A generalized algorithm for gravity or self-potential data inversion with application to mineral exploration

Abstract

An inversion algorithm is developed to estimate the depth and associated model parameters of the anomalous body from the gravity or self-potential (SP) whole measured data. The problem of the depth (z) estimation from the observed data has been transformed into a nonlinear equation of the form F(z) = 0. This equation is then solved for z by minimizing an objective functional in the least-squares sense. Using the estimated depth and applying the least-squares method, the polarization angle and the dipole moment or the amplitude coefficient are computed from the measured SP or gravity data, respectively. The proposed approach is applicable for a class of geometrically simple anomalous bodies such as the semi-infinite vertical cylinder, the dike, the horizontal cylinder and the sphere, and it is tested and verified on synthetic examples with and without noise. This technique is also successfully applied to real data sets for mineral exploration, and it is found that the estimated depths and the associated model parameters are in good agreement with the actual values.