Tensor-based reduced order modeling in reservoir engineering : an application to production optimization

Edwin Insuasty Moreno, Paul Van den Hof, Siep Weiland, Jan-Dirk Jansen

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
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Abstract

In this paper, a novel framework for reduced order modeling in reservoir engineering is introduced, where tensor decompositions and representations of flow profiles are used to characterize empirical features of flow simulations. The concept of classical Galerkin projection is extended to perform projections of flow equations onto empirical tensor subspaces, generating in this way, reduced order approximations of the original mass and momentum conservation equations. The methodology is applied to compute gradient-based optimal production strategies for water flooding using tensor-based reduced order adjoints
Original languageEnglish
Pages (from-to)254-259
JournalIFAC-PapersOnLine
Volume48
Issue number6
DOIs
Publication statusPublished - 27 May 2015
Event2nd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production (OOGP 2015), May 27-29, 2015, Florianópolis, Brazil - Florianópolis, Brazil
Duration: 27 May 201529 May 2015
http://www.ifac-oilfield.ufsc.br/

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