Quantitative multi-layer conductivity inversion of multi-configuration electromagnetic induction measurements
Electromagnetic induction (EMI) measurements return an apparent electrical conductivity (ECa) that represents a weighted average of the electrical conductivity distribution over a certain depth range . Different sensing depths are obtained for different orientations, different coil offsets, and different frequencies, which can in principle be used for a multi-layer inversion. However, instrumental shifts, which often occur in EMI data, prevent the use of quantitative multi-layer inversion. Here, we apply a new calibration method that uses electrical resistivity tomography (ERT) inversion results and returns quantitative ECa values . These calibrated multi-configuration EMI data can be fitted with a Maxwell-based electromagnetic horizontally layered forward model to obtain a layered subsurface . Recently, a novel quasi three-dimensional imaging algorithm was implemented that uses quantitative multi-configuration EMI data to reconstruct lateral and vertical electrical conductivity patterns that can be used for large-scale high resolution catchment characterization. At each inversion location a three-layer electrical conductivity model is obtained that are stitched together to form a quasi-3D subsurface . The layer-wise electrical conductivities are related to changes in soil water content, soil-texture and salinity.
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