Abstract

With the recent advance in high speed data communication offered by wired drill pipe telemetry, several automated control systems directly utilize downhole data (e.g. vibration) to optimize drilling performance such as rate of penetration (ROP). With additional high-speed telemetry data such as pressure, it is possible to couple ROP and drilling hydraulics into a single controller for managed pressure drilling systems. This multivariate controller improves drilling performance during normal drilling operations and enhances safety during abnormal drilling conditions such as pipe connection procedures and with unwanted gas influx. These automation strategies rely on a foundation of stable and reliable measurements of critical drilling parameters. When high-speed telemetry to downhole measurements is unavailable then several automation applications degrade in performance, require use of soft sensors (predictive models), or revert to manual control. Incorporating the predictive capability of high-fidelity hydraulic and drill-string dynamic models into automation strategies is an active area of development. This presentation explores the intersection of varying degrees of model sophistication and changing measurement availability for managed pressure drilling automation. The objective is to maintain bit pressure within +/- 1 bar of the 400 bar set point during normal drilling operations despite temporary signal loss and poor data quality. Also, the bit pressure is held within +/- 5 bar of the 340 bar set point during a pipe connection procedure with no bit pressure measurements available to the controller. Additionally, the controller response to unexpected gas influx as a process disturbance is simulated. The ensemble approach is proposed to automatically switch between models and available measurements to achieve a higher degree of reliability and availability during common phases of drilling.

Short bio

John Hedengren is an Assistant Professor in the Department of Chemical Engineering at Brigham Young University. He received a PhD degree in Chemical Engineering from the University of Texas at Austin. Previously, he developed the APMonitor Optimization Suite and worked with ExxonMobil on Advanced Process Control for 5 years. His current research interests include drilling automation, fiber optic monitoring, Intelli-fields, reservoir optimization, unmanned aerial systems, and model predictive control.  He is a principal investigator of the Center for Unmanned Aircraft Systems (C-UAS) and applies UAV computer vision and optimization technology to energy and infrastructure monitoring. He is a member of the DSAT (Drilling Systems Automation Technical Section) committee of the Society of Petroleum Engineers (SPE), focusing on accelerating automation technology in the well drilling industry and has been an invited panelist to discuss emerging topics in automation. BP, ExxonMobil, Hess, Astro Technology, Apache Corp, SINTEF, Schlumberger, NOV, IRIS, and others have been active collaborators of the BYU PRISM group in developing upstream telemetry and automation.