Achim Mester

Three‐dimensional imaging of subsurface structural patterns using quantitative large‐scale multiconfiguration electromagnetic induction data

Electromagnetic induction (EMI) systems measure the soil apparent electrical conductivity (ECa), which is related to the soil water content, texture, and salinity changes. Large-scale EMI measurements often show relevant areal ECa patterns, but only few researchers have attempted to resolve vertical changes in electrical conductivity that in principle can be obtained using multiconfiguration EMI devices. In this work, we show that EMI measurements can be used to determine the lateral and vertical distribution of the electrical conductivity at the field scale and beyond. Processed ECa data for six coil configurations measured at the Selhausen (Germany) test site were calibrated using inverted electrical resistivity tomography (ERT) data from a short transect with a high ECa range, and regridded using a nearest neighbor interpolation. The quantitative ECa data at each grid node were inverted using a novel three-layer inversion that uses the shuffled complex evolution (SCE) optimization and a Maxwell-based electromagnetic forward model. The obtained 1-D results were stitched together to form a 3-D subsurface electrical conductivity model that showed smoothly varying electrical conductivities and layer thicknesses, indicating the stability of the inversion. The obtained electrical conductivity distributions were validated with low-resolution grain size distribution maps and two 120 m long ERT transects that confirmed the obtained lateral and vertical large-scale electrical conductivity patterns. Observed differences in the EMI and ERT inversion results were attributed to differences in soil water content between acquisition days. These findings indicate that EMI inversions can be used to infer hydrologically active layers.

Quantitative multi-layer electromagnetic induction inversion and full-waveform inversion of crosshole ground penetrating radar data

Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction (EMI) and ground penetrating radar (GPR) systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell’s equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography (ERT) calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results.

Development and drift-analysis of a modular electromagnetic induction system for shallow ground conductivity measurements

Electromagnetic induction (EMI) is used for fast near surface mapping of the electrical conductivity (EC) for a wide range of geophysical applications. Recently, enhanced methods were developed to measure depth-dependent EC by inverting quantitative multi-configuration EMI data, which increases the demand for a suitable multi-channel EMI measurement system. We have designed a novel EMI system that enables the use of modular transmitter/receiver (TX/RX) units, which are connected to a central measurement system and are optimized for flexible setups with coil separations of up to 1.0 m. Each TX/RX-unit contains a coil, which is specifically adjusted for transmitting or receiving magnetic fields. All units enable impedance measurements at the coils, which are used to simulate its electrical circuit and analyze temperature-induced drift effects. A laboratory drift analysis at 8 kHz showed that 88% of the drift in the measured data is due to the change in the electrical transmitter coil resistance. The remaining 12% is due to changes in the transmitter coil inductance and capacitance, the receiver impedance and drifts in the amplification circuit. A measurement under field conditions proved that the new EMI system is able to detect a water-filled swimming pool with 50 mS m−1, using a coil separation of 0.3 m. In addition, the system allows in-field ambient noise spectra measurements in order to select optimal low-noise measurement frequencies.

Two-layer Inversion of Post-calibrated Multi-configuration Electromagnetic Induction Data

Common electromagnetic induction (EMI) devices are capable of collecting apparent conductivity values which represent a single value that is assigned to the cumulatively sensed electrical conductivity over a certain depth range. Here, different sensing depths are obtained for different coil orientations, different coil offsets, and different frequencies in the given order of significance. We introduce an inversion scheme that uses post-calibrated EMI data and inverts for a two-layer earth. The inversion minimizes the misfit between the measured and modeled magnetic field by a combined global and local search and does not use any smoothing parameter. Joint inversion of EMI data from horizontal coplanar (HCP) and vertical coplanar (VCP) loop configurations, coil offsets of 1 and 1.22 m, and frequencies of 8 and 15 kHz provides lateral and vertical conductivity variations very similar as observed in an elaborate ERT experiment. Application of this method enables the fast mapping of true conductivity distributions over large areas. This approach can be easily extended for multi-layer inversion when the appropriate multi-configuration EMI data is available.