Algorithms to Automate the Drilling Monitoring Process
January 1, 2012Shell International Exploration & Production Inc. Mathematics, 2011-12
Liaison(s): Don Sitton, Jose Mota ’95
Advisor(s): Talithia Williams
Students(s): Emil Guliyev, Lindsay Hall (PM), Brandon Wei, Rebecca Young
In 2002, Shell Oil began monitoring real-time drilling data from offshore rigs in order to detect and respond to potential problems as early as possible. In this project, we aim to design and implement an algorithm which monitors key drilling parameters in real time, automatically detects abnormal behavior, and alerts rig monitors of potential issues. This algorithm is intended to assist rig monitors in detecting deviating trends in drilling data and recognizing impending issues quickly.