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Title: Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications

Abstract

Achieving a representative elementary volume (REV) has become a de facto criterion for demonstrating the quality of {mu}CT measurements in porous media systems. However, the data quality implications of an REV requirement have not been previously examined. In this work, deterministic REVs for porosity, moisture saturation (S{sub W}), and air-water interfacial area (A{sub I}) were estimated using a set of 49 {mu}CT images of eight unsaturated homogeneous porous media with heterogeneity in moisture distributions present in varying degrees. Estimated porosity REVs were <8 mm{sup 3} for all cases, smaller than typical CT image sizes ({approx}100 mm{sup 3}). Estimated S{sub W} and A{sub I} REVs were <55 mm{sup 3} for cases with homogeneous moisture distributions but could not be estimated for cases with heterogeneous moisture distributions, due to the absence of a distinct 'REV plateau' within the maximum imaged volume. Conventionally, S{sub W} and A{sub I} data from such non-REV cases would be excluded. The implications of excluding data on the basis of REV were examined by comparing A{sub I}-S{sub W} data measured on image windows of increasing size against the expected linear A{sub I}-S{sub W} relationship. At measurement scales exceeding porosity REV, random fluctuations in A{sub I}-S{sub W} data weremore » excluded, even for cases containing heterogeneous moisture distributions. In contrast, requiring measurement scales to exceed S{sub W} and A{sub I} REV appeared overly restrictive and resulted in visible loss of reliable A{sub I}-S{sub W} data. We attribute these findings to overestimation of REVs due to inherently problematic estimation of deterministic REVs in real systems. Implications of these findings for ensuring CT data quality and the efficient use of CT data are discussed.« less

Authors:
; ;  [1]
  1. (Middlebury College)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
Sponsoring Org.:
National Science Foundation (NSF)
OSTI Identifier:
1018858
Resource Type:
Journal Article
Journal Name:
Water Resour. Res.
Additional Journal Information:
Journal Volume: 47; Journal Issue: 2011; Journal ID: ISSN 0043-1397
Country of Publication:
United States
Language:
ENGLISH
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; FLUCTUATIONS; MOISTURE; POROSITY; SATURATION; WINDOWS

Citation Formats

Costanza-Robinson, Molly S., Estabrook, Benjamin D., and Fouhey, David F. Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications. United States: N. p., 2011. Web. doi:10.1029/2010WR009655.
Costanza-Robinson, Molly S., Estabrook, Benjamin D., & Fouhey, David F. Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications. United States. doi:10.1029/2010WR009655.
Costanza-Robinson, Molly S., Estabrook, Benjamin D., and Fouhey, David F. Fri . "Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications". United States. doi:10.1029/2010WR009655.
@article{osti_1018858,
title = {Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications},
author = {Costanza-Robinson, Molly S. and Estabrook, Benjamin D. and Fouhey, David F.},
abstractNote = {Achieving a representative elementary volume (REV) has become a de facto criterion for demonstrating the quality of {mu}CT measurements in porous media systems. However, the data quality implications of an REV requirement have not been previously examined. In this work, deterministic REVs for porosity, moisture saturation (S{sub W}), and air-water interfacial area (A{sub I}) were estimated using a set of 49 {mu}CT images of eight unsaturated homogeneous porous media with heterogeneity in moisture distributions present in varying degrees. Estimated porosity REVs were <8 mm{sup 3} for all cases, smaller than typical CT image sizes ({approx}100 mm{sup 3}). Estimated S{sub W} and A{sub I} REVs were <55 mm{sup 3} for cases with homogeneous moisture distributions but could not be estimated for cases with heterogeneous moisture distributions, due to the absence of a distinct 'REV plateau' within the maximum imaged volume. Conventionally, S{sub W} and A{sub I} data from such non-REV cases would be excluded. The implications of excluding data on the basis of REV were examined by comparing A{sub I}-S{sub W} data measured on image windows of increasing size against the expected linear A{sub I}-S{sub W} relationship. At measurement scales exceeding porosity REV, random fluctuations in A{sub I}-S{sub W} data were excluded, even for cases containing heterogeneous moisture distributions. In contrast, requiring measurement scales to exceed S{sub W} and A{sub I} REV appeared overly restrictive and resulted in visible loss of reliable A{sub I}-S{sub W} data. We attribute these findings to overestimation of REVs due to inherently problematic estimation of deterministic REVs in real systems. Implications of these findings for ensuring CT data quality and the efficient use of CT data are discussed.},
doi = {10.1029/2010WR009655},
journal = {Water Resour. Res.},
issn = {0043-1397},
number = 2011,
volume = 47,
place = {United States},
year = {2011},
month = {9}
}