碳酸盐岩裂隙网络中酸性矿坑水反应运移数值模拟

袁奕梁; 杨蕴; 宋健; 吴剑锋; 窦智; 王锦国; 吴吉春

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中国环境科学 ›› 2025, Vol. 45 ›› Issue (11) : 6168-6177.

水污染与控制

碳酸盐岩裂隙网络中酸性矿坑水反应运移数值模拟

袁奕梁¹, 杨蕴¹, 宋健¹, 吴剑锋², 窦智¹, 王锦国¹, 吴吉春²

作者信息 +

Numerical simulation of acid mine drainage reactive transport in carbonate rock fracture network

YUAN Yi-liang¹, YANG Yun¹, SONG Jian¹, WU Jian-feng², DOU Zhi¹, WANG Jin-guo¹, WU Ji-chun²

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摘要

为了准确预测裂隙介质中酸性水污染迁移过程和向地表环境的排泄强度,提出了基于升尺度离散裂隙-基质方法(Upscaled Discrete Fracture-Matrix method, UDFM)的模拟技术,该技术通过对裂隙结构进行局部加密并将其映射为等效连续介质模型.在此基础上,构建了碳酸盐岩裂隙网络中酸性矿坑水反应运移数值算例,结合酸性水排泄通量和Damkohler数分析,定量化揭示了关键裂隙参数(裂隙方向、裂隙密度P₃₂)对酸性水迁移过程的影响规律,刻画裂隙与基质的水动力-水化学交互和演化过程.模拟结果表明:裂隙密度越高、裂隙夹角越小(即方向集中),酸性水迁移速率越快、排泄强度越大;连通裂隙优势流现象明显,当裂隙密度较高时,酸性水通过基质扩散至优势通道附近的非连通裂隙,促使非连通裂隙由反应占优向对流占优转变,由于其与下游边界的连通性导致酸性水的排泄强度增大;裂隙密度越低,裂隙方向越集中,在反应系统达到稳定后反应占优的裂隙模拟单元越多,即未充分与酸性水发生中和反应的区域越大.

Abstract

To accurately predict the migration process of acidic minedrainage (AMD) in fractured media and its discharge intensity into the surface environment, an novel simulation technique based on the Upscaled Discrete Fracture-Matrix (UDFM) method is proposedinthisstudy, which involves locally refining the fracture structure and mapping it onto an equivalent continuum model. Building upon this approach, we construct a series of numerical casesfor AMD reactive transport in carbonate fracture networks. By integrating AMD discharge flux analysis with Damkohler number(Da_I), we quantitatively elucidate the influence of key fracture parameters (fracture direction, fracture density P₃₂) on AMD migration patterns and meticulously characterize the hydrogeochemical interactions and their dynamic evolution between fractures and the rock matrix. The simulation results demonstrate that: The higher the fracture density and the smaller the fracture angle (i.e., direction concentrating)correlate with the faster AMD migration rates and increased discharge intensity; conductive fractures dominates preferential flow under high-density conditions, AMD diffuses through the matrix into adjacent non-conductive fractures near preferential pathways, triggering a transition from reaction-dominated (highDa_I) to advection-dominated (lowDa_I) regimes within these fractures. Connectivity to the downstream boundary subsequently amplifies AMD discharge; lower fracture density and greater orientation alignment result in a higher proportion of reaction- dominated simulation units after system stabilization, indicating larger zones of incomplete neutralization.

导出引用

袁奕梁, 杨蕴, 宋健, 吴剑锋, 窦智, 王锦国, 吴吉春. 碳酸盐岩裂隙网络中酸性矿坑水反应运移数值模拟[J]. 中国环境科学. 2025, 45(11): 6168-6177

YUAN Yi-liang, YANG Yun, SONG Jian, WU Jian-feng, DOU Zhi, WANG Jin-guo, WU Ji-chun. Numerical simulation of acid mine drainage reactive transport in carbonate rock fracture network[J]. China Environmental Science. 2025, 45(11): 6168-6177

