Quantitative analysis of water-content estimation errors usi
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  • journal_title:Geophysics
  • Contributor:Bernard Giroux ; Michel Chouteau
  • Publisher:Society of Exploration Geophysicists
  • Date:2010-
  • Format:text/html
  • Language:en
  • Identifier:10.1190/1.3464329
  • journal_abbrev:Geophysics
  • issn:0016-8033
  • volume:75
  • issue:4
  • firstpage:WA241
  • section:SPECIAL SECTION - HYDROGEOPHYSICS - ELECTRIC AND ELECTROMAGNETIC METHODS
摘要

Expressions are derived to quantify the error when estimating permittivity that results from using the low-loss approximation under lossy conditions and to examine the repercussions on estimating water content θ. Values are computed under a range of porosity, clay-content, water-quality, and frequency conditions. Although in most cases the error is negligible, it can be significant for some hydrogeophysical applications involving cross-hole measurements or low-frequency surface ground-penetrating radar (GPR). For instance, when the loss tangent Formula equals 0.5, corresponding to an effective conductivity of Formula, a dielectric constantof 11, and a frequency of Formula, the relative error on dielectric permittivity is approximately 6%. If the conductivity doubles or the frequency is halved, the loss tangentdoubles but the error grows to 21%. In addition, considering a situation where the porosity is 20% and Formula, the use of the low-loss approximation leads to a 10% deviation from θ. In the context of water-content estimation, we therefore suggest to perform attenuation tomography, in addition to velocity tomography for crosshole data, or estimate the quality factor Q for surface GPR data to compute the loss tangent over the probed area. If proven necessary, the parameters sought can then be determined more accurately using a lossy formulation. We also propose to supplement GPR measurements with electrical-resistivity tomography to constrain the borehole GPR amplitude data-processing steps required by attenuation tomography or to complement the characterization of the survey area and improve the knowledge brought by Q estimates alone.

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