Abstract

Abstract High accuracy, speed, and a low false alarm rate are critical to the success of event detection systems and the reduction of non-productive time (NPT) due to unplanned events. The balance between them has been difficult to achieve; however, the application of a probabilistic approach with the use of Bayesian methods has shown significant promise. The results of a research prototype for kick detection using such methods were described in a previous paper (Hargeaves, Jardine, Jeffryes, 2001). The improvements in automated signal processing technology and increased computer power have meant that these new approaches to large scale data analysis in real time are now more widely possible. This paper describes the extension of this work to develop a rig-based quick event detection (QED) system for mitigating a number of common drilling risks, including kicks, circulation loss, and drillstring washout detection. The QED software application runs on a standard standalone PC at the wellsite and continuously calculates the probability that an event is occurring. The probability changes as an event occurs, which may trigger an alarm. The system continues to evaluate the event as the real-time data is updated and this evaluation provides the drilling team with a continuously evolving probability that the event is occurring. This system helps the team make timely, informed decisions. The system requires minimal hands-on interaction to set up and uses data input via WITS for flow-in and flow-out measurements from typical rig sensors. The detection of drilling problems in real time using the QED software on several Integrated Project Management well construction projects is presented, including the lessons learned from deploying the technology in field operations. The significance of this development is to mitigate drilling risks during well construction projects, where minimizing NPT due to unplanned events is critical to success.

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