Three-dimensional inversion of QAMT airborne natural-source electromagnetic data

Abstract Airborne natural-source electromagnetics (EM), similar to the magnetovariational technique, offers the potential of great penetration depth combined with superior time- and cost-efficiency compared with other established EM methods. The obtained data are frequency-dependent transfer functions between airborne magnetic field receivers and a ground-based reference site. Accordingly, the inversion of these data requires handling inter-site transfer functions in the forward modeling code. Applications in inaccessible and often rough terrain demand an accurate representation of topography in the model domain. To handle these requirements, we extended the open-source toolbox custEM for calculating inter-site vertical and horizontal magnetic transfer functions and corresponding sensitivities. Using this forward solver in combination with the pyGIMLI framework, the inverse problem is solved by applying a Gauss–Newton minimization scheme. We validate the implementation with a synthetic study, comparing the recovered resistivity models of ground and airborne natural-source EM to those of semi-airborne EM data. We demonstrate the application to real-world problems by presenting the first 3D inversion of data from the novel QAMT system measured at the Lake Hatchet area (Canada). The QAMT system measures the three-component airborne magnetic fields and uses horizontal fields measured at a reference site. ZTEM data from the same area are available for cross-validation; the ZTEM system records the vertical airborne magnetic fields and horizontal magnetic field at a ground reference site. Using two independently acquired data sets from the QAMT and ZTEM systems allowed for system-independent benchmarking of the developed inversion routines. We analyze and interpret the corresponding individual inversion results and performed also a combined inversion of both data sets, providing the chance to discuss the related observations. The presented data and code are freely available. Graphical abstract