A new algorithm for gravity or self-potential data interpretation: Fid-Bau Portal

A new algorithm for gravity or self-potential data interpretation

Khalid S Essa

An inversion algorithm is developed to estimate the depth and the 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, the polarization angle and the dipole moment or the depth and the amplitude coefficient are computed from the measured SP or gravity data, respectively. The method is based on determining the root mean square (RMS) of the depths estimated from using all s-values for each shape factor. The minimum RMS is used as a criterion for estimating the correct shape and depth of the buried structure. When the correct shape factor is used, the RMS of the depths is always less than the RMS computed using wrong shape factors. The proposed approach is applicable to 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 four real datasets for mineral exploration, and it is found that the estimated depths and the associated model parameters are in good agreement with the actual values.