ISSN 1000-3665 CN 11-2202/P

    低渗透岩土有效扩散系数的室内测定与分析

    Laboratory determination and analysis of effective diffusion coefficients for low-permeability rock and clay

    • 摘要: 低渗透岩土是水文地质及环境地质研究的重点关注对象,有效扩散系数是研究低渗透岩土的关键参数之一。文章以原状黏土和粉砂质黏土为例,以Cl-为示踪剂,利用自主研发的室内径向扩散实验装置,建立Cl-径向运移模型,模拟其扩散运移过程。以实验模型为初始条件和边界条件,利用COMSOL软件模拟溶质理论浓度随时间变化的曲线,与实验数据进行拟合,利用绝对残差平均值进行理论浓度与实测值拟合优度统计,提取试样的有效扩散系数。结果表明:试样塘沽G1孔101.2~101.5 m、苏北SY1孔147.1~147.3 m、170.48~170.68 m的有效扩散系数分别为6.0×10-10 m2/s、4.5×10-10 m2/s、3.9×10-10 m2/s 时,理论浓度的绝对残差平均值最小,且孔隙度和有效扩散系数高度相关,进一步证明了该实验方法的可行性。同时,利用Archie定律有效孔隙度与有效扩散系数的关系,取常量n=1.9,预测了试验样品的有效孔隙度,分别为0.26,0.19,0.16。

       

      Abstract: Low-permeability rock and clay are focuses in hydrogeology and environmental geology research objects. Physical movement of dissolved species through these media is mainly governed by diffusion processes. In this study, intact clay and silty clay are used as examples, and Cl- as a tracer. The migration model and radial diffusion process of Cl- are established depending on the radial diffusion experimental apparatus. Data fitting and average absolute residual analysis of the theoretical concentrations and the measured values are performed by using the Comsol software, based on the initial and boundary conditions of the experimental model. The effective diffusion coefficients are considered in the simulation of transport coupled with the experimentally calculated values. The results show that the effective diffusion coefficients of G1-Core (with the depth of 101.2~101.5 m) and SY1-Core (with the depth of 147.1~147.3 m and 170.48~170.68 m) samples are 6.0×10-10 m2/s, 4.5×10-10 m2/s and 3.9×10-10 m2/s with the lowest average absolute residual, respectively. The linear relationship of the effective diffusion coefficient and porosity also demonstrates the feasibility of the test method. Furthermore, the relationship between the effective diffusion coefficient of Cl- and the diffusion-accessible porosity can be described by the Archie’s law with the exponent n=1.9 of the fine-grained soil. It is applied to predict the effective porosity of samples.

       

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