Cloud-Based Real-Time Well Engineering: An Intelligent and Modular Multi-Engineering Modeling and Prediction

Abstract

Abstract Nowadays, the increasing drilling difficulties due to limited access to conventional reservoirs and high drilling costs put extra emphasis on drilling performance and safety. The advancement of real-time measurements and cloud computing make it possible to automate the monitoring, detection, and prediction processes, therefore trigger alarms before drilling issues even occur. In this paper, a scalable cloud-based real-time well engineering system was developed to monitor and forecast drilling operations by integrating multiple drilling model workflows such as torque and drag modeling, bit wear prediction, early kick loss prediction, hydraulics, swab and surge, anti-collision, stuck pipe avoidance. As demonstrated, this workflow can efficiently handle large and complex datasets in real-time and make real-time analysis and predictions. Moreover, this can be scaled up to support more users and wells. This cloud-based architecture makes it easier for the development team to apply hotfixes or major releases with no down time, and this new workflow makes it possible for drilling engineers to monitor live drilling wells anywhere and anytime while enabling the rig personnel to make significant improvement to operations and make timely and accurate decisions.