Drilling Automation & Intelligent Operations provides an engineering-focused introduction to how drilling evolves from manual operation and mechanization into closed-loop control, connected operations, intelligent decision support, and bounded autonomy. The course begins with the human control functions of measurement, interpretation, decision, action, and verification, then develops the industrial automation foundation through sensors and I/O, controllers and PLCs, drives and actuators, HMI/SCADA, historians, industrial networking, OPC UA, WITSML/ETP, IIoT, edge and cloud computing, data timing, cybersecurity, and drilling-rig automation architecture. These concepts are then applied to workflow and rig-state management, WOB/RPM/ROP control, PID and model-predictive control, protection, fallback, and supervisory control.

Designed for drilling and well engineers, automation and digital professionals, drilling-performance personnel, and technical practitioners who need to understand how intelligent drilling systems actually work, the course progresses into physics-based models, digital twins, machine learning, AI and generative AI, drilling optimization, dysfunction detection, hole-cleaning and stuck-pipe intelligence, directional and workflow automation, application arbitration, and bounded autonomous execution. Commercial examples connect the architecture to current industry platforms while maintaining a vendor-neutral functional perspective. Participants will leave able to distinguish automation from autonomy, trace data and command authority through an automated drilling system, evaluate intelligent applications and their limitations, and design safer, more reliable automation strategies in which technology supports- rather than bypasses-engineering judgment and human accountability. The commercial-product chapter already explicitly adopts this educational, vendor-neutral framing.