Abstract

We describe a pore- to reservoir-scale investigation of wettability variation and its impact on waterflooding. We use a three-dimensional pore-scale network model of a Berea sandstone to predict relative permeability and capillary pressure hysteresis. We successfully predict experimentally measured relative permeability data for the water-wet case, and demonstrate that the model captures experimentally observed trends in waterflood recovery for mixed-wet media. We then focus upon the effect of variations in initial water saturation associated with capillary rise above the oil–water contact (OWC). This may lead to wettability variations with height because the number of pore-walls which may be rendered oil-wet during primary drainage, increases as the oil saturation increases. We investigate empirical hysteresis models in which scanning curves are used to connect bounding drainage and waterflood curves for a given initial water saturation, and find that if wettability varies with initial water saturation, then the scanning water relative permeability curves predicted by the empirical model are significantly higher than those predicted by the network model. We then use a conventional simulator, in conjunction with the relative permeability curves obtained from the network and empirical models, to investigate the reservoir-scale impact of wettability variations on waterflooding. If the wettability varies with height above the OWC, we find that using the network model to generate scanning relative permeability curves yields a significantly higher recovery than using empirical models or assuming that the reservoir is uniformly oil-wet or water-wet. This is because the scanning water curves are generally low (characteristic of water-wet media), yet the residual oil saturation is also low (characteristic of oil-wet media). Our aim is to demonstrate that network models of real rocks may be used as a tool to predict wettability variations and their impact on field-scale flow.

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