Geophysical methods are widely used to gather information about the subsurface as they are nonintrusive and comparably cheap during acquisition, however, the solution to the geophysical inverse problem is inherently non-unique which introduces considerable uncertainties. Therefore, independently acquired geophysical data sets can be jointly inverted to reduce ambiguities in the resulting multi-physical subsurface images. Zhdanov et al. (2022) introduce a novel cooperative inversion approach using joint minimum entropy constraints in the regularization term of the objective functionals to create more consistent multi-physical images with sharper boundaries. Here, this approach is implemented in an open-source software and its applicability on electrical resistivity tomography (ERT), seismic refraction tomography (SRT) and magnetic data is investigated. A synthetic 2D ERT and SRT data study is used to demonstrate the approach and to investigate the influence of the governing parameters. The findings showcase the advantage of the joint minimum entropy (JME) stabilizer over separate, conventional smoothness-constrained inversions. The method is then used to analyze field data from Rockeskyller Kopf, Germany. 3D ERT and magnetic data is combined and results confirm the expected volcanic diatreme structure with improved details. The multi-physical images of both methods are consistent in some regions as similar boundaries are produced in the resulting models, which have been lacking in previous studies. Because of its sensitivity to hydrologic conditions in the subsurface, observations suggest that the ERT method senses different structures than the magnetic method. However, these structures in the ERT result do not seem to be enforced on the magnetic susceptibility distribution, showcasing the flexibility of the approach. Both investigations outline the importance of a suitable parameter and reference model selection for the performance of the approach and suggest careful parameter tests prior to the joint inversion. With proper settings, the JME inversion is a promising tool for geophysical imaging, however, this thesis also lists some objectives for future studies and additional research to explore and optimize the method.