Machine learning agents for stuck-pipe prevention and ROP optimization.
Exebenus Spotter machine learning agents enable real-time drilling optimization and alert monitoring teams to stuck-pipe risks.
Digital operating procedures and real time activity validation.
Exebenus Pulse generates digital operating procedures, standardization based on best practices and active risk management. Real-time activity validation ensures adherence to plan and provides real-time records of planned vs actual activities.
If you are a player in the oil and gas industry today, you are already on the road toward digitalization. Our experts will guide you through the process, one manageable step at a time.
In this free webinar, Jan Kare Igland will explore the ML-driven ROP optimization solution capabilities and field test results from two offshore drilling operations in West Africa and Southeast Asia, where live recommendations by ML application were applied by rig crews to assess real-world effectiveness in improving ROP. Register for the webinar here!
On the conference 2nd day, on the 15th of September, Jan Kåre Igland will present “Case Studies and Results from 2.5 Years of Using Targeted Machine Learning Models to Predict Stuck Pipe Incidents”.
Join us for an insightful webinar on Case Studies of Automated Detection of Drilling Hazards with Machine Learning applications.