Exebenus is a US-Norwegian company 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, ROP optimization and others. The offered solution is an automated plug-and-play web application that takes 5-20 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.
The Machine Learning solution that 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 Spotter 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 being difficult to access, to an everyday "wrench" tool. The system is easy to use, reliable, scalable, robust against false alarms and affordable.
"Why would you ever drill a well without an application that can predict getting a stuck pipe 1-4 hours in advance ? Its like driving a car without the ABS or any other safety system." - senior drilling engineer, US Permian
