Multi-rate mass transfer modeling of two-phase flow in highly heterogeneous fractured and porous media
Multi-rate mass transfer modeling of two-phase flow in highly heterogeneous fractured and porous media
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DOI：
10.1016/j.advwatres.2016.02.010
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发表时间：
2016-05
影响因子：
4.7
通讯作者：
J. Tecklenburg;I. Neuweiler;J. Carrera;M. Dentz
中科院分区：
文献类型：
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作者：
J. Tecklenburg;I. Neuweiler;J. Carrera;M. Dentz
我们研究高度非均质裂缝和多孔介质中的两相流模型。高渗透性（移动的）裂缝域和低渗透性（不移动的）基质块之间的质量传递强烈影响流动行为。我们量化的有效的两相流行为，使用多速率传质（MRMT）的方法。我们讨论的MRMT方法的适用范围在相关的粘性和毛细扩散的时间尺度。我们仔细研究的线性化的毛细管扩散在不动的区域，这使得MRMT的非本地单方程模型的形式制定。全局记忆函数是该方法的核心，它对移动的和非移动的区域之间的质量传递进行编码。我们提出了两种方法来估计的整体记忆功能的裂缝网络与给定的裂缝和矩阵的几何形状。两者都采用了缩放方法的基础上，已知的本地记忆功能为一个给定的不动区域。第一种方法是数值计算局部记忆函数，而第二种方法采用截断幂律形式的参数记忆函数。开发的概念应用和测试不同复杂性的裂缝网络。我们发现，这两个物理为基础的参数估计方法的全局记忆功能提供了预测MRMT方法的描述在高度非均质多孔介质中的多相流。
We study modeling of two-phase flow in highly heterogeneous fractured and porous media. The flow behaviour is strongly influenced by mass transfer between a highly permeable (mobile) fracture domain and less permeable (immobile) matrix blocks. We quantify the effective two-phase flow behavior using a multirate rate mass transfer (MRMT) approach. We discuss the range of applicability of the MRMT approach in terms of the pertinent viscous and capillary diffusion time scales. We scrutinize the linearization of capillary diffusion in the immobile regions, which allows for the formulation of MRMT in the form of a non-local single equation model. The global memory function, which encodes mass transfer between the mobile and the immobile regions, is at the center of this method. We propose two methods to estimate the global memory function for a fracture network with given fracture and matrix geometry. Both employ a scaling approach based on the known local memory function for a given immobile region. With the first method, the local memory function is calculated numerically, while the second one employs a parametric memory function in form of truncated power-law. The developed concepts are applied and tested for fracture networks of different complexity. We find that both physically based parameter estimation methods for the global memory function provide predictive MRMT approaches for the description of multiphase flow in highly heterogeneous porous media.