Two dimensional joint inversion of direct current resistivity, radio-magnetotelluric and seismic refraction data: An application from Bafra Plain, Turkey

Direct current resistivity, radio-magnetotelluric and seismic refraction methods are widely used in the identification of near surface structures with collected data generally being interpreted separately. In recent decades, the use of joint inversion algorithms in geosciences has become widespread to identify near surface structures. However, there is no developed joint inversion algorithm using direct current resistivity, radio-magnetotelluric and seismic refraction methods. In this study, we developed a new two-dimensional joint inversion algorithm for direct current resistivity, radio-magnetotelluric and seismic refraction data based on a cross gradient approach. In addition, we proposed a new data weighting matrix to stabilize the convergence behavior of the joint inversion algorithms. We used synthetic data to show the advantage of the algorithm. The developed joint inversion algorithm found resistivity and velocity models that are better than the individual inversion of each data set. We also tested an algorithm with the field data collected in the Bafra Plain (Samsun, Turkey) to investigate saltwater intrusion. In comparing the field data inversion results with the sounding log, it can be seen that the developed joint inversion algorithm with the proposed data weighting matrix recovered the resistivity and velocity model better than the individual inversion and classical joint inversion of each data set. Our results showed that a more unique hydrogeological scenario might be obtained, especially in highly conductive media, with the joint usage of these methods.