Self-constrained inversion of potential fields

Abstract We present a constrained inversion procedure based on a priori information derived exclusively from the analysis on the potential field data themselves (self-constrained inversion). The procedure effectively applies to underdetermined problems and involves scenarios where the source distribution can be assumed to be of some simple character, but perturbations from this simplified body might occur. To set up effective constraints we first estimate by an analysis of the gravity or magnetic field some or all of the following source parameters: the source depth-to-the-top, the structural index, the horizontal position of the source body edges and their dip. The second step is incorporating the information related to these constraints in the objective function as depth and spatial weighting functions. We show, through some 2D and 3D synthetic and real data examples, that the sole potential field-based constraints are most of times enough to obtain rather good improvements in the density and magnetization models.