Exebenus AS, a leading provider of AI-driven solutions for the oil and gas industry, and Kongsberg Digital, a leading industrial software company, are thrilled to announce a strategic partnership that will deliver significant cost savings and efficiency to oil and gas operations.
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!
Location Gabon, West Africa Ultra deepwater Challenge Show that real-time rate of penetration (ROP) optimization can signifi cantly contribute to improving ROP, decreasing drilling time and reducing costs, even when an auto driller is used. Solution The agent was used by RTO engineers to provide the rig crew with real-time drilling parameter recommendations for optimizing…
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.
In the O&G industry, drilling is a complex and challenging process that requires advanced technology and expertise. One of the critical challenges that drilling teams face is the risk of stuck pipe incidents, which can cause significant delays and cost overruns.