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1 2023

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DC resistivity inversion constrained by magnetic method through sequential inversion

Varfnezhad Ramin, Parnow Saeed, Florio Giovanni, Fedi Maurizio, Vizheh Mehdi Mohammadi

Acta Geophysica

2023

Vol. 71, no. 1

247--260

In the inversion of geophysical data, an attempt is made to obtain a model with the best ft on the observed data. Unfortunately, the results are usually accompanied by non-uniqueness and ambiguity. These inversion problems can be reduced by inverting different geophysical datasets. Sequential inversion is one of the most common ways to integrate two or more geophysical datasets, to obtain a model that is compatible with all geophysical data, thus reducing the amount of ambiguity. This paper presents separate inversions of DC resistivity and magnetic data and sequential inversion of DC resistivity constrained by magnetic data. Here, the inverse model of magnetic data is considered the initial model for the sequential inversion of DC resistivity data. At first, the algorithm is applied to a synthetic model composed of four conductive and magnetized bodies, and the results show notable improvement for the resistivity model after sequential inversion, compared with the separate resistivity inversion model. Finally, encouraged by the results obtained in the synthetic case, the algorithm was applied to DC resistivity and magnetic datasets that were collected in the archeological area of old Pompeii city nearby Naples, Italy. The result of the sequential resistivity inversion model was notably superior to the corresponding resistivity model obtained from standard separate inversion.