中图分类号： X703

参考文献

[1] 贾梦旋,王金满,李禹凝,等.基于自然解决方案的矿山生态修复研究进展 [J]. 煤炭科学技术, 2024,52(8):209-221. Jia M, Wang J, Li Y, et al. Ecological restoration of mines based on nature-based solution: a review [J]. Coal Science and Technology, 2024,52(8):209-221.
[2] Bai Q, Tu S. A general review on longwall mining-induced fractures in near-face regions [J]. Geofluids, 2019,2019(19):1-22.
[3] Ning J, Wang J, Tan Y, et al. Mechanical mechanism of overlying strata breaking and development of fractured zone during close- distance coal seam group mining [J]. International Journal of Mining Science and Technology, 2020,30(2):207-215.
[4] Kong X, He D, Liu X, et al. Strain characteristics and energy dissipation laws of gas-bearing coal during impact fracture process [J]. Energy, 2022,242:123028.
[5] Zhang L, Huang M, Li M, et al. Experimental study on evolution of fracture network and permeability characteristics of bituminous coal under repeated mining effect [J]. Natural Resources Research, 2022, 31(1):463-486.
[6] Zheng P, Xia Y, Yao T, et al. Formation mechanisms of hydraulic fracture network based on fracture interaction [J]. Energy, 2022, 243:123057.
[7] Kuzmenko O, Dychkovskyi R, Petlovanyi M, et al. Mechanism of interaction of backfill mixtures with natural rock fractures within the zone of their intense manifestation while developing steep ore deposits [J]. Sustainability, 2023,15(6):4889.
[8] Doolaeghe D, Davy P, Hyman J D, et al. Graph-based flow modeling approach adapted to multiscale discrete-fracture-network models [J]. Physical review E, 2020,102(5):053312.
[9] Hyman J D. Flow channeling in fracture networks: characterizing the effect of intensity on preferential flow path formation [J]. Water Resources Research, 2020,56(9):e2020WR027986.
[10] Liao J, Xu B, Mehmood F, et al. Numerical study of the long-term performance of EGS based on discrete fracture network with consideration of fracture deformation [J]. Renewable Energy, 2023, 216:119045.
[11] Sweeney M R, Hyman J D, O’Malley D, et al. Characterizing the impacts of multi-scale heterogeneity on solute transport in fracture networks [J]. Geophysical Research Letters, 2023,50(21): e2023GL104958.
[12] Han B, Wang S, Zhang Z, et al. Numerical simulation of geothermal reservoir thermal recovery of heterogeneous discrete fracture network-rock matrix system [J]. Energy, 2024,305:132306.
[13] 黄鸿蓝,宋健,杨蕴,等.三维裂隙网络中典型重金属污染物反应运移数值模拟 [J]. 地球科学, 2024,49(8):2879-2890. Huang H, Song J, Yang Y, et al. Reactive transport numerical modeling of typicalheavy metal pollutants in three-dimensional fracture networks [J]. Earth Science, 2024,49(8):2879-2890.
[14] Cacas M, Ledoux E, de Marsily G, et al. Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model. Water Resources Research [J]. 1990,26(3):479-489.
[15] Li X, Li D, Xu Y, et al. A DFN based 3D numerical approach for modeling coupled groundwater flow and solute transport in fractured rock mass [J]. International Journal of Heat and Mass Transfer, 2020, 149:119179.
[16] Tran M, Jha B. Effect of poroelastic coupling and fracture dynamics on solute transport and geomechanical stability [J]. Water Resources Research, 2021,57(10):e2021WR029584.
[17] Zhang X, Ma F, Dai Z, et al. Radionuclide transport in multi-scale fractured rocks: A review [J]. Journal of hazardous materials, 2022, 424:127550.
[18] 黄诗棋,胡立堂,刘东旭,等.裂隙介质中Pu迁移的连续时间随机游走模拟 [J]. 中国环境科学, 2023,43(12):6321-6328. Huang S, Hu L, Liu D, et al. Transport simulation of Pu through fractured media based on continuous time random walk model [J]. China Environmental Science, 2023,43(12):6321-6328.
[19] Masciopinto C, Alghalandis Y F. A new two-step particle tracking and channels model method for preferential 3-D flow and transport in large DFNs of fractured aquifers [J]. Journal of Hydrology, 2024,629: 130566.
[20] Viswanathan H S, Ajo-Franklin J, Birkholzer J T, et al. From fluid flow to coupled processes in fractured rock: Recent advances and new frontiers [J]. Reviews of Geophysics, 2022,60(1):e2021RG000744.
