TY - JOUR
T1 - Control-Oriented Modeling for Managed Pressure Drilling Automation Using Model Order Reduction
AU - Lordejani, Sajad Naderi
AU - Besselink, Bart
AU - Abbasi, Mohammad Hossein
AU - Kaasa, Glenn Ole
AU - Schilders, Wil H.A.
AU - Van De Wouw, Nathan
N1 - Funding Information:
Manuscript received October 2, 2019; revised March 9, 2020; accepted April 13, 2020. Date of publication May 25, 2020; date of current version April 12, 2021. Manuscript received in final form May 11, 2020. This research has been carried out in the HYDRA Project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No. 675731. Recommended by Associate Editor S. Gumussoy. (Corresponding author: Sajad Naderi Lordejani.) Sajad Naderi Lordejani is with the Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands (e-mail: [email protected]).
Funding Information:
This research has been carried out in the HYDRA Project, which has received funding from the European Union's Horizon 2020 Research and Innovation Program under Grant Agreement No. 675731.
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2021/5
Y1 - 2021/5
N2 - Automation of managed pressure drilling (MPD) enables fast and accurate pressure control in drilling operations. The performance that can be achieved by automated MPD is determined by, first, the controller design and, second, the hydraulics model that is used as a basis for controller design. On the one hand, such hydraulics model should be able to accurately capture essential flow dynamics, for example, wave propagation effects, for which typically complex models are needed. On the other hand, a suitable model should be simple enough to allow for extensive simulation studies supporting scenario analysis and high-performance controller design well. In this paper, we develop a model order reduction approach for the derivation of such a control-oriented model for single-phase flow MPD operations. In particular, a nonlinear model order reduction procedure is presented that preserves key system properties such as stability and provides guaranteed (accuracy) bounds on the reduction error. To demonstrate the quality of the derived control-oriented model, comparisons with field data and both open-loop and closed-loop simulation-based case studies are presented.
AB - Automation of managed pressure drilling (MPD) enables fast and accurate pressure control in drilling operations. The performance that can be achieved by automated MPD is determined by, first, the controller design and, second, the hydraulics model that is used as a basis for controller design. On the one hand, such hydraulics model should be able to accurately capture essential flow dynamics, for example, wave propagation effects, for which typically complex models are needed. On the other hand, a suitable model should be simple enough to allow for extensive simulation studies supporting scenario analysis and high-performance controller design well. In this paper, we develop a model order reduction approach for the derivation of such a control-oriented model for single-phase flow MPD operations. In particular, a nonlinear model order reduction procedure is presented that preserves key system properties such as stability and provides guaranteed (accuracy) bounds on the reduction error. To demonstrate the quality of the derived control-oriented model, comparisons with field data and both open-loop and closed-loop simulation-based case studies are presented.
KW - Automatic control
KW - managed pressure drilling
KW - model order reduction
KW - modeling
KW - wave propagation
UR - http://www.scopus.com/inward/record.url?scp=85104350892&partnerID=8YFLogxK
U2 - 10.1109/TCST.2020.2994535
DO - 10.1109/TCST.2020.2994535
M3 - Article
AN - SCOPUS:85104350892
SN - 1063-6536
VL - 29
SP - 1161
EP - 1174
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 3
M1 - 9099213
ER -