Model order reduction for managed pressure drilling systems based on a model with local nonlinearities

Research output: Contribution to journalConference articleAcademicpeer-review

Abstract

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.

LanguageEnglish
Pages50-55
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number8
DOIs
StatePublished - 1 Jan 2018

Fingerprint

Drilling
Hydraulic models
Control systems
Pressure control
Feedback
Controllers

Keywords

  • Automatic Control
  • Managed Pressure Drilling
  • Model Order Reduction
  • Modeling

Cite this

@article{fde504a4369c409c8ece05b503b329aa,
title = "Model order reduction for managed pressure drilling systems based on a model with local nonlinearities",
abstract = "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.",
keywords = "Automatic Control, Managed Pressure Drilling, Model Order Reduction, Modeling",
author = "S. Naderilordejani and B. Besselink and M.H. Abbasi and G.O. Kaasa and W.H.A. Schilders and {van de Wouw}, N.",
year = "2018",
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Model order reduction for managed pressure drilling systems based on a model with local nonlinearities. / Naderilordejani, S.; Besselink, B.; Abbasi, M.H.; Kaasa, G.O.; Schilders, W.H.A.; van de Wouw, N.

In: IFAC-PapersOnLine, Vol. 51, No. 8, 01.01.2018, p. 50-55.

Research output: Contribution to journalConference articleAcademicpeer-review

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AU - Schilders,W.H.A.

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AB - 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.

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