Abstract
Subsurface formations often contain multiple minerals with different wettability characteristics upon contact with nonaqueous-phase liquids (NAPLs). Constitutive relationships between microstructure heterogeneity and NAPL fate and transport in these formations are difficult to predict. Several studies have used pore-scale network models with faithful representations of rock pore space topology to predict macroscopic descriptors of two-phase flow, however wettability is usually considered as a spatially random variable. This study attempts to overcome this limitation by considering more realistic representations of rock mineralogy and wettability in these models. This is especially important for heterogeneous rocks where properties vary at the pore-scale. The work was carried out in two phases. First, pore-fluid occupancy maps during waterflooding were obtained by X-ray microtomography to elucidate the impact of pore wall mineralogy and wettability on water preferential flow paths and NAPL trapping within a heterogeneous aquifer sandstone (Arkose). Then, microtomography images of the rock were used to generate a hybrid pore network model (PNM) that incorporated both pore space topology and pore wall mineralogy. In-situ contact angles (CA) measured on the surface of different minerals were assigned to the network on a pore-by-pore basis to describe the exact wettability distribution of the rock (Pore-by-pore model). The equivalent network was used as input in a quasi-static flow model to simulate waterflooding, and the predictions of residual NAPL saturation and relative permeabilities were compared against their experimental counterparts. To examine the sensitivity of the model to the underlying fluid-solid interactions, we also used traditional methods of wettability characterization in the input data and assigned them randomly to the PNM. Wettability in this case was assessed from macroscale CA distribution of oil droplets on the surface of unpolished Arkose substrates released by spontaneous imbibition of water (Arkose model) and from pendant drop measurements on polished quartz (Quartz model). Our results revealed that the Pore-by-pore model predicted waterflooding with the highest accuracy among all three cases. The Arkose model slightly overestimated NAPL removal whereas the Quartz model failed to predict the experiments. More in-depth analysis of the Pore-by-pore and Arkose models showed that macroscopic transport quantities are less dependent to microstructure heterogeneity if minerals are distributed uniformly across the rock. The predictions herein indicate the importance of incorporating mineralogy and wettability maps to improve the prediction capabilities of PNMs especially in systems with high mineral heterogeneity, where minerals are nonuniformly distributed, or selective fluid-mineral interactions are targeted.
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