Behrooz Oskooi

We advance a previously established method for 2D inversion of electromagnetic data, in which the smoothness constraints are locally reweighted according to the seismic envelope fractional gradients (SEFGs). As the first step of our modifications, seismic envelope values are edited and normalized. This results in the rejection of noise-contaminated parts, clipping the envelope outliers and increasing the reflectivity power of weak seismic signals. Second, we introduce a weighting matrix in the normalization process to incorporate prior information in the constrained inversion regarding the relative contrasts of electrical resistivity in the given parts of the model. Third, due to normalizing the SEFG, there is no need to search for an optimum stabilization factor to modify local smoothing weights, and hence, we set it to a constant value. Finally, an Occam inversion with additional Levenberg-Marquardt damping is used to mitigate possible artifacts in the resistivity model generated by reflection seismic constraints. In applying the proposed scheme to a synthetic example, interfaces of various geologic units are restored as sharp boundaries. In addition, artifacts generated in the original approach are effectively mitigated thanks to the applied normalization process. For the first time, we apply the method to radio-magnetotelluric (RMT) and controlled-source audio-magnetotelluric (CSAMT) field data acquired along a profile across a known aquifer in Heby, Sweden. Our inversion models compare favorably to previously presented results from seismic and geoelectric data. By modifying the smoothness weights based on SEFG, the depth to the bedrock is recovered well, being constrained by the corresponding interfaces in the seismic image. The resistivity models from seismically constrained inversions of RMT and CSAMT data reveal steeply dipping and possibly fractured bedrock underneath the valley-shaped aquifer in the area. This interpretation is verified by borehole logs.

Frequency domain helicopter-borne electromagnetic (FHEM) surveys have been used as an effective tool for the exploration of underground resources for as long as airborne electromagnetics (AEM) has existed. Large FHEM data sets are commonly interpreted with very fast 1D inversion algorithms that often numerically adequately fit the data sets, even though they yield incorrect results near 2D/3D geological structures. The present study aims to compare 1D and 2D inversion algorithms when applied to the reconstruction of geologically complex regions. We have developed a 2D inversion algorithm incorporating the Levenberg–Marquardt least-squares approach regularised through spatial constraints to retrieve 2D electrical resistivity models associated with arbitrary surface topography. The approach uses a 2D finite element frequency domain solution and a tailored triangular meshing algorithm based on the Ruppert’s Delaunay refinement for the forward modelling. We illustrate how rough topographic effects obscure the FHEM response and affect recovered resistivity models through numerical experiments. We also demonstrate the influence of acquisition frequency and resistivity structure on the topographic effect. In the Appendix, we discuss the FHEM footprint concept from a 2D perspective to assess how 2D effects affect and bias 1D inversion results. Complex 2D synthetic scenarios are presented to compare 1D and 2D inversion in various settings. Two field cases from Norway and Iran are presented to show the model improvements with 2D inversion. For the Norwegian case, the 2D FHEM inversion aligns well with a model retrieved from ground-based electrical resistivity tomography. We show the bias imposed on the 2D inversion of the data set from Iran by improper system calibration.