Relative permeability (kr(SW)) and capillary pressure (PC(SW)) saturation functions are key uncertainties in reservoir engineering. Therefore, many resources are devoted to measuring these key functions for various operations. Despite the effort and the time needed to perform SCAL experiments, it is not yet customary to simulate SCAL data (Special Core Analysis) or to perform numerical history matching for their interpretation. However, a comprehensive numerical description is important in order to reliably extract kr(SW) and PC(SW) with a realistic estimate of uncertainties. In this presentation, we discuss a Matlab-MRST-based SCAL interpretation tool for simultaneous matching of SCAL data sets form different experiments. For this purpose, we discuss the kr(SW) and PC(SW) saturation functions, the SCAL experimental workflow and the limitations of the classical interpretation methods. We focus on the most common SCAL methods namely steady-state relative permeability and centrifuge capillary pressure. These (and other) techniques have been implemented in the numerical workflow beyond the current best standard. Thereby, we attach importance on the uncertainty analysis, which is the basis for an honest and stochastic evaluation of the reservoir performance.