The wetting properties of pore walls have a strong effect on multiphase flow through porous media. However, the fluid flow behaviour in porous materials with both complex pore structures and non-uniform wettability are still unclear. Here, we performed unsteady-state quasi-static oil- and waterflooding experiments to study multiphase flow in two sister heterogeneous sandstones with variable wettability conditions (i.e. one natively water-wet and one chemically treated to be mixed-wet). The pore-scale fluid distributions during this process were imaged by laboratory-based X-ray micro-computed tomography (micro-CT). In the mixed-wet case, we observed pore filling events where the fluid interface appeared to be at quasi-equilibrium at every position along the pore body (13% by volume), in contrast to capillary instabilities typically associated with slow drainage or imbibition. These events corresponded to slow displacements previously observed in unsteady-state experiments, explaining the wide range of displacement time scales in mixed-wet samples. Our new data allowed us to quantify the fluid saturations below the image resolution, indicating that slow events were caused by the presence of microporosity and the wetting heterogeneity. Finally, we investigated the sensitivity of the multi-phase flow properties to the slow filling events using a state-of-the-art multi-scale pore network model. This indicated that pores where such events took place contributed up to 19% of the sample’s total absolute permeability, but that the impact on the relative permeability may be smaller. Our study sheds new light on poorly understood multiphase fluid dynamics in complex rocks, of interest to e.g. groundwater remediation and subsurface CO2 storage.

Image-based pore-scale modeling is an important method to study multiphase flow in permeable rocks. However, in many rocks, the pore size distribution is so wide that it cannot be resolved in a single pore-space image, typically acquired using micro-computed tomography (micro-CT). Recent multi-scale models therefore incorporate sub-voxel porosity maps, created by differential micro-CT imaging of a contrast fluid in the pores. These maps delineate different microporous flow zones in the model, which must be assigned petrophysical properties as input. The uncertainty on the pore scale physics in these models is therefore heightened by uncertainties on the representation of unresolved pores, also called sub-rock typing. Here, we address this by validating a multi-scale pore network model using a drainage experiment imaged with differential micro-CT on an Estaillades limestone sample. We find that porosity map-based sub-rock typing was unable to match the micrometer-scale experimental fluid distributions. To investigate why, we introduce a novel baseline sub-rock typing method, based on a 3D map of the experimental capillary pressure function. By incorporating this data, we successfully remove most of the sub-rock typing uncertainty from the model, obtaining a close fit to the experimental fluid distributions. Comparison between the two methods shows that in this sample, the porosity map is poorly correlated to the multiphase flow behavior of the microporosity. The validation method introduced in this paper serves to separate and address the uncertainties in multi-scale models, facilitating simulations in complex geological reservoir rocks important for e.g. geological storage of CO2 and renewable energy.