[21] Cavalcante T M, Souza A C R, Hajibeygi H, et al. Simulation of two-phase flow in 3D fractured reservoirs using a projection-based Embedded Discrete Fracture Model on Unstructured tetrahedral grids(pEDFM-U) [J]. Advances in Water Resources, 2024,187: 104679.
[22] Sherman T, Hyman J, Dentz M, et al. Characterizing the influence of fracture intensity on network scale transport [J]. Journal of Geophysical Research: Solid Earth, 2020,125(1):e2019JB018547.
[23] Zhang X, Ma F, Yin S, et al. Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review [J]. Applied Energy, 2021,303:117603.
[24] Ma L, Gao D, Qian J, et al. Multiscale fractures integrated equivalent porous media method for simulating flow and solute transport in fracture-matrix system [J]. Journal of Hydrology, 2023,617:128845.
[25] Andrews E M, Hyman J D, Sweeney M R, et al. Fracture intensity impacts on reaction front propagation and mineral weathering in three-dimensional fractured media [J]. Water Resources Research, 2023,59(2):e2022WR032121.
[26] 佴宇鏖,周佳庆,李长冬,等.基于裂隙网络几何特征参数的岩体溶质传输过程预测模型研究 [J]. 岩土工程学报, 2025,47(8):1641-1652. Nai Y, Zhou J, Li C, et al. Predictive model for solute transport processes in fractured rocks based on geometric parameters of fracture network [J]. Chinese Journal of Geotechnical Engineering, 2025, 47(8):1641-1652.
[27] 王婷,王子龙,李炎隆,等.粗糙裂隙渗流-溶蚀耦合过程可视化试验及渗透性演化规律研究 [J]. 岩土工程学报, 2025,47(8):1662- 1671. Wang T, Wang Z, Li Y, et al. Visualization experiments study on coupling process of flow-erosion in rough fractures and evolution of permeability [J]. Chinese Journal of Geotechnical Engineering, 2025, 47(8):1662-1671.
[28] Wenli Y, Sharifzadeh M, Yang Z, et al. Assessment of fracture characteristics controlling fluid flow performance in discrete fracture networks (DFN) [J]. Journal of Petroleum Science and Engineering, 2019,178:1104-1111.
[29] Yan X, Yu H. Numerical simulation of hydraulic fracturing with consideration of the pore pressure distribution based on the unified pipe-interface element model [J]. Engineering Fracture Mechanics, 2022,275:108836.
[30] Reeves D M, Pham H, Parashar R, et al. Fracture connectivity and flow path tortuosity elucidated from advective transport to a pumping well in complex 3D networks [J]. Engineering Geology, 2023,313: 106960.
[31] Zhao Z, Chen S, Zhang J, et al. In-situ tracer test in fractured rocks for nuclear waste repository [J]. Earth-Science Reviews, 2024,250: 104683.
[32] Lichtner P C, Hammond G E, Lu C, et al. PFLOTRAN user manual: A massively parallel reactive flow and transport model for describing surface and subsurface processes [R]. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); OFM Research, Redmond, WA (United States), 2015.
[33] Hyman J D, Karra S, Makedonska N, et al. dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport [J]. Computers & Geosciences, 2015,84:10-19.
[34] Sweeney M R, Gable C W, Karra S, et al. Upscaled discrete fracture matrix model (UDFM): an octree-refined continuum representation of fractured porous media [J]. Computational Geosciences, 2020,24(1): 293-310.
[35] de Dreuzy J R, Méheust Y, Pichot G. Influence of fracture scale heterogeneity on the flow properties of three-dimensional discrete fracture networks (DFN) [J]. Journal of Geophysical Research: Solid Earth, 2012,117(B11).
[36] Hyman J D, Aldrich G, Viswanathan H, et al. Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size [J]. Water Resources Research, 2016,52(8):6472-6489.
[37] Hyman J D, Painter S L, Viswanathan H, et al. Influence of injection mode on transport properties in kilometer‐scale three‐dimensional discrete fracture networks [J]. Water Resources Research, 2015,51(9): 7289-7308.
[38] Jordan G, Rammensee W. Dissolution rates of calcite (1014) obtained by scanning force microscopy: Microtopography-based dissolution kinetics on surfaces with anisotropic step velocities [J]. Geochimica et Cosmochimica Acta, 1998,62(6):941-947.
[39] Trinchero P, Sanglas J, Iraola A, et al. On the parameterisation of dual-continuum models for reactive transport modelling in fractured media [J]. Journal of Hydrology, 2022,615:128691.