Improving the computational efficiency of approximate gradients using a multiscale reservoir simulation framework

Rafael Jesus de Moraes, Rahul Fonseca, M. Helici, Arnold Heemink, Jan Dirk Jansen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

22 Downloads (Pure)

Abstract

In this work, the application of tensor methodologies for computer-assisted history matching of channelized reservoirs is explored. A tensor-based approach is used for the parameterization of petrophysical parameters to reduce the dimensionality of the parameter estimation problem. Building on the work of Afra and Gildin (2013); Afra et.al. (2014); Afra and Gildin (2016), permeability fields of multiple model realizations are collected in a tensor form which is subsequently decomposed to derive a low-dimensional representation of the dominant spatial structures in the models. This representation then is used to estimate an identifiable reduced set of parameters using an ensemble Kalman filter (EnKF) strategy. This approach is attractive for the parameter estimation of permeabilities because it increases the ability to represent channelized structures in the updates resulting in an improved predictive capacity of the history-matched models. In particular, channel continuity is better preserved than with a Principal Component Analysis (PCA) parameterization.
Original languageEnglish
Title of host publicationSPE Reservoir Simulation Conference
Subtitle of host publicationMontgomery, Texas, USA
PublisherSPE
Number of pages20
DOIs
Publication statusPublished - 2017
EventSPE Reservoir Simulation Conference - Conference Center at La Torretta, Montgomery, United States
Duration: 20 Feb 201722 Feb 2017
Conference number: 23
http://www.spe.org/events/en/2017/conference/17rsc/about-the-conference.html

Conference

ConferenceSPE Reservoir Simulation Conference
Abbreviated titleRSC 2017
Country/TerritoryUnited States
CityMontgomery
Period20/02/1722/02/17
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Fingerprint

Dive into the research topics of 'Improving the computational efficiency of approximate gradients using a multiscale reservoir simulation framework'. Together they form a unique fingerprint.

Cite this