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• W3034453359 startingPage "E153" @default.
• W3034453359 abstract "All available inversion software for airborne electromagnetic (AEM) data can at a minimum fit a nondispersive conductivity model to the observed inductive secondary field responses, whether operating in the time or frequency domain. Quasistatic inductive responses are essentially controlled by the induction number, the product of frequency with conductivity and magnetic permeability. Recent research has permitted the conductivity model to be dispersive, commonly using a single Cole-Cole parameterization of the induced polarization (IP) effect; but this parameterization slows down and destabilizes any inversion, and it does not account for the need for dual or multiple Cole-Cole responses. Little has been published on inverting AEM data affected by frequency-dependent magnetic permeability, or superparamagnetism (SPM), usually characterized by a Chikazumi model. Because the IP and SPM effects are small and are usually only obvious at late delay times, the aim of our research is to determine if these IP and SPM effects can be fitted and stripped from the AEM data after being approximated with simple dispersive models. We are able to successfully automate a thin-sheet model to do this stripping. Stripped data then can be inverted using a nondispersive conductivity model. The IP and SPM parameters fitted independently to each independent measured decay to provide stripping are proven to be spatially coherent, and they are geologically sensible. The results are found to enhance interpretation of the regolith geology, particularly the nature and distribution of transported materials that are not afforded by mapping conductivity/conductance alone." @default.
• W3034453359 created "2020-06-19" @default.
• W3034453359 creator A5017681777 @default.
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• W3034453359 date "2020-09-01" @default.
• W3034453359 modified "2023-10-08" @default.
• W3034453359 title "Estimation and geologic interpretation of regolith chargeability and superparamagnetic susceptibility in airborne electromagnetic data" @default.
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• W3034453359 doi "https://doi.org/10.1190/geo2019-0395.1" @default.
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