Analysis of potential fields through source decomposition in hypercompact atoms

We introduce a new filtering method for both detrending and local separation of potential field anomalies. The method is based on the modelling of a set of equivalent sources with the smallest possible volume, a sort of “ atoms” selected among the many possible model that satisfy the potential field inverse problem. In fact, it is well known that potential field problems are non-unique, and any dataset can be fitted by an infinite number of solutions. Among these, we select the one in which the sources are compact and well separated from each other. We will refer to them as “atoms” or ECS (“Extremely Compact Sources”). Our approach allowsus to define a very localized filter by “muting” the cells in the model associated with the unwanted sources. To find such a model we use an iterative inversion algorithm that increase the compactness of the sources with the increasing of the iterations. Besides that, we explored the role of the depth weighting function as a tool to obtain the most compact solution along both vertical and horizontal directions. We will show that our method can be successfully used even in case of strong interferences among different anomalies e.g., the superimposition of anomalies caused by sources in the same area or the presence of a regional field contaminating the anomalies of interest. Moreover, we apply the method to discriminate the different contributionsin the Campi Flegrei caldera (Italy).