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    Comparison of novel semi-airborne electromagnetic data with multi-scale geophysical, petrophysical and geological data from Schleiz, Germany
    (Amsterdam [u.a.] : Elsevier Science, 2020) Steuer, Annika; Smirnova, Maria; Becken, Michael; Schiffler, Markus; Günther, Thomas; Rochlitz, Raphael; Yogeshwar, Pritam; Mörbe, Wiebke; Siemon, Bernhard; Costabel, Stephan; Preugschat, Benedikt; Ibs-von Seht, Malte; Zampa, Luigi Sante; Müller, Franz
    In the framework of the Deep Electromagnetic Sounding for Mineral EXploration (DESMEX) project, we carried out multiple geophysical surveys from regional to local scales in a former mining area in the state of Thuringia, Germany. We prove the applicability of newly developed semi-airborne electromagnetic (EM) systems for mineral exploration by cross-validating inversion results with those of established airborne and ground-based investigation techniques. In addition, supporting petrophysical and geological information to our geophysical measurements allowed the synthesis of all datasets over multiple scales. An initial regional-scale reconnaissance survey was performed with BGR's standard helicopter-borne geophysical system deployed with frequency-domain electromagnetic (HEM), magnetic and radiometric sensors. In addition to geological considerations, the HEM results served as base-line information for the selection of an optimal location for the intermediate-scale semi-airborne EM experiments. The semi-airborne surveys utilized long grounded transmitters and two independent airborne receiver instruments: induction coil magnetometers and SQUID sensors. Due to the limited investigation depth of the HEM method, local-scale electrical resistivity tomography (ERT) and long-offset transient electromagnetic (LOTEM) measurements were carried out on a reference profile, enabling the validation of inversion results at greater depths. The comparison of all inversion results provided a consistent overall resistivity distribution. It further confirmed that both semi-airborne receiver instruments achieve the bandwidth and sensitivity required for the investigation of the resistivity structure down to 1 km depth and therewith the detection of deeply seated earth resources. A 3D geological model, lithological and geophysical borehole logs as well as petrophysical investigations were integrated to interpret of the geophysical results. Distinct highly-conductive anomalies with resistivities of less than 10 Om were identified as alum shales over all scales. Apart from that, the petrophysical investigations exhibited that correlating geophysical and geological information using only one single parameter, such as the electrical resistivity, is hardly possible. Therefore, we developed a first approach based on clustering methods and self-organizing maps (SOMs) that allowed us to assign geological units at the surface to a given combination of geophysical and petrophysical parameters, obtained on different scales. © 2020 The Authors
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    pyGIMLi: An open-source library for modelling and inversion in geophysics
    (Amsterdam [u.a.] : Elsevier Science, 2017) Rücker, Carsten; Günther, Thomas; Wagner, Florian M.
    Many tasks in applied geosciences cannot be solved by single measurements, but require the integration of geophysical, geotechnical and hydrological methods. Numerical simulation techniques are essential both for planning and interpretation, as well as for the process understanding of modern geophysical methods. These trends encourage open, simple, and modern software architectures aiming at a uniform interface for interdisciplinary and flexible modelling and inversion approaches. We present pyGIMLi (Python Library for Inversion and Modelling in Geophysics), an open-source framework that provides tools for modelling and inversion of various geophysical but also hydrological methods. The modelling component supplies discretization management and the numerical basis for finite-element and finite-volume solvers in 1D, 2D and 3D on arbitrarily structured meshes. The generalized inversion framework solves the minimization problem with a Gauss-Newton algorithm for any physical forward operator and provides opportunities for uncertainty and resolution analyses. More general requirements, such as flexible regularization strategies, time-lapse processing and different sorts of coupling individual methods are provided independently of the actual methods used. The usage of pyGIMLi is first demonstrated by solving the steady-state heat equation, followed by a demonstration of more complex capabilities for the combination of different geophysical data sets. A fully coupled hydrogeophysical inversion of electrical resistivity tomography (ERT) data of a simulated tracer experiment is presented that allows to directly reconstruct the underlying hydraulic conductivity distribution of the aquifer. Another example demonstrates the improvement of jointly inverting ERT and ultrasonic data with respect to saturation by a new approach that incorporates petrophysical relations in the inversion. Potential applications of the presented framework are manifold and include time-lapse, constrained, joint, and coupled inversions of various geophysical and hydrological data sets.