Direct characterization of solute transport in unsaturated porous media using fast X-ray synchrotron microtomography

Abstract

Solute transport in unsaturated porous materials is a complex process, which exhibits some distinct features differentiating it from transport under saturated conditions. These features emerge mostly due to the different transport time scales at different regions of the flow network, which can be classified into flowing and stagnant regions, predominantly controlled by advection and diffusion, respectively. Under unsaturated conditions, the solute breakthrough curves show early arrivals and very long tails, and this type of transport is usually referred to as non-Fickian. This study directly characterizes transport through an unsaturated porous medium in three spatial dimensions at the resolution of 3.25 μm and the time resolution of 6 s. Using advanced high-speed, high-spatial resolution, synchrotron-based X-ray computed microtomography (sCT) we obtained detailed information on solute transport through a glass bead packing at different saturations. A large experimental dataset (>50 TB) was produced, while imaging the evolution of the solute concentration with time at any given point within the field of view. We show that the fluids’ topology has a critical signature on the non-Fickian transport, which yet needs to be included in the Darcy-scale solute transport models. The three-dimensional (3D) results show that the fully mixing assumption at the pore scale is not valid, and even after injection of several pore volumes the concentration field at the pore scale is not uniform. Additionally, results demonstrate that dispersivity is changing with saturation, being twofold larger at the saturation of 0.52 compared to that at the fully saturated domain.

Process-Dependent Solute Transport in Porous Media

“…Additionally, as seen in Fig. 3, there is a positive power law relation between the dispersion coefficient and pore velocity as reported in the literature (Babaei and Joekar-Niasar 2016;An et al 2020;Bijeljic et al 2006;Hasan et al 2020). It should be noted that the precise nature of this power law dependence is at least partly a consequence of fitting the data with solution of the ADE, which assumes that the dispersive transport at the investigated experimental spatial and temporal scales is Fickian (Berkowitz et al 2006(Berkowitz et al , 2009.…”

“…The ratio of advection to diffusion is referred to as the dimensionless Péclet number, P e = vL D m , where L denotes the characteristic transport length and D m is the molecular diffusion coefficient. The pore scale Péclet number is defined based on the characteristic diameter of a pore (Hasan et al 2019(Hasan et al , 2020, while the field Péclet number is usually defined based on the distance between the injection point and the measurement location; as such the values of these two Péclet numbers are significantly different. In addition, due to the presence of the no-slip boundary on solid surfaces, tortuosity of the porous material and preferential pathways, a solute will also spread along the flow direction via fluctuations from the average velocity.…”

Rapid-Response Unsaturated Zone Hydrology: Small-Scale Data, Small-Scale Theory, Big Problems

“…A further problem with traditional approaches is that preferential flow fundamentally involves nonequilibrium processes, in that rapid flow through preferential pathways begins and usually ends long before there has been adequate time for equilibrium to be established in directions perpendicular to the direction of flow (Jarvis, 2007;Jarvis et al, 2016). Various studies, for example by Hasan et al (2020), have demonstrated this characteristic. Thus the process is not a diffusive one in which the state of water in each individual pore is determined by conditions in the adjacent pores.…”

Transition From Viscous Fingering to Capillary Fingering: Application of GPU‐Based Fully Implicit Dynamic Pore Network Modeling

“…Following Although the optical/micromodel experimental studies provide valuable insights, the results might be only valid for 2-D systems as the percolation threshold and relative permeability curves are significantly different for 2-D versus 3-D systems (Sahimi, 1994). However, accurate characterization of dynamic two-phase flow in 3-D microscale experiments is very challenging (Armstrong et al, 2016;Hasan et al, 2020;Primkulov et al, 2019), especially under high flow rate conditions. To realize the rapid scanning, unconsolidated packed glass beads are recently utilized to analyze the flow patterns in the crossover zone (Hu et al, 2020;Patmonoaji et al, 2020).…”