COURSE OVERVIEW

This practical and highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 

 

This course is designed to provide participants with a detailed and up-to-date overview of Artificial Intelligence in Drilling Engineering. It covers the Al-driven data analytics for drilling operations and machine learning for drilling optimization; the Al for well planning and trajectory optimization; the drill bit selection and performance optimization; the Al-enabled real-time drilling monitoring, predictive drilling performance analysis and drilling fluid optimization; and the Al for early kick detection and well control, downhole tool optimization and automated drilling rig operations.  

 

Further, the course will also discuss the Al for drilling equipment health monitoring, Al-driven robotic drilling systems, automated mud logging and cutting analysis; the digital twins in drilling and the Al for predictive modeling of downhole conditions and Al-powered decision support systems; the Al for drilling risk assessment and hazard detection, well integrity monitoring and enhanced blowout prevention and control; and the Al for environmental monitoring in drilling operations and Al for offshore drilling operations.  

 

During this interactive course, participants will learn the Al trends and innovations in drilling engineering and Al for intelligent decision-making in drilling; the Al-powered loT sensors for real-time monitoring and Al driven real-time drilling parameter adjustment; the Al-powered cost optimization in drilling and Al for reducing non-productive time (NPT); and the Al-driven predictive scheduling of drilling operations and Al for optimizing drilling fluids and material consumption.