Cloud-Based Real-Time Well Engineering: Coupling Torque-And-Drag and Uncertainty Modeling

Abstract

Surface hookload and torque values serve as good indicators for some undesirable scenarios or anomalies during drilling, such as stuck pipe, buckling, and inadequate hole cleaning. However, to detect these risks, it requires drilling engineers to perform the friction factor calibration manually and regularly, which costs more effort and poses significant uncertainties on the detection. In this paper, a cloud-based real-time well engineering webapp has been developed to monitor and forecast tripping frictions and drilling performance. Results of field tests were presented to prove the successful testing of this cloud- based real-time workflow. Real-time hookload and torque values were streamed smoothly to the web application interface. Rig activity, friction factor, and mechanical specific energy (MSE) were also evaluated and displayed in real-time with predicted uncertainty zone. It has been demonstrated that this cloud-based web application supports a multi-tenancy architecture and multiple wells can stream simultaneously with no down time. This new workflow made it possible for drilling engineers to monitor live drilling wells anywhere and anytime while enabling the rig personnel to make significant improvements to operations and make timely and accurate decisions.