Inverse modeling returns many solutions apart from the final product. Exploring and visualizing the solution space covered by an inversion leads to a greater understanding of the problem. Our method combines an inversion algorithm with an effective two-dimensional representation of the multidimensional model parameter space. The analysis of all solutions is done through a visualization technique known as self-organized mapping, resulting in a simple view of an otherwise complicated problem. A user may infer much about the controlling factors in the model through a few graphical displays of the data.