For timelapse resistivity processing (where we are interested in changes) we use the process which is shown schematically in the figure below. We start with a background dataset. This dataset is inverted, and gives us a background conductivity. This conductivity is used as the starting model for subsequent datasets, and each inversion results in another distribution of conductivities. We can then visualize and interpret the difference between the background conductivity and the conductivity of subsequent inversions.