Seepage–dissolution in carbonate rock fractures serves as the core driver governing the evolution of key engineering projects, including reservoir dam stability, CO2 geological sequestration, and unstable rock collapse mitigation strategies. While physical heterogeneity (e.g., fracture aperture, mineral distribution) is widely recognized as a critical factor regulating dissolution processes, the specific influence of mineral distribution heterogeneity on dissolution rates still lacks quantitative quantification. To address this gap, this study focuses on limestone fractures and employs multi-component reactive transport numerical simulations to model acidic fluid (pH = 5.0) seepage–dissolution under two Darcy flux conditions (37.8/378 m·yr−1). It investigates the controlling mechanisms of fracture roughness (λb = 0.036~0.308) and calcite contents (55%, 75%, 95%) on dissolution dynamics, and analyzes spatial variations in local Darcy velocity, reaction rate, and effective dissolution rate (Reff,i). Results demonstrate that mineral distribution heterogeneity directly induces pronounced spatial heterogeneity in dissolution behavior: diffusion dominates under low flux (simulation duration: 48.3 days), forming discrete reaction fronts (~15 mm) controlled by mineral clusters; advection prevails under high flux (simulation duration: 4.83 days), generating alternating dissolution–deposition zones (~7.5 mm) with Reff,i one order of magnitude greater than that under low flux. Notably, 55% calcite content yields the highest Reff,i (1.87 × 10−11 mol·m−2·s−1), 0.94 orders of magnitude greater than that at 95% calcite content. A strong linear correlation (R2 > 0.98) exists between the Damköhler number (DaI) and Reff,i at the same calcite content. Furthermore, the synergistic interaction between fracture aperture and mineral heterogeneity amplifies dissolution complexity, with high roughness (λb= 0.308) coupled with 55% calcite content achieving the highest Reff,i of 2.1 × 10−11 mol·m−2·s−1. This study provides critical theoretical insights and quantitative data support for fractured rock mass evolution prediction models, geological hazard prevention, and geological carbon sequestration optimization.
Lei et al. (Wed,) studied this question.