4.7 Article

A note on variational multiscale methods for high-contrast heterogeneous porous media flows with rough source terms

期刊

ADVANCES IN WATER RESOURCES
卷 34, 期 9, 页码 1177-1185

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2010.12.011

关键词

Multiscale; High-contrast; Heterogeneous; Source; Variational multiscale; Multiscale finite element

资金

  1. King Abdullah University of Science and Technology (KAUST) [KUS-C1-016-04]
  2. DOE
  3. NSF [DMS 0934837, DMS0621113, DMS 0724704, DMR-0844082, DMS 0811180]
  4. Direct For Mathematical & Physical Scien
  5. Division Of Mathematical Sciences [0934837] Funding Source: National Science Foundation
  6. Direct For Mathematical & Physical Scien
  7. Division Of Mathematical Sciences [0811180] Funding Source: National Science Foundation

向作者/读者索取更多资源

In this short note, we discuss variational multiscale methods for solving porous media flows in high-contrast heterogeneous media with rough source terms. Our objective is to separate, as much as possible, subgrid effects induced by the media properties from those due to heterogeneous source terms. For this reason, enriched coarse spaces designed for high-contrast multiscale problems are used to represent the effects of heterogeneities of the media. Furthermore, rough source terms are captured via auxiliary correction equations that appear in the formulation of variational multiscale methods [23]. These auxiliary equations are localized and one can use additive or multiplicative constructions for the subgrid corrections as discussed in the current paper. Our preliminary numerical results show that one can capture the effects due to both spatial heterogeneities in the coefficients (such as permeability field) and source terms (e.g., due to singular well terms) in one iteration. We test the cases for both smooth source terms and rough source terms and show that with the multiplicative correction, the numerical approximations are more accurate compared to the additive correction. (C) 2010 Elsevier Ltd. All rights reserved.

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