In this sub-section, we propose a strategy to automatically tune CSP viscosity model based on the sensitivity analysis and Bayesian calibration described in the previous sub-sections. Such strategy is motivated by the fact that CSP viscosity model has four tuning parameters but, depending on the oil characteristics, just a subset of tuning parameters is required. Analyzing the CSP model, it is clear that (1stCSP ) and (2ndCSP ) are related to light oils (small amount of heavier components fractions) or gases such that the reference state is calculated using methane. Likewise, when the reference state is obtained using a crude oil based fluid, parameters (3rdCSP ) and (4thCSP ) play an important role in model tuning. However, how we could determine which parameters have to be tuned in a generic way, i.e., for any given mixture and regardless of CSP configuration? This is the fundamental question that motivated us to elaborate a simple and practical solution -that we describe in the followingusing the method of Elementary Effects.