A fit-for-purpose saturation exponent is specific to a given rock type and to a particular interpretative algorithm for the evaluation of water saturation. This concept is expanded to include the degree of maturity of the core database. Four data scenarios are enacted to derive data-specific values of fit-for-purpose saturation exponent using two type-algorithms. The first scenario assumes no core data beyond measurements of water saturation and resistivity index using simulated formation water. The second draws additionally on a measurement of porosity for each desaturated core plug. The third scenario further requires a dual-salinity determination of intrinsic formation resistivity factor. The fourth and most comprehensive scenario calls for a more complete electrical characterization of a core plug through multiple-salinity conductivity measurements. The value of these scenarios is examined by comparing the resulting predictions of water saturation with those obtained through the reference Scenario 4 and by cross-comparing the predictive performance of the type-algorithms.
The outcome is practically the same for the two type-algorithms. The first data scenario is erratic. The results of the type-methods converge through Scenario 2, for which similar water saturations are predicted by the two algorithms. Scenarios 2 and 3 furnish predicted values of water saturation that agree well with those resulting from Scenario 4. Because Scenario 2 has the smallest data requirement of these three approaches, it is proposed as the most effective way of deriving a fit-for-purpose saturation exponent and thence obtaining a meaningful evaluation of water saturation. This scenario therefore allows data needs to be optimized with the further containment of uncertainty in integrated reservoir description. Thus, both costs and risks can be reduced simultaneously.