Physical and Chemical Heterogeneity of Aquifers: A Quantitative Geological Investigation

含水层的物理和化学非均质性：定量地质调查

• 批准号: 9526795
• 负责人: J. Matthew Davis
• 金额: $ 16.5万
• 依托单位: University of New Hampshire
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-05-15 至 1999-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9526795&HistoricalAwards=false
• 关键词: Physical; Chemical; Heterogeneity; Aquifers; Quantitative

9526795 Davis One of the major challenges facing hydrogeologists today is the prediction of solute movement in the subsurface. It has been generally recognized that the spatial variation of aquifer permeability is one of the dominant controls on the evolution of a contaminant plume. In addition, recent studies suggest that the spatial variation in aquifer chemical properties may also influence solute movement. One very promising approach to quantifying subsurface variability and the associated contaminant transport is the geostatistical approach. Geostatistical, or stochastic, models represent aquifer properties with spatially correlated random field. In recent years, a wide variety of statistical models have been proposed in the literature to represent the spatial variation of permeability. Some of these models have also been applied to the spatial variation of chemical properties. In general, each model is based on a different method for mathematically representing, or computationally generating, spatially correlated random variables and each exhibits overall differences in appearance. This research investigates how the various statistical models relate to the geological processes of deposition and how geologic information can be used to select and parameterize the most appropriate model. Results from previous work indicate that a quantifiable relationship exists between the sedimentological features of fluvial bounding surfaces and the geostatistical properties of modality