Seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) 2D profiles are commonly employed in near surface geophysical surveys to gather subsurface information. Structurally coupled joint inversions algorithms have been developed to process ERT and SRT data simultaneously 1. The primary objective of these algorithms is to mitigate problems related to equivalency in solving the inverse problem and enhance the quality of the final image. Nevertheless, to date of this article, the prevalence of commercially accessible software for joint inversion remains uncommon. The objective of this work is to provide a summary of the findings from two ERT and SRT geophysical profiles obtained in different geological environment (altered volcanic materials and a landslide in coastal environment) and processed with the cross gradient structural joint inversion technique. The findings indicate that the utilization of this type of joint inversion can successfully improve the resolution and data coverage of some of the seismic and/or the electrical profiles. The algorithm facilitates the recognition of structural similarities during the inversion process, but it has also the potential to induce instability in the inversion process making the approach not practical in all cases. Specific findings for this study are: Carefully individually inverting the ERT profiles with specific parameters before running the cross gradient seems to slightly improve the resulting electric tomographic image from subsequent cross gradient joint inversion with the SRT data. In this situation the joint inversion is used as a refinement step and had to be parameterized with the Cross Correlation Criteria turned off and a light to medium strength pushing factor.Enabling the Cross Correlation Criteria in the cross gradient joint inversion improves the quality of the seismic profile. However, it can also introduce excessive model complexity in the electrical profile, although reducing RMS error.Supplementary data, such as boreholes, are extremely important for enhancing the quality of the final image. This is primarily due to their ability to facilitate the selection of the most suitable combination of joint inversion parameters.
Seive et al. (Mon,) studied this question.