Regularization strategy for the layered inversion of airborne TEM data: application to VTEM data acquired over the basin of Franceville (Gabon)
Julien Guillemoteau (IPGS), Pascal Sailhac (IPGS), Mickael Behaegel, (IPGS)

TL;DR
This paper compares regularization strategies for layered earth inversion of airborne TEM data, demonstrating their effectiveness on synthetic and real data from Franceville, Gabon, to improve conductivity imaging accuracy.
Contribution
It introduces and evaluates three regularization methods, including Tikhonov-based and condition number reduction techniques, for layered inversion of airborne TEM data.
Findings
All methods yield similar data misfit and accuracy on synthetic data.
Regularization improves model stability and realism, especially with the logarithmic filter.
Real data inversion aligns well with borehole logs, with some depth biases in complex areas.
Abstract
Airborne transient electromagnetic (TEM) is a cost-effective method to image the distribution of electrical conductivity in the ground. We consider layered earth inversion to interpret large data sets of hundreds of kilometre. Different strategies can be used to solve this inverse problem. This consists in managing the a priori information to avoid the mathematical instability and provide the most plausible model of conductivity in depth. In order to obtain fast and realistic inversion program, we tested three kinds of regularization: two are based on standard Tikhonov procedure which consist in minimizing not only the data misfit function but a balanced optimization function with additional terms constraining the lateral and the vertical smoothness of the conductivity; another kind of regularization is based on reducing the condition number of the kernel by changing the layout of…
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