Non‐Fickian transport through two‐dimensional rough fractures: Assessment and prediction

Non‐Fickian transport through two‐dimensional rough fractures: Assessment and prediction
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DOI:
10.1002/2013wr014459
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发表时间:
2014-02
影响因子:
5.4
通讯作者:
Lichun Wang;M. Cardenas
Lichun Wang;M. Cardenas
中科院分区:
地球科学1区
文献类型:
--
作者:
Lichun Wang;M. Cardenas

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非Fickian输运普遍存在于裂隙地质介质中的所有尺度上。因此,通过单一裂缝的非Fickian输运的详细表征对于预测溶质和其他流体承载实体通过裂缝介质的命运至关重要。我们通过二维粗糙壁裂缝的溶质运移的直接数值模拟显示了穿透曲线(BTC)的早期到达和重尾,这是非Fickian运移的显著特征。使用标准平流-弥散方程(ADE)进行弥散系数(DADE)分析,导致误差随裂缝非均质性线性增加。估计的泰勒色散系数偏离估计的DADE,即使在较高的Peclet数。或者,我们使用具有截断幂律转移率概率的连续时间随机游走(CTRW)模型来表征非菲克传输。CTRW建模显着和一致地改善拟合BTC相对于那些拟合ADE解决方案。从Fickian到非Fickian迁移的偏差程度由截断幂律的参数β捕获。我们发现β与裂缝非均匀性成正比。我们还发现,CTRW传输速度可以预测的基础上的流速。沿着预测β的能力,这是使用可测量的物理性质预测通过CTRW的传输的重要一步。
Non‐Fickian transport ubiquitously occurs across all scales within fractured geological media. Detailed characterization of non‐Fickian transport through single fractures is thus critical for predicting the fate of solutes and other fluid‐borne entities through fractured media. Our direct numerical simulations of solute transport through two‐dimensional rough‐walled fractures showed early arrival and heavy tailing in breakthrough curves (BTCs), which are salient characteristics of non‐Fickian transport. Analyses for dispersion coefficients (DADE) using the standard advection‐dispersion equation (ADE) led to errors which increased linearly with fracture heterogeneity. Estimated Taylor dispersion coefficients deviated from estimated DADE even at higher Peclet numbers. Alternatively, we used continuous time random walk (CTRW) model with truncated power law transition rate probability to characterize the non‐Fickian transport. CTRW modeling markedly and consistently improved fits to the BTCs relative to those fitted with ADE solutions. The degree of deviation of transport from Fickian to non‐Fickian is captured by the parameter β of the truncated power law. We found that β is proportional to fracture heterogeneity. We also found that the CTRW transport velocity can be predicted based on the flow velocity. Along with the ability to predict β, this is a major step toward prediction of transport through CTRW using measurable physical properties.