Enhancing Stuck Pipe Risk Detection in Exploration Wells Using Machine Learning Based Tools: A Gulf of Mexico Case Study AbstractBy ExebenusMarch 6, 2024Prepared with Wintershall Dea
Drilling In The Digital Age: Case Studies Of Field Testing A Real-time ROP Optimization System Using Machine Learning AbstractBy ExebenusJanuary 19, 2024Prepared with Petronas
Leveraging Targeted Machine Learning for Early Warning and Prevention of Stuck Pipe, Tight Holes, Pack Offs, Hole Cleaning Issues and Other Potential Drilling Hazards AbstractBy ExebenusFebruary 12, 2023Prepared with Petronas
Unsupervised machine learning: A well planning tool for the future AbstractBy ExebenusJune 2, 2022Prepared with Petronas
Case Studies for the Successful Deployment of Wells Augmented Stuck Pipe Indicator in Wells Real Time Centre AbstractBy ExebenusJune 2, 2022Prepared with Petronas
Application of Machine Learning to Augment Wellbore Geometry-Related Stuck Pipe Risk Identification in Real Time AbstractBy ExebenusMarch 18, 2022Prepared with Petronas
Digitalized Operation Procedures Provide Rig Automation System With Context To Manage Longer And Broader Sequences Of Activities AbstractBy ExebenusFebruary 25, 2022Prepared with Petronas
Real-time Estimation Of Downhole Equivalent Circulating Density (ECD) Using Machine Learning And Applications AbstractBy ExebenusFebruary 24, 2022Prepared with Petronas
Successful Development and Deployment of a Global ROP Optimization Machine Learning Model AbstractBy ExebenusFebruary 24, 2022Prepared with Petronas
Automated Detection of Rig Events From Real-time Surface Data Using Spectral Analysis and Machine Learning AbstractBy ExebenusJanuary 23, 2022By Exebenus