Geophysical Data Interpretation Using a General Inversion Code Based on Regularized Weighted Minimum Length Solution: Application to Three Case Studies

It has been shown that regularized weighted minimum length solution algorithm is an efficient tool for inversion of geophysical data sets. In this paper, a general inversion code is developed based on this algorithm for interpretation of DC resistivity, EM34, magnetometry and gravity data sets. At first, we test our written codes using two synthetic complex models and inverted models prove the usefulness of the inversion codes so that convince us to utilize them for interpretation of three case studies. The first real case is a landfill in Germany for which inversion of apparent resistivities are in good agreement with the subsurface standard model. The algorithm is then applied to magnetic and gravity data collected in Iran for a salt case and reconstructed 3D density and susceptibility models show a salt source with depth range from 12 to about 100m which is confirmed by the information of log data. Ultimately, this algorithm allows successful recovery of a resistive dolerite dyke in Grootefontein site through conductivity and susceptibility inverse models derived from EM34 and magnetometry data. In spite of larger thickness of the dyke retrieved by EM34 data, both approaches show a high degree of agreement regarding depth range which is from near surface to 20m.