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arxiv: 2605.18223 · v1 · pith:MJTNLQFEnew · submitted 2026-05-18 · ⚛️ physics.flu-dyn

Dynamic Evolution of Pore-scale Heterogeneity and Transport Conditions Control Mineral Dissolution Regimes

Jinlei Wang , Yongfei Yang , Martin J. Blunt , Branko Bijeljic This is my paper

Pith reviewed 2026-05-20 00:24 UTC · model grok-4.3

classification ⚛️ physics.flu-dyn
keywords mineral dissolutionporous mediapore-scale heterogeneitychanneled dissolutionpermeability-porosity relationshipreactive transportmicro-CT imagingmicro-continuum simulation
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0 comments X

The pith

Initial flow heterogeneity in rocks controls reactant access and drives dynamic channeled dissolution with time-varying permeability scaling.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes that static regime diagrams based on dimensionless numbers fail for complex rocks because initial flow heterogeneity determines which mineral surfaces receive fresh reactant. This steers dissolution along dynamic trajectories where pore structure and flow field reorganize together into channeled patterns. The resulting permeability-porosity relation cannot be captured by any fixed power law; instead the effective exponent grows with heterogeneity and changes over time, reaching maxima of 9.8, 18.0 and 40.9 in the three samples. Effective reaction rates therefore fall one to three orders of magnitude below uniform-dissolution predictions because mass-transfer limitations intensify inside the channels.

Core claim

Initial flow heterogeneity controls the accessibility of reactants to mineral surfaces, thereby setting the dissolution regime and converting what were thought to be static regimes into dynamic trajectories. Channeled dissolution appears as a joint reorganization of pore structure and flow distribution. The permeability-porosity relation that results cannot be described by one fixed power law; the effective exponent grows with the degree of heterogeneity and evolves with time, reaching maximum values of 9.8, 18.0, and 40.9 in the three rock samples examined. This causes the effective reaction rate to fall one to three orders of magnitude below the rate expected for uniform dissolution, with

What carries the argument

The coupled evolution of dissolution morphology, velocity distribution, and reaction rate tracked in three-dimensional micro-continuum simulations on micro-CT images of three heterogeneous rock samples.

If this is right

  • Permeability rises with porosity according to a time-dependent power law whose exponent increases with initial flow heterogeneity.
  • Effective reaction rates are suppressed by one to three orders of magnitude relative to uniform-dissolution models.
  • Channeled dissolution morphology forms through simultaneous reorganization of structure and flow field.
  • Mass-transfer limitations grow stronger as initial flow heterogeneity increases.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Reactive-transport models at larger scales may need to track evolving heterogeneity rather than rely on static Pe-Da diagrams to avoid overestimating dissolution.
  • Field applications such as acidizing or carbon storage could produce slower mineral alteration than expected when initial flow variations are present.
  • Laboratory tests varying starting flow distributions could check whether the reported exponent maxima scale directly with a simple heterogeneity metric.

Load-bearing premise

The simulations on the three rock images correctly capture the real pore-scale coupling of hydrodynamics, transport, and reaction kinetics without significant numerical artifacts or sample-selection bias.

What would settle it

Direct pore-scale imaging during dissolution that shows reaction rates matching uniform predictions or a permeability-porosity relationship following a single fixed power law independent of heterogeneity level would contradict the central claim.

Figures

Figures reproduced from arXiv: 2605.18223 by Branko Bijeljic, Jinlei Wang, Martin J. Blunt, Yongfei Yang.

Figure 1
Figure 1. Figure 1: Pore-scale characterization and heterogeneity quantification of the three representative [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: (a–c) 3D visualizations of the dissolved solid with semi-transparent pore space in the [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: (a) The maximum exponent, nmax as a function of P e for the three rock samples. The dashed line at nmax=4 marks the channeled dissolution threshold, the shaded band marks the borderline zone (3.5≤nmax≤4.5). (b) Channel decay ratio Rdecay=(nmax−n2000)/nmax versus nmax, where n2000 is the exponent at 2000 PV, with marker size scaled to log(P e). Shaded convex hulls enclose the data range of each rock. (c) Ve… view at source ↗
Figure 4
Figure 4. Figure 4: a tracks the joint evolution of the exponent n(PV) and the normalized flow heterogeneity CVv(t)/CVv, as a function of PV. Figure 4d visualizes the corresponding 3D streamline behaviors at three characteristic stages: t1 (PV = 0, initial), t2 (PV = 600, channel emergence), and t3 (PV = 1200, channel widening), and the corresponding velocity PDF evolution is shown in Figure S3. From PV = 0, n and CVv(t)/CVv … view at source ↗
read the original abstract

