GNGTS 2023 - Atti del 41° Convegno Nazionale

Session 3.3 ______ ___ GNGTS 2023 Analysis of the model weighting function in the inversion of gravity and electrical resistivity data M. Milano 1 , M. Fedi 1 , R. Varfinezhad 2 1 Università degli Studi di Napoli Federico II; 2 University of Tehran Geophysical data inversion is now of fundamental importance for subsurface modeling. Numerous mining exploration surveys, as well as archaeological and water explorations, are in fact conducted through the acquisition and processing of gravity and electrical tomography data. However, the correct estimation of the physical and geometric properties of the anomaly sources by means of inverse techniques, cannot ignore the use of appropriate weighting functions, better known as model weighting functions (MWFs). This work aims at analyzing the inversion with the mostly used model weighting functions for both gravity and dc resistivity data. We show that the model weighting function built with depth weighting and compacting factor, formerly formulated for the gravity and magnetics problems, can be useful also for dc resistivity data. The results show how the model obtained from the inversion of the gravity data is more dependent on the choice of the exponent ( β ) of the depth weighting; however, dc resistivity data inversion is less sensitive to β , but the above-indicated choice leads to faster convergence. In the same way, the use of the compactness function allows in both cases to converge in even shorter times and to provide more compact models of the source. The use of the most common MWFs for resistivity data inversion (L1 - L2 norm roughness matrix ) instead tends to provide a general decrease in resolution with depth.