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Reactive transport modeling of subsurface environments plays an important role in addressing critical problems of geochemical processes, such as dissolution and precipitation of minerals. Current transport models for porous media span various scales, ranging from pore-scale to continuum-scale. In this study, we established an upscaling method connecting pore-scale and continuum-scale models by employing a deep learning methodology of Convolutional Neural Networks (CNNs). We applied Darcy-Brinkmann-Stokes (DBS) method to simulate the fluid flow and reactive transport in pore-scale models, which would act as constituents of a continuum-scale model. The datasets of spatial pore distribution of subvolume samples were used as the input for the deep learning model, and the continuum (Darcy)-scale parameters such as permeability, effective surface area, and effective diffusion coefficient were figured out as outputs (i.e., labels). By applying the trained models of the subvolumes in the entire sample volume, we generated the initial field of porosity, permeability, effective diffusion coefficient, and effective surface area for continuum-scale simulation of a mineral dissolution problem. We took an acid dissolution case as an example to utilize the outcomes of trained deep learning models as input data in the continuum-scale simulation. This work presents a comprehensive upscaling workflow, as bridging the findings of microscale simulations to the continuum-scale simulations of a reactive transport problem.
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Effects of Pore‐Scale Three‐Dimensional Flow and Fluid Inertia on Mineral Dissolution
Abstract Mineral dissolution releases ions into fluids and alters pore structures, affecting geochemistry and subsurface fluid flow. Thus, mineral dissolution plays a crucial role in many subsurface processes and applications. Pore‐scale fluid flow often controls mineral dissolution by controlling concentration gradients at fluid‐solid interfaces. In particular, recent studies have shown that fluid inertia can significantly affect reactive transport in porous and fractured media by inducing unique flow structures such as recirculating flows. However, the effects of pore‐scale flow and fluid inertia on mineral dissolution remain largely unknown. To address this knowledge gap, we combined visual laboratory experiments and micro‐continuum pore‐scale reactive transport modeling to investigate the effects of pore‐scale flow and fluid inertia on mineral dissolution dynamics. Through flow topology analysis, we identified unique patterns of 2D and 3D recirculating flows and their distinctive effects on dissolution. The simulation results revealed that 3D flow topology and fluid inertia dramatically alter the spatiotemporal dynamics of mineral dissolution. Furthermore, we found that the 3D flow topology fundamentally changes the upscaled relationship between porosity and reactive surface area compared to a conventional relationship, which is commonly used in continuum‐scale modeling. These findings highlight the critical role of 3D flow and fluid inertia in modeling mineral dissolution across scales, from the pore scale to the Darcy scale.
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- Award ID(s):
- 1813526
- PAR ID:
- 10590555
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 61
- Issue:
- 4
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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