Automated Managed Pressure Drilling Research Articles

Model Order Reduction for Managed Pressure Drilling Systems based on a Model with Local Nonlinearities

Automated Managed Pressure Drilling (MPD) is a method for fast and accurate pressure control in drilling operations. The achievable performance of automated MPD is limited, firstly, by the control system and, secondly, by the hydraulics model based on which this control system is designed. Hence, an accurate hydraulics model is needed that, at the same time, is simple enough to allow for the use of high performance controller design methods. This paper presents an approach for nonlinear Model Order Reduction (MOR) for MPD systems. For a single-phase flow MPD system, a nonlinear model is derived that can be decomposed into a feedback interconnection of a high-order linear subsystem and low-order nonlinear subsystem. This structure, under certain conditions, allows for a nonlinear MOR procedure that preserves key system properties such as stability and provides a computable error bound. The effectiveness of this MOR method for MPD systems is illustrated through simulations.

Design and Experimental Validation of Nonlinear Infinite-Dimensional Adaptive Observer in Automated Managed Pressure Drilling

Utilizing flow rate and pressure data in and out of the fluid circulation loop provides a driller with real-time trends for early detection of well-control problems that impact the drilling efficiency. Due to limited number of sensors and time delay in processing and measurements, the flow rate and pressure along the annulus and drill string need to be estimated. This paper presents state and parameter estimations for infinite-dimensional models used in automated managed pressure drilling (MPD). The objective is to monitor the key process variables associated with process safety by designing a nonlinear adaptive observer that use the available information coming from the continuous-time online process measurements at the outlet of the well. The adaptive observer consists of a copy of the infinite-dimensional model plus output injection terms where the gain is computed analytically in terms of the Bessel function of the first kind. The design is tested using field data from a drilling commissioning test by Statoil ASA, Stavanger, Norway. The results show that the nonlinear adaptive observer estimates the flow rate and pressure of the drilling fluid accurately.