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

Abstract

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.