Collaborative Research: Solute Transport in Multimodal, Heterogeneous Geological Formations, Combining Sedimentologic and Engineering Approaches

0001165 Rubin我们将开发一个分层空间随机函数（HSRF）模型，该模型代表颗粒含水层系统中边界面定义的渗透率、沉积结构和沉积单元。 在最小的尺度上，相被定义为单峰渗透率区域，如果存在，则为与纹层具有共同方向的交叉地层集。 相将由具有由层理和/或交叉地层组的方向控制的各向异性相关性的连续随机变量表示。 相的组合，例如填充单个通道的相的组合，将由指示随机变量和表示每个相的比例、几何形状和并置的相关转移概率来表示。 复杂的相组合，如并列通道填充，酒吧加积，和河道带沉积物内的漫滩组合，是由一个更高层次的指示随机变量与过渡概率代表的组合的比例，几何形状和并列。 所有三个水平的连续变量和指示变量将在单个HSRF模型中进行数学表达，该模型适用于与溶质扩散的分析表达式整合。 HSRF模型与当前的模型和方法不同，因为它可以捕获复杂的非高斯空间分布，并可以结合解释沉积学来约束地质统计学模型。在结合实地研究和模型气质，我们试图解决以下问题有关（1）在粒状介质中的渗透率分布和（2）溶质扩散。 (1)与渗透率分布有关的问题： HSRF模型及其三个层次是否捕捉到了渗透率和沉积结构的方面，这些方面对于理解典型羽流尺度下的溶质扩散很重要？ o任何一个层级的属性是否与另一个层级的属性相关？ HSRF模型能否用于改进未知位置渗透率的条件估计？ HSRF模型能否作为一个框架，在开发地质学模型时纳入地质/沉积学软数据？ (2)与溶质扩散相关的问题： 三个层次对纵向和横向溶质扩散的相对贡献是什么？ 随着单变量统计学和渗透率的空间相关性在相边界之间变得越来越不同，溶质扩散的时刻在什么时候受到显著影响？ o在什么情况下可以忽略任何层级的表示？ o在什么条件下可以用有效的、依赖于羽流尺度的参数来模拟多模态异质性中的输运？ 为了回答这些问题，我们正在进行一个跨学科的合作项目，涉及加州大学伯克利分校和赖特州立大学的研究人员。 与过去在赖特州立大学由URI资助的项目一样，该项目将为本科生提供研究经验。

0001165RubinWe will develop a hierarchical spatial random function (HSRF) model that represents permeability, sedimentary structures, and sedimentary units defined by bounding surfaces in granular aquifer systems. At the smallest scale, facies are defined as regions of unimodal permeability and, if present, of cross-strata sets with common orientation to the laminae. Facies will be represented by a continuous random variable having anisotropic correlation controlled by bedding and/or the orientation of cross-strata sets. Assemblages of facies, such as the combination of facies filling a single channel, will be represented by an indicator random variable and associated transition probabilities which represent the proportions, geometries, and juxtapositioning of each facies. A complex of facies assemblages, such as juxtaposed channel fill, bar accretion, and overbank assemblages within channel belt deposits, is represented by a higher-tier indicator random variable with transition probabilities representing the proportions, geometries, and juxtapositioning of the assemblages. The continuous and indicator variables of all three levels will be mathematically expressed in a single HSRF model suitable for integration with analytical expressions for solute spreading. The HSRF model departs from current models and approaches in that it can capture complex, non-Gaussian spatial distributions and can incorporate interpretive sedimentology to constrain the geostatistical models. In combined field studies and model temperament, we seek to address the following questions relating to (1) the distribution of permeability in granular media and (2) solute spreading. (1) Questions relating to distribution of permeability: o Does the HSRF model, with its three hierarchical levels, capture the aspects of permeability and sedimentary structure important for understanding solute spreading at the scale of typical plumes? o Are the attributes of any one hierarchical level correlated with those of another level? o Can the HSRF model be used to improve the conditional estimation of permeability at unknown locations? o Can the HSRF model be used as a framework for incorporating geological/sedimentological soft data as geostatisticl models are developed? (2) Questions related to solute spreading: o What are the relative contributions of the three hierarchical levels to both longitudinal and lateral solute spreading? o As the univariate statististics and the spatial correlation of permeability become increasingly different across facies boundaries, at what point are the moments of solute spreading significantly affected? o Under what conditions can representation of any of the hierarchical levels be ignored? o Under what conditions can transport in a multimodal heterogeneity be modeled with effective, plume-scale-dependent parameters? To answer these questions, we are conducting a collaborative, interdisciplinary project involving investigators at both the University of California, Berkeley, and Wright State University. As in past URI-funded projects at Wright State University, the project will provide research experiences for undergraduates.