Multiphase Flow in Mixed-wet Porous Media

Abstract

Multiphase flow in porous media is important in a wide range of industrial and environmental processes. It is well-known that the fluids’ relative affinity to the porous media (i.e., wettability) is a crucial factor controlling multiphase flow in porous media. Despite having a good understanding of multiphase flow in porous media under uniform wettability conditions, our knowledge of how fluids flow in mixed-wet porous media is more limited. Mixed-wet porous media (i.e., porous media with spatially heterogeneous wettability) is prevalent in nature, from groundwater aquifers to oil-bearing rocks. This Thesis aims to better understand the complexities of multiphase flow in mixed-wet porous media. The study begins with investigating fluid-fluid displacement in mixed-wet microfluidic flow cells. We performed experiments over a range of capillary numbers and mixed-wettability conditions, and our results show that the fluid-fluid interface in mixed-wet pores resembles an S shaped saddle with very low capillary pressure. In the next step, we derive analytical expressions for fluid-fluid interface evolution through mixed-wet pore throats. These analytical expressions are incorporated into a dynamic pore network model, which enables us to develop a numerical framework capable of simulating fluid-fluid displacement in mixed-wet porous media. Next, we leverage our model to simulate multiphase flow in simple mixed-wet porous micro-models consisting of distinct water-wet and oil-wet regions whose fractions are systematically varied to yield a variety of displacement patterns over a wide range of capillary numbers. Our simulations reveal that mixed-wettability impacts are most prominent at low capillary numbers, and it depends on the complex interplay between the wettability fraction and the intrinsic contact angle of the water-wet regions. We also investigate the dynamics of multiphase flow in mixed-wet porous media under quasi-static conditions and discover that it exhibits self-organized criticality (SOC). Finally, we determine the correlation between spatial and temporal aspects of this dynamical system.