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Title: A Parallel Stochastic Framework for Reservoir Characterization and History Matching

The spatial distribution of parameters that characterize the subsurface is never known to any reasonable level of accuracy required to solve the governing PDEs of multiphase flow or species transport through porous media. This paper presents a numerically cheap, yet efficient, accurate and parallel framework to estimate reservoir parameters, for example, medium permeability, using sensor information from measurements of the solution variables such as phase pressures, phase concentrations, fluxes, and seismic and well log data. Numerical results are presented to demonstrate the method.
Authors:
 [1] ;  [2] ;  [2] ;  [3]
  1. Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA, Chevron ETC, San Ramon, CA 94583, USA
  2. Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA, ConocoPhillips, Houston, TX 77252, USA
  3. Institute for Computational Engineering and Sciences, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712, USA, Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA
Publication Date:
OSTI Identifier:
1235382
Grant/Contract Number:
FGO2-04ER25617; SC0001114
Type:
Published Article
Journal Name:
Journal of Applied Mathematics
Additional Journal Information:
Journal Volume: 2011; Related Information: CHORUS Timestamp: 2016-08-04 11:35:30; Journal ID: ISSN 1110-757X
Publisher:
Hindawi Publishing Corporation
Sponsoring Org:
USDOE
Country of Publication:
Country unknown/Code not available
Language:
English