TY - JOUR A1 - Klose, Tim A1 - Guillemoteau, Julien A1 - Simon, Francois-Xavier A1 - Tronicke, Jens T1 - Toward subsurface magnetic permeability imaging with electromagnetic induction sensors BT - Sensitivity computation and reconstruction of measured data JF - Geophysics N2 - In near-surface geophysics, small portable loop-loop electro-magnetic induction (EMI) sensors using harmonic sources with a constant and rather small frequency are increasingly used to investigate the electrical properties of the subsurface. For such sensors, the influence of electrical conductivity and magnetic permeability on the EMI response is well-understood. Typically, data analysis focuses on reconstructing an electrical conductivity model by inverting the out-of-phase response. However, in a variety of near-surface applications, magnetic permeability (or susceptibility) models derived from the in-phase (IP) response may provide important additional information. In view of developing a fast 3D inversion procedure of the IP response for a dense grid of measurement points, we first analyze the 3D sensitivity functions associated with a homogeneous permeable half-space. Then, we compare synthetic data computed using a linear forward-modeling method based on these sensitivity functions with synthetic data computed using full nonlinear forward-modeling methods. The results indicate the correctness and applicability of our linear forward-modeling approach. Furthermore, we determine the advantages of converting IP data into apparent permeability, which, for example, allows us to extend the applicability of the linear forward-modeling method to high-magnetic environments. Finally, we compute synthetic data with the linear theory for a model consisting of a controlled magnetic target and compare the results with field data collected with a four-configuration loop-loop EMI sensor. With this field-scale experiment, we determine that our linear forward-modeling approach can reproduce measured data with sufficiently small error, and, thus, it represents the basis for developing efficient inversion approaches. KW - Electromagnetics KW - Imaging KW - Magnetic+Susceptibility KW - Near+Surface KW - Modeling Y1 - 2018 U6 - https://doi.org/10.1190/GEO2017-0827.1 SN - 0016-8033 SN - 1942-2156 VL - 83 IS - 5 SP - E335 EP - E345 PB - Society of Exploration Geophysicists CY - Tulsa ER - TY - JOUR A1 - Guillemoteau, Julien A1 - Simon, Francois-Xavier A1 - Hulin, Guillaume A1 - Dousteyssier, Bertrand A1 - Dacko, Marion A1 - Tronicke, Jens T1 - 3-D imaging of subsurface magnetic permeability/susceptibility with portable frequency domain electromagnetic sensors for near surface exploration JF - Geophysical journal international N2 - The in-phase response collected by portable loop-loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (<= 1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop-loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments. KW - Magnetic properties KW - Controlled source electromagnetics (CSEM) KW - Electromagnetic theory KW - Environmental magnetism KW - Inverse theory Y1 - 2019 U6 - https://doi.org/10.1093/gji/ggz382 SN - 0956-540X SN - 1365-246X VL - 219 IS - 3 SP - 1773 EP - 1785 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Guillemoteau, Julien A1 - Simon, Francois-Xavier A1 - Lück, Erika A1 - Tronicke, Jens T1 - 1D sequential inversion of portable multi-configuration electromagnetic induction data JF - Near surface geophysics N2 - We present an algorithm that performs sequentially one-dimensional inversion of subsurface magnetic permeability and electrical conductivity by using multi-configuration electromagnetic induction sensor data. The presented method is based on the conversion of the in-phase and out-of-phase data into effective magnetic permeability and electrical conductivity of the equivalent homogeneous half-space. In the case of small-offset systems, such as portable electromagnetic induction sensors, for which in-phase and out-of-phase data are moderately coupled, the effective half-space magnetic permeability and electrical conductivity can be inverted sequentially within an iterative scheme. We test and evaluate the proposed inversion strategy using synthetic and field examples. First, we apply it to synthetic data for some highly magnetic environments. Then, the method is tested on real field data acquired in a basaltic environment to image a formation of archaeological interest. These examples demonstrate that a joint interpretation of in-phase and out-of-phase data leads to a better characterisation of the subsurface in magnetic environments such as volcanic areas. Y1 - 2016 U6 - https://doi.org/10.3997/1873-0604.2016029 SN - 1569-4445 SN - 1873-0604 VL - 14 SP - 423 EP - 432 PB - Wiley-VCH CY - Houten ER -