Stochastic modeling of the permeability of randomly generated porous media

Yusong Li, Eugene J. LeBoeuf, P. K. Basu, Sankaran Mahadevan

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Permeability of porous media in subsurface environments is subject to potentially large uncertainties due to the heterogeneity of natural systems. In this study, a first-order reliability method (FORM) is combined with a lattice Boltzmann method (LBM) to estimate the permeability of randomly generated porous media. The proposed procedure provides an increased ease of addressing complex pore structures by employing LBM to model fluid flow, while inheriting the computational efficiency from FORM. Macroscale-equivalent permeability can thus be estimated with significantly reduced computational efforts, while maintaining a connection to the complex microscale fluid dynamics within a pore structure environment. Implemented on several randomly generated porous media domains, the proposed method provides 13-120 times the efficiency compared to Monte Carlo methods.

Original languageEnglish (US)
Pages (from-to)835-844
Number of pages10
JournalAdvances in Water Resources
Issue number8
StatePublished - Aug 2005
Externally publishedYes


  • First order reliability method
  • Lattice Boltzmann method
  • Permeability
  • Porous media
  • Stochastic modeling

ASJC Scopus subject areas

  • Water Science and Technology


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