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  -