<p>Predicting the geometrical evolution of the pore space in geological formations due to fluid–solid interactions has applications in reservoir engineering, oil recovery, and geological storage of carbon dioxide. However, modeling frameworks that combine fluid flow with physical and chemical processes at a rock’s pore scale are scarce. Here, we report a method for modeling a rock’s pore space as a network of connected capillaries and to simulate the capillary diameter modifications caused by reactive flow processes. Specifically, we model mineral erosion, deposition, dissolution, and precipitation processes by solving the transport equations iteratively, computing diameter changes within each capillary of the network simultaneously. Our automated modeling framework enables simulations with digital rock samples as large as (1.125 mm)<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11242_2025_2193_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$^3$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mrow /> <mn>3</mn> </mmultiscripts> </math></EquationSource> </InlineEquation> having 125<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11242_2025_2193_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$\times$</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> 10<InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11242_2025_2193_Article_IEq3.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$^6$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mrow /> <mn>6</mn> </mmultiscripts> </math></EquationSource> </InlineEquation> voxels, within seconds of CPU time per iteration. As an application of the computational method, we have simulated brine injection and calcium carbonate precipitation in sandstone. For quantitatively comparing simulation results obtained with models predicting either a constant or a flow rate-dependent precipitation, we track the time-dependent capillary diameter distribution as well as the permeability of the connected pore space. For validation and reuse, we have made the automated simulation workflow, the reactive flow model library, and the digital rock samples available in public repositories.</p>

Simulating Carbon Mineralization at Pore Scale in Capillary Networks of Digital Rock

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2025年7月16日

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David A. Lazo Vasquez,
Jaione Tirapu Azpiroz,
Rodrigo Neumann Barros Ferreira,
Ronaldo Giro,
Manuela Fernandes Blanco Rodriguez,
Matheus Esteves Ferreira,
Mathias B. Steiner

摘要

Predicting the geometrical evolution of the pore space in geological formations due to fluid–solid interactions has applications in reservoir engineering, oil recovery, and geological storage of carbon dioxide. However, modeling frameworks that combine fluid flow with physical and chemical processes at a rock’s pore scale are scarce. Here, we report a method for modeling a rock’s pore space as a network of connected capillaries and to simulate the capillary diameter modifications caused by reactive flow processes. Specifically, we model mineral erosion, deposition, dissolution, and precipitation processes by solving the transport equations iteratively, computing diameter changes within each capillary of the network simultaneously. Our automated modeling framework enables simulations with digital rock samples as large as (1.125 mm) $^3$ $^{3}$ having 125 $\times$ $\times$ 10 $^6$ $^{6}$ voxels, within seconds of CPU time per iteration. As an application of the computational method, we have simulated brine injection and calcium carbonate precipitation in sandstone. For quantitatively comparing simulation results obtained with models predicting either a constant or a flow rate-dependent precipitation, we track the time-dependent capillary diameter distribution as well as the permeability of the connected pore space. For validation and reuse, we have made the automated simulation workflow, the reactive flow model library, and the digital rock samples available in public repositories.