Abstract
Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σa), and σa represents an average value for the depth range investigated with a specific coil separation and orientation. Multi-coil EMI data can be inverted to obtain layered bulk electrical conductivity models. However, above-ground stationary influences alter the signal and the inversion results can be unreliable. This study proposes an improved data processing chain, including EMI data calibration, conversion, and inversion. For the calibration of σa, three direct current resistivity techniques are compared: Electrical resistivity tomography with Dipole-Dipole and Schlumberger electrode arrays and vertical electrical soundings. All three methods obtained robust calibration results. The Dipole-Dipole-based calibration proved stable upon testing on different soil types. To further improve accuracy, we propose a non-linear exact EMI conversion to convert the magnetic field to σa. The complete processing workflow provides accurate and quantitative EMI data and the inversions reliable estimates of the intrinsic electrical conductivities. This improves the ability to combine EMI with, e.g., remote sensing, and the use of EMI for monitoring purposes.
Highlights
The critical zone contains water resources, influences the climate, supports ecosystems, and sustains anthropogenic activities such as agriculture, infrastructure, and waste disposal
The upper few meters of the subsurface can be investigated using minimally-invasive or non-invasive geoelectrical methods, such as ground penetrating radar, electromagnetic induction (EMI), and direct current (DC) methods. Both EMI and the DC methods are sensitive to the electrical conductivity of the subsurface, which depends on subsurface properties such as clay and mineral content, soil texture, water content, and salinity
We presented a novel data processing workflow that consists of conversion, calibration, and inversion of EMI data for reliable and high resolution large-scale subsurface imaging and characterization
Summary
The critical zone contains water resources, influences the climate, supports ecosystems, and sustains anthropogenic activities such as agriculture, infrastructure, and waste disposal. The upper few meters of the subsurface can be investigated using minimally-invasive or non-invasive geoelectrical methods, such as ground penetrating radar, electromagnetic induction (EMI), and direct current (DC) methods Both EMI and the DC methods are sensitive to the electrical conductivity of the subsurface, which depends on subsurface properties such as clay and mineral content, soil texture, water content, and salinity. For large-scale measurements, portable and mobile multi-coil EMI systems are often used Such systems provide apparent electrical conductivity (σa ) values that can be used to infer the soil water content distribution within a catchment [1,2], and/or upscale other soil properties [3,4] up to the sub-continental scale [5]. Heil et al [19] provided a comprehensive overview of σa mapping applications focusing on the two-coil EM38 (Geonics Ltd., Mississauga, Canada) system
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