SPE Distinguished Lecturer Presentation at DTU Glassalen

Well construction is currently being challenged to become more sustainable while reducing the skill sets needed to have efficient and consistent directional drilling operations. Challenges related to directional drilling include encountering constantly changing formations, steering responses, planned trajectories difficult to follow perfectly, drilling data having huge uncertainties, especially the continuous measurements being affected by shock and vibrations, navigating efficiently into the reservoir for enhanced production capabilities, ever changing conditions between one well to another. These challenges often require significant human skillsets to become an efficient directional driller; and skillful directional drillers, who make the best directional decisions, are difficult to deliver for service companies and operators and becoming even more difficult as time goes.

 

The proposed topic is to highlight the technical challenges involved in providing an AI system to perform autonomous directional drilling. The AI system includes a continuous feedback loop between surface and downhole controllers to always make optimized decision. In addition to complex sensor fusion for the best state estimation, an optimization engine outputs the best candidate trajectory at each decision point. Several enhancements were necessary to move from advisory to control. The system has been made much more resilient to unexpected measurement-while-drilling (MWD) telemetry or downlink issues. the system’s surface deviation controller actively monitors continuous data and takes the appropriate course of actions to rectify unplanned situations without overreacting.

 

Samba has over 20 years’ experience in drilling and drilling related technologies. He received a first Masters degree from the renown Ecole Polytechnique in France in 2001 with a major in Applied mathematics. He also holds a diplome des Grandes Ecoles from the Ecole National des Ponts et Chaussees and a DEA from the University Pierre et Marie Curie in Paris VI. He has worked in a bank as a mathematician for one year and then joined Schlumberger in 2004. He has worked in the field for the Drilling and Measurement segment as Measurement While Drilling (MWD), Logging While Drilling (LWD) and then Directional Driller (DD) up to 2006, before joining Schlumberger Cambridge Research (SCR) in Cambridge, United Kingdom as a research scientist, where he spent around 6.5 years on drilling related research. He then worked as a project Manager at the newly created (in 2012) Schlumberger Motor Center of Excellence in Katy, USA from 2012 to 2019. From 2019 to 2023, he was a domain solution architect, developing AI solutions for autonomous drilling while being based at Beijing Geoscience Center in China. Since 2023, he returned to Houston working on AI autonomous solution to help reach the highest level of drilling autonomy. His main interests are in applied engineering, drilling technologies and innovative digital solutions. In 2025, he was selected to become a board director for the Schlumberger Foundation supporting women pursue STEM education for developing countries.