In reservoir characterization studies, static reservoir rock types, SRRTs, are utilized to guide the modeling of reservoir petrophysical properties in static geological models. However, since the reservoir dynamic properties are not considered in the static rock typing schemes, the SRRTs should not be used - as being practiced now – to guide the distribution of the reservoir multiphase dynamic properties of capillary pressure, Pc, and relative permeability, Kr, curves to the cells of dynamic simulation models.
Considering the rock attributes that goes into any SRRTs scheme and assuming identical interfacial tension between the different reservoir fluids, this paper suggests that the dynamic reservoir rock types, DRRTs, would only be a function of wettability for any SRRT. Thus by imposing wettability on the SRRTs, reservoir engineers should be able to generate the DRRTs, the proper guide for generating and distributing Pc and Kr curves for simulation models.
This technique is applied for building the simulation model of a major carbonate oil reservoir. The gradual change of reservoir wettability from oil wet to water wet dictated the generation of many DRRTs for any SRRT, each defines that SRRT at a different reservoir level between the top and the upper limit of the transition zone.
Available experimental Pc and Kr data, acquired for only few SRRTs, were utilized to develop correlations to determine the saturation and Kr endpoints of the Kr curves. The connate water saturation, Swc, of any DRRT is picked from the Pc curve of the parent SRRT at that DRRT reservoir level. Swc correlated with the residual oil saturation, Sorw. Sorw is in turn used to establish the maximum water Kr point of Krwmax. Oil Kr maximum point, Kromax, is assumed to be 1. Furthermore, the shape of the different Kr curves would be devised by picking the corresponding Corey exponents as they are correlated with wettability for any SRRT. The consistently derived sets of Kr curves helped build a very well initialized and history matched simulation model.