Exebenus is a US-Norwegian company with 40+ drilling engineers and data scientists, focused on developing real-time machine learning applications (agents) to address critical drilling NPT and ILT issues. Targeted machine learning algorithms each work on specific problems, such as mechanical sticking, differential sticking, hole cleaning, washouts, mud losses, bit degradation, motor/tool failure, ROP optimization and others. The offered solution is an automated plug-and-play web application that takes about 20 min to set it up on your next well. It is WITSML vendor-agnostic, with no need for the models to be pre-trained on offset data and no back-office engineering support required.
 
Machine Learning we apply is based on proprietary, new generation and physics informed algorithms that consistently deliver over 90% precision metric on any wells: onshore or offshore, conventional or unconventional, horizontal or vertical. 

The Exebenus Current ML machine learning agents enable real-time predictive situational awareness during oilfield operations, providing drilling engineers with pragmatic, manageable and easy-to-use instruments to significantly reduce downtime and increase drilling performance. 

We are transforming Machine Learning from "rocket science" to an everyday "wrench" tool. It is easy, reliable, scalable, "false alarms" proof and affordable. 
 
"Why would you ever drill a well without an application that can predict getting a stuck pipe 1-4 hours in advance ? It's like driving a car without the ABS or any other safety system." - senior drilling engineer, US Permian

AI/ML

Automation

Energy

Fuel

Software

Exebenus

Olav Revheim

Tim Robinson

Stine Tuxen

Nabil Al-Riyami

Mats Hermansen

Paal Bekkeheien

Exebenus

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