Self-Potential data inversion through the integration of spectral analysis and tomographic approaches

Abstract

An integrated approach to interpret Self-Potential (SP) anomalies based on spectral analysis and tomographic methods is presented. The Maximum Entropy Method (MEM) is used for providing accurate estimates of the depth of the anomaly source. The 2-D tomographic inversion technique, based on the underground charge occurrence probability (COP) function, is, then, used to fully characterize the anomalous body, as the MEM is not helpful in delineating the shape of the anomaly source. The proposed integrated approach is applied for the inversion of synthetic SP data generated by geometrically simple anomalous bodies, such as cylinders and inclined sheets. This numerical study has allowed the determination of mathematical relationships between zero lines of the COP distributions, the polarization angles and the positions along the profile of the causative sources, which have been of great help for interpreting the related SP anomalies. Finally, the analysis of field examples shows the high potential applicability of the proposed integrated approach for SP data inversion.