Potential-Field Inversion for Topographic Sources with Uncorrelated Top and Bottom

Inversion of large-scale potential-field anomalies usually proceeds in the Fourier domain, where a large amount of data can be properly addressed. The commonly adopted geometry is based on a layer of constant thickness, i.e. with a bottom level at a fixed distance from the top level. We propose a method that overcomes this limiting geometry by inverting in the usual iterating scheme for top and bottom levels of any shape. Randomly generated synthetic models will be explored both for gravity and magnetic data, and finally the good performance of this method will be tested by the real isostatic residual anomaly of the Tyrrhenian Sea in Italy. The final result is a density model that allows the investigation of the distribution of the oceanic crust in this region, which is still a point under discussion.