Applying simpler and more powerful waterflood performance analytical modeling tools to history match and forecast fluid (oil and water) production rates is always a subject of interest. Increasing improvements of these no grid-based tools trigger their use as predictive and trustworthy precursors of grid-based modeling, providing significant insights and allowing a previous assessment of historical and future waterflood performance without a significant time- and investment-consuming modeling.

Setting up a unified fractional-flow model (UFFM), that considers both the traditional Buckley-Leverett-based stable fractional-flow model (BLBFFM) and instabilities due to oil viscous-fingering effect, to accurately predict the oil recovery from traditional waterflood performance analytical modeling tools is the objective of this paper. The unification is based on using appropriate kro/krw vs. water saturation expression that considers viscous-oil effect based on the effective finger model (EFM), allowing the substitution of a classic semilog linear relationship of kro/krw vs. Sw (constant coefficients A and B) by a unified nonlinear oil-water relative permeability ratio.

This UFFM approach aims to boost the analysis from well-known waterflood performance analytical methods: water-oil ratio (WOR), X-plot, Y-function and the capacitance-resistance model (CRM). Such waterflood performance diagnosis methods, traditionally based on the BLBFFM, were redefined by using the new UFFM. Conceptual and field cases were tested using new definitions to evaluate impact on ultimate oil recovery and various reservoir parameters.

Results demonstrated that unified approach improves reliability when estimating oil recovery for stable and unstable waterfloods. As expected, they quantitatively yield, for example, that the greater the viscous-fingering effect, the lower the viscous-oil recovery.

The universalization of fractional-flow functions (fw and fo) by incorporating UFFM upon all traditional waterflood performance methods based on BLBFFM can allow insights of important physical phenomenon that affect relative permeability, such as the oil-water viscosity ratio, injection rate, and known physical parameters affecting ultimate oil recovery.

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