Mineral dissolution in porous media is classically partitioned into static regimes within the Pe-Da plane, but this framework fails to capture the dissolution behavior of structurally complex rocks. Using three-dimensional micro-continuum simulations on micro-CT images of three rock samples spanning a wide range of pore-space heterogeneity, we track the joint evolution of dissolution morphology, velocity distribution, and reaction rate. Our results reveal that initial flow heterogeneity controls accessibility of reactants, thereby controlling the dissolution regime,reshaping them as dynamic trajectories. Channeled dissolution emerges as a simultaneous reorganization of structure and flow, and the resulting permeability-porosity relationship cannot be captured by a single power-law. The effective power-law exponent increases with heterogeneity and changes over time, reaching a maximum of 9.8, 18.0, and 40.9 for the three samples. Consequently, the effective reaction rate falls one to three orders of magnitude below the uniform dissolution prediction, with the suppression scaling with flow heterogeneity due to mass transfer limitations in channeled dissolution.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 3 minor

Summary. The manuscript reports 3D micro-continuum simulations of mineral dissolution performed on micro-CT images of three rock samples spanning a range of pore-space heterogeneity. It claims that initial flow heterogeneity governs reactant accessibility and thereby sets the dissolution regime, which then evolves dynamically rather than remaining static in the Pe-Da plane. Channeled dissolution is shown to reorganize both structure and flow simultaneously, so that the permeability-porosity relationship cannot be described by a single power law; instead the effective exponent increases with heterogeneity, varies in time, and reaches maxima of 9.8, 18.0 and 40.9 for the three samples. As a direct consequence the effective reaction rate is suppressed by one to three orders of magnitude relative to the uniform-dissolution prediction, with the degree of suppression scaling with flow heterogeneity because of mass-transfer limitations inside channels.

Significance. If the numerical results are robust, the work provides a clear mechanistic explanation for why classical static regime diagrams fail in structurally complex rocks and supplies quantitative evidence that permeability evolution must be treated as a time-dependent, heterogeneity-dependent process. The image-based approach and the reported range of effective exponents (up to 40.9) would be directly useful for upscaling dissolution in carbon-storage and acid-stimulation models. The demonstration that rate suppression scales with initial heterogeneity is a falsifiable prediction that could be tested experimentally.

major comments (3)
  1. §3 (Numerical Methods) and §4 (Results): the central quantitative claims—exponent maxima of 9.8/18.0/40.9 and 1–3 order-of-magnitude rate suppression—are presented as direct outputs of the micro-continuum solver, yet no mesh-sensitivity study, grid-convergence test, or comparison against a resolved sharp-interface benchmark is reported. Because the permeability-porosity scaling and the degree of channeling are known to be sensitive to artificial diffusion at the solid-fluid interface, the absence of such checks makes the reported exponents and suppression factors load-bearing but unverified.
  2. §3.2 (Micro-continuum formulation): the volume-fraction update and smoothed reaction term are used to represent the moving interface. If the grid spacing is comparable to or larger than the local reaction-front thickness in the smallest pores, numerical diffusion can either suppress or artificially enhance channeling. This directly affects the time evolution of the velocity distribution and the recomputed permeability values that underlie the high reported exponents; an explicit demonstration that the chosen resolution resolves the front in all three samples is required.
  3. §5 (Discussion): the claim that the permeability-porosity trajectory 'cannot be captured by a single power-law' rests on post-processed fits whose R² values or residual statistics are not shown. Without these diagnostics it is unclear whether the time-varying exponent description is necessary or whether a more complex but still static functional form could suffice.
minor comments (3)
  1. Abstract: 'regime,reshaping' is missing a space.
  2. Figure 4 (or equivalent permeability-porosity plot): the time-dependent exponent curves should be accompanied by the instantaneous R² of each power-law fit so readers can judge the quality of the local approximation.
  3. The three samples are referred to only by labels (e.g., Sample A, B, C); a brief table summarizing their initial porosity, permeability, and heterogeneity metrics (e.g., velocity variance or coordination-number distribution) would help readers assess the generality of the reported exponent range.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed comments, which have helped us improve the clarity and robustness of our numerical results. We address each major comment point by point below and have revised the manuscript to incorporate additional validation and statistical details.

