Enhanced thermal fingering in a shear-thinning fluid flow through porous media: Dynamic pore network modeling

Abstract

Thermal-viscous fingering instability in porous media is a common phenomenon in nature as well as in many scientific problems and industrial applications. Despite the importance, however, thermal transport in flow of a non-Newtonian fluid in porous media and the resulting fingering has not been studied extensively, especially if the pore space is heterogeneous. In this paper, we propose a pore network model with full graphics processing unit-parallelized acceleration to simulate thermal transport in flow through three-dimensional unstructured pore networks at centimeter scale, containing millions of pores. A thermal Meter equation is proposed to model temperature- and shear stress-dependent rheology of the non-Newtonian fluids. After comparing the simulation results with an analytical solution for the location of the thermal front in a spatially uncorrelated pore network, thermal transport in flow of both Newtonian and non-Newtonian fluids is studied in the spatially uncorrelated and correlated pore networks over a range of injection flow rates. The simulations indicate that the injection flow rate, the shear-thinning rheology, and the morphological heterogeneity of the pore space all enhance thermal-viscous fingering instability in porous media, but with distinct patterns. In spatially correlated networks, the average temperature and apparent viscosity at the breakthrough point in flow of a shear-thinning fluid exhibit non-monotonic dependence on the injection flow rate. An analysis of the fractal dimension of thermal patterns at the breakthrough point supports the conclusion. The results highlight the importance of designing optimal flow conditions for application purposes.

Upscaling Hydrodynamic Dispersion in Non‐Newtonian Fluid Flow Through Porous Media

“…To accelerate the computational speed and enlarge the simulation domain, flow and solute transport simulations were fully parallelized using the proposed GPU‐CUDA algorithm (An, Yu, Wang, et al., 2017; An, Yu, & Yao, 2017; An et al., 2022). A GPU‐based linear solver based on Jacobi's preconditioned conjugation gradient method was adopted to solve the mass balance equations (An et al., 2020).…”

Assessing Rheology Effects and Pore Space Complexity in Polymer Flow Through Porous Media: A Pore‐Scale Simulation Study

“…Numerous studies have investigated non‐Newtonian fluids through porous media, including experimental studies (Chase & Dachavijit, 2003; Chauveteau, 1982; Comba et al., 2011; Comiti et al., 2000; Ferreira & Moreno, 2019; Koh et al., 2017; Perrin et al., 2006; Rodríguez de Castro & Radilla, 2017a), theoretical modeling (Hayes et al., 1996; Kozicki & Tiu, 1988; Liu & Masliyah, 1999; Shende et al., 2021), and pore network simulation (An, Sahimi, & Niasar, 2022; An, Sahimi, Shende, et al., 2022; Balhoff & Thompson, 2006; Sahimi, 1993). These approaches have notable limitations and challenges, for example, the difficulty associated with running lab experiments in real porous rocks under diverse boundary conditions and complications in solving the differential equations analytically.…”

X-ray tomographic micro-particle velocimetry in porous media

“…groundwater flow in aquifers (Mercer and Cohen, 1990), gas-brine flow in geological energy or carbon storage reservoirs (Mouli-Castillo et al, 2019;Bui et al, 2018), and the performance of filtration devices, fuel cells and catalysts (Miele, Anna, and Dentz, 2019;Mularczyk et al, 2020). The intricate pore geometries in such materials can lead to complex phenomena, particularly during solute and colloid transport (Zhang et al, 2021;Haffner and Mirbod, 2020;Russell and Bedrikovetsky, 2021), multiphase flows (Blunt, 2017;Singh et al, 2019) and non-Newtonian flows (An et al, 2022). While experiments on simplified (often 2D) model geometries give valuable insights on flow behavior in the confinement of generic pore walls (Primkulov et al, 2019;Lenormand, Zarcone, and Sarr, 1983;Holtzman, 2016;Datta, Dupin, and Weitz, 2014), the physical interactions in the complex 3D pore networks encountered in many applications remain difficult to probe.…”