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TitleCapacitive resistivity inversion using effective dipole lengths for line antennas
AuthorOldenborger, G AORCID logo; LeBlanc, A -MORCID logo
SourceJournal of Applied Geophysics vol. 98, 2013 p. 229-236,
Alt SeriesEarth Sciences Sector, Contribution Series 20130095
PublisherElsevier BV
Mediapaper; on-line; digital
File formatpdf
Lat/Long WENS-68.5000 -68.0000 63.7500 63.5000
Subjectsgeophysics; Nature and Environment; resistivity; resistivity interpretations; electrical resistivity; permafrost; freezing ground; ground ice
Illustrationslocation maps; plots; models; histograms
ProgramClimate Change Geoscience
Released2013 11 01
AbstractNon-contacting capacitively-coupled resistivity (CCR) surveys find application in permafrost investigations and investigations over engineered surfaces. However, we observe discrepancies between line-antenna CCR data and galvanic resistivity (GR) data. Inverse models recovered from the different data types exhibit differences in both resistivity magnitude and structure. We apply and test the concept of effective dipole length for lineantenna CCR data collected over permafrost terrain in Iqaluit, Nunavut. We compare inversions of corrected CCR data to the GR counterpart. Results show that correcting CCR data with an effective dipole length of 80% of the physical antenna length results in a resistivitymodel most in accordancewith the GRmodel. After correction, the CCR model does not precisely emulate the GRmodel; potential sources of remaining discrepancy are incomplete representation of the line-antenna nature of the CCR data and the realities of field data acquisition including significantly different noise levels and the potential violation of CCR operating conditions.
Summary(Plain Language Summary, not published)
Non-contacting capacitively-coupled resistivity (CCR) surveys find application in permafrost investigations and investigations over engineered surfaces such as at Iqaluit International Airport, Nunavut. CCR geophysical surveys are useful for mapping geological and permafrost terrain units, and for estimating their subsidence potential associated with permafrost degradation. Subsidence can have significant detrimental impacts on land-based infrastructure. We examine the accuracy of CCR data and test a hypothesis for improving the reliability of models generated from these data. Simple manipulation of the CCR data results in models that are more consistent with other data sets. Results allow for better estimation of material properties (subsidence potential) and better comparison of data over a regional area.

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