read point-by-point responses

  1. Referee: §3 (Numerical Methods) and §4 (Results): the central quantitative claims—exponent maxima of 9.8/18.0/40.9 and 1–3 order-of-magnitude rate suppression—are presented as direct outputs of the micro-continuum solver, yet no mesh-sensitivity study, grid-convergence test, or comparison against a resolved sharp-interface benchmark is reported. Because the permeability-porosity scaling and the degree of channeling are known to be sensitive to artificial diffusion at the solid-fluid interface, the absence of such checks makes the reported exponents and suppression factors load-bearing but unverified.

    Authors: We agree that explicit mesh-sensitivity and convergence checks strengthen the quantitative claims. In the revised manuscript we have added a dedicated subsection in §3 reporting grid-convergence tests performed on representative sub-volumes of all three samples. These tests confirm that the reported maximum exponents (9.8, 18.0, 40.9) and rate-suppression factors remain within 5 % under successive refinement. While a full sharp-interface benchmark on the entire 3D micro-CT domains is computationally prohibitive, we have included validation against analytical and literature benchmark cases for simpler geometries and note that the micro-continuum formulation has been cross-checked in prior work. The new convergence data are now presented in the main text and supplementary figures. revision: yes

  2. Referee: §3.2 (Micro-continuum formulation): the volume-fraction update and smoothed reaction term are used to represent the moving interface. If the grid spacing is comparable to or larger than the local reaction-front thickness in the smallest pores, numerical diffusion can either suppress or artificially enhance channeling. This directly affects the time evolution of the velocity distribution and the recomputed permeability values that underlie the high reported exponents; an explicit demonstration that the chosen resolution resolves the front in all three samples is required.

    Authors: We thank the referee for highlighting the importance of front resolution. In the revised §3.2 we now provide an explicit estimate of local reaction-front thickness (derived from the local Damköhler number and pore-scale length scales) for each sample and compare it directly to the grid spacing. The analysis shows that the grid resolves the front by at least a factor of three in the dominant flow channels across all samples. We have added a supplementary figure illustrating this ratio and confirmed that the velocity-distribution evolution and permeability recomputation are insensitive to moderate changes in the smoothing length within the converged regime. revision: yes

  3. Referee: §5 (Discussion): the claim that the permeability-porosity trajectory 'cannot be captured by a single power-law' rests on post-processed fits whose R² values or residual statistics are not shown. Without these diagnostics it is unclear whether the time-varying exponent description is necessary or whether a more complex but still static functional form could suffice.

    Authors: We accept that fit-quality diagnostics should have been reported. In the revised §5 and supplementary material we now include R² values, root-mean-square residuals, and Akaike information criterion comparisons for both single power-law fits and the time-dependent exponent description. The single power-law fits yield R² < 0.65 for later dissolution stages with systematic residuals, whereas the dynamic-exponent model consistently achieves R² > 0.92. We also discuss why a more elaborate but static functional form cannot reproduce the observed reorganization of flow paths and the associated temporal increase in effective exponent. revision: yes

Circularity Check

0 steps flagged

No circularity: results are direct simulation outputs

full rationale

The paper reports outcomes from 3D micro-continuum simulations performed on micro-CT images of three rock samples. Claims regarding initial flow heterogeneity controlling reactant accessibility, the emergence of channeled dissolution as simultaneous structure-flow reorganization, time-varying permeability-porosity power-law exponents (maxima 9.8, 18.0, 40.9), and effective reaction rate suppression are presented as post-processed observations extracted from the simulation trajectories. No load-bearing step reduces by construction to a fitted parameter, self-citation, or ansatz; the derivation chain consists of numerical experiments whose outputs are independent of the target quantities by design.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the micro-continuum simulation method for capturing pore-scale coupled processes and on the three rock samples representing a wide range of heterogeneity.

axioms (1)
  • domain assumption Micro-continuum simulations on micro-CT images can accurately represent pore-scale flow, transport, and mineral dissolution kinetics.
    Invoked by the choice of method and data source in the abstract.

pith-pipeline@v0.9.0 · 5716 in / 1341 out tokens · 66293 ms · 2026-05-20T00:24:59.339916+00:00 · methodology

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Reference graph

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