An Intelligent Risk-Based Monitoring System for Safer and More Efficient Drilling Operations

Abstract

The oil and gas sector is currently experiencing a reduction in available skilled personnel, driven by an aging workforce, evolving energy priorities, pandemic-related impacts, and geopolitical factors. In real-time operations centers (RTOCs), this challenge is compounded by the demanding nature of continuous drilling surveillance, where engineers typically oversee only three to five wells simultaneously. Sustained monitoring requires high cognitive focus, often limited to a few effective hours per shift, and is further strained by extended rotations of 28 to 42 days, night shifts, and open-office environments. These conditions can reduce situational awareness and delay hazard detection, directly impacting safety, increasing operational risk, and potentially compromising rig safety. This highlights the need for more efficient, safety-focused, and scalable monitoring solutions. To address these limitations, an integrated digital framework combining planning and real-time engineering capabilities has been developed with a strong emphasis on safety and risk reduction. The system incorporates physics-based models, including hydraulics, torque and drag, and geo-pressure models, alongside continuous access to sensor data, model outputs, and user-defined calculations. Advanced mathematical functions and condition-based logic enable automated workflows, including rig state detection and event-triggered actions. Customizable true/false criteria allow the system to evaluate operational conditions dynamically, supporting proactive hazard detection and reducing risk exposure. Predefined notifications are automatically transmitted to end users when specific thresholds or anomalies are identified. The implemented solution introduces a drilling hazard detection workflow powered by a risk indicator algorithm and automated alert system. The platform generates smart alerts when predefined thresholds are exceeded, providing early warnings of potential safety-critical issues such as inefficient hole cleaning, elevated torque and drag, or wellbore instability. Each alert is associated with a quantified risk level, enabling engineers to prioritize attention across multiple wells and take timely corrective actions. This approach enhances situational awareness, strengthens hazard detection capabilities, and improves rig safety by converting large volumes of real-time data into clear, actionable safety insights. Field implementation demonstrates a significant improvement in operational efficiency and safety performance. With the same number of engineers, the number of wells being monitored increased from 24 to 36, representing a 50% gain in coverage. Assuming an average annual cost of $120,000–$150,000 per RTOC engineer, this improvement corresponds to an estimated cost avoidance of approximately $720,000 to $900,000 per year for a six-engineer team, while maintaining high safety standards. Additionally, less experienced engineers were able to double their monitoring capacity from two to four wells without compromising hazard detection effectiveness. The system enables earlier identification of drilling hazards through visual and automated alerts, simplifies interpretation using a unified indicator, and reduces manual workload through automation. Its flexible, condition-based design eliminates the need for hard-coded logic, allowing rapid customization to different operational environments while reinforcing safety, reducing risk, and enhancing overall rig safety performance.