machine Learning with Integrated Preventive Safeguards Against Hole Cleaning Issues and Stick-Slip SPE-223713-MS: T.S Robinson, P. Mohammed Arshad, O. E. Revheim, M. Regan, P....

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...

Enhancing Stuck Pipe Risk Detection in Exploration Wells Using Machine Learning Based Tools: A Gulf of Mexico Case Study

by exebenus-admin-2025 | Mar 6, 2024 | Technical Papers

Home Technical Papers Enhancing Stuck Pipe Risk Detection in Exploration Wells Using Machine Learning Based Tools: A Gulf of Mexico Case Study SPE-217963-MS: D. Gomes (Exebenus), T. Jaritz (Wintershall Dea), T. S. Robinson (Exebenus), and O. E. Revheim (Exebenus)...

Drilling In The Digital Age: Case Studies Of Field Testing A Real-time ROP Optimization System Using Machine Learning

by exebenus-admin-2025 | Jan 19, 2024 | Technical Papers

Home Technical Papers Drilling In The Digital Age: Case Studies Of Field Testing A Real-time ROP Optimization System Using Machine Learning SPE-214521-MS:Al-Riyami (Exebenus), O. Revheim (Exebenus), T. S. Robinson (Exebenus), P. Batruny (PETRONAS Carigali), M. H. Meor...

Leveraging Targeted Machine Learning for Early Warning and Prevention of Stuck Pipe, Tight Holes, Pack Offs, Hole Cleaning Issues and Other Potential Drilling Hazards

by exebenus-admin-2025 | May 12, 2023 | Technical Papers

Home Technical Papers Leveraging Targeted Machine Learning for Early Warning and Prevention of Stuck Pipe, Tight Holes, Pack Offs, Hole Cleaning Issues and Other Potential Drilling Hazards OTC-32169-MS:Tim S. Robinson (Exebenus), Vlad K. Payrazyan (Exebenus) Abstract:...
« Older Entries

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

Recent Comments

No comments to show.
Quicklinks

Exebenus Spotter

Exebenus Pulse

Resources

News & Insights

About us

Contact info

+47 917 63 400

info@exebenus.com

 

Copyright © Exebenus AS. All rights reserved.

Exebenus General Privacy Statement