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

Onderzoeksoutput: Bijdrage aan tijdschriftCongresartikelpeer review

1 Citaat (Scopus)
3 Downloads (Pure)

Samenvatting

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
Originele taal-2Engels
Pagina's (van-tot)254-259
TijdschriftIFAC-PapersOnLine
Volume48
Nummer van het tijdschrift6
DOI's
StatusGepubliceerd - 27 mei 2015
Evenement2nd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production (OOGP 2015), May 27-29, 2015, Florianópolis, Brazil - Florianópolis, Brazilië
Duur: 27 mei 201529 mei 2015
http://www.ifac-oilfield.ufsc.br/

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