Validation of a multicomponent reactive-transport model at pore scale based on the coupling of COMSOL and PhreeqC

Jyoti, Apoorv; Haese, Ralf R.

doi:10.1016/j.cageo.2021.104870

Cited by 9 publications

(3 citation statements)

References 37 publications

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“…Figure 1 illustrates the simulation procedure, where the fluid flow, the species transport, and the equilibrium steps are solved consecutively. Due to the simplicity and effectiveness in applying the SNIA coupling between the transport solvers and the chemical equilibrium codes, this coupling method is widely adopted in the following software: OpenGeoSys (Shao et al, 2009;Naumov et al, 2022), poreReact (coupling of Open-FOAM (Weller et al, 1998) and Reaktoro) (Oliveira et al, 2019), CSMP++GEM (Yapparova et al, 2019), FEniCS-Reaktoro (Damiani et al, 2020), Osures (Moortgat et al, 2020), FEniCS-based Hydro-Mechanical-Chemical solver (Kadeethum et al, 2021), PorousFlow (based on the MOOSE Framework; Permann et al, 2020) (Wilkins et al, 2021), IC-FERST-REACT (Yekta et al, 2021), COMSOL and PHREEQC (Jyoti and Haese, 2021), GeoChemFoam (coupling of OpenFOAM and PHREEQC) (Maes and Menke, 2021), coupling of Reaktoro and Firedrake (Rathgeber et al, 2016) (Kyas et al, 2022), and P3D-BRNS (Golparvar et al, 2022). For reviews of reactive transport codes and the underlying coupling approaches, we refer the reader to the publications by Gamazo et al (2015), Damiani et al (2020).…”

Section: Coupling Flow Transport and Chemical Equilibriummentioning

confidence: 99%

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Huang,

Flemisch,

Qin

et al. 2023

Geosci. Model Dev.

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Abstract. Reactive transport processes in natural environments often involve many ionic species. The diffusivities of ionic species vary. Since assigning different diffusivities in the advection–diffusion equation leads to charge imbalance, a single diffusivity is usually used for all species. In this work, we apply the Nernst–Planck equation, which resolves unequal diffusivities of the species in an electroneutral manner, to model reactive transport. To demonstrate the advantages of the Nernst–Planck model, we compare the simulation results of transport under reaction-driven flow conditions using the Nernst–Planck model with those of the commonly used single-diffusivity model. All simulations are also compared to well-defined experiments on the scale of centimeters. Our results show that the Nernst–Planck model is valid and particularly relevant for modeling reactive transport processes with an intricate interplay among diffusion, reaction, electromigration, and density-driven convection.

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Section: Coupling Flow Transport and Chemical Equilibriummentioning

confidence: 99%

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Huang,

Flemisch,

Qin

et al. 2023

Geosci. Model Dev.

View full text Add to dashboard Cite

show abstract

“…Due to the simplicity and effectiveness in applying the SNIA coupling between the transport solvers and the chemical equilibrium codes, this coupling method is widely adopted in the following software: OpenGeoSys (Shao et al, 2009;Naumov et al, 2022), poreReact (coupling of OpenFOAM (Weller et al, 1998) and Reaktoro) (Oliveira et al, 2019), CSMP++GEM (Yapparova et al, 2019), FEniCS-Reaktoro (Damiani et al, 2020), Osures (Moortgat et al, 2020), FEniCS-based Hydro-Mechanical-Chemical solver (Kadeethum et al, 2021), PorousFlow (based on the MOOSE Framework (Permann et al, 2020)) (Wilkins et al, 2021), IC-FERST-REACT (Yekta et al, 2021), COMSOL and PHREEQC (Jyoti and Haese, 2021), GeoChem-Foam (coupling of OpenFOAM and PHREEQC) (Maes and Menke, 2021), coupling of Reaktoro and Firedrake (Rathgeber et al, 2016) (Kyas et al, 2022), and P3D-BRNS (Golparvar et al, 2022). For reviews of reactive transport codes and the underlying coupling approaches, we refer the reader to the publications by Gamazo et al (2015); Damiani et al (2020).…”

Section: Coupling Flow Transport and Chemical Equilibriummentioning

confidence: 99%

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Huang

Flemisch

Qin

et al. 2022

Preprint

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Abstract. Reactive transport processes in natural environments often involve many ionic species. The diffusivities of ionic species vary. Since assigning different diffusivities in the advection-diffusion equation leads to charge imbalance, a single diffusivity is usually used for all species. In this work, we apply the Nernst–Planck equation, which resolves unequal diffusivities of the species in an electroneutral manner, to model reactive transport. To demonstrate the advantages of the Nernst–Planck model, we compare the simulation results of transport under reaction-driven flow conditions using the Nernst–Planck model with those of the commonly used single-diffusivity model. All simulations are also compared to well-defined experiments. Our results show that the Nernst–Planck model is valid and particularly relevant for modeling reactive transport processes with an intricate interplay among diffusion, reaction, electromigration, and density-driven convection.

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“…High-resolution image analysis in combination with MICP has been effectively used to quantitatively estimate the porosity and variations in the grain size [9]. The 3D images can be further used for flow, transport and reactive transport simulations either using direct pore-scale simulations [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] or using porenetwork modelling which is efficient for very large models and approximates the pore structure [29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Petrophysical Properties of Porous Rocks Using NMR, Micro-CT, and Fluid Flow Simulations

Jyoti

Haese

2021

Geosciences

Self Cite

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Micro-computed tomography (micro-CT) is increasingly utilized to image the pore network and to derive petrophysical properties in combination with modelling software. The effect of micro-CT image resolution and size on the accuracy of the derived petrophysical properties is addressed in this study using a relatively homogenous sandstone and a heterogenous, highly porous bioclastic limestone. Standard laboratory procedures including NMR (nuclear magnetic resonance) analysis, micro-CT analysis at different image resolutions and sizes and pore-scale flow simulations were used to determine and compare petrophysical properties. NMR-derived pore-size distribution (PSD) was comparable to the micro-CT-derived PSD at a resolution of 7 µm for both the rock types. Porosity was higher using the water saturation method as compared to the NMR method in both rocks. The resolution did not show a significant effect on the porosity of the homogeneous sandstone, but porosity in the heterogeneous limestone varies depending on the location of the sub-sample. The transport regime in the sandstone was derived by simulations and changed with the resolution of the micro-CT image. The transport regime in the sandstone was advection-dominated at higher image resolution and diffusion-dominated when using a lower image resolution. In contrast, advection was the dominant transport regime for the limestone based on simulations using higher and lower image resolutions. Simulation-derived permeability for a 400 Voxel3 image at 7 µm resolution in the Berea sandstone matched laboratory results, although local heterogeneity within the rock plays an integral role in the permeability estimation within the sub-sampled images. The simulation-derived permeability was highly variable in the Mount Gambier limestone depending on the image size and resolution with the closest value to a laboratory result simulated with an image resolution of 2.5 µm and a size of 300 Voxel3. Overall, the study demonstrates the need to decide on micro-CT parameters depending on the type of petrophysical property of interest and the degree of heterogeneity within the rock types.

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Validation of a multicomponent reactive-transport model at pore scale based on the coupling of COMSOL and PhreeqC

Cited by 9 publications

References 37 publications

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0

Comparison of Petrophysical Properties of Porous Rocks Using NMR, Micro-CT, and Fluid Flow Simulations

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