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Reduced basis method for managed pressure drilling based on a model with local nonlinearities
Author(s) -
Abbasi Mohammad Hossein,
Iapichino Laura,
Naderi Lordejani Sajad,
Schilders Wil,
Wouw Nathan
Publication year - 2020
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.6362
Subject(s) - model order reduction , nonlinear system , context (archaeology) , computer science , basis (linear algebra) , control theory (sociology) , drilling , reduction (mathematics) , controller (irrigation) , speedup , control engineering , simulation , engineering , algorithm , mechanical engineering , mathematics , control (management) , artificial intelligence , parallel computing , geology , geometry , projection (relational algebra) , paleontology , agronomy , physics , quantum mechanics , biology
To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single‐phase flow processes can be modeled as a feedback interconnection of a high‐order linear system and a low‐order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real‐time purposes (eg, online model‐based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced‐order model can be used for efficient online simulation and controller design for drilling systems with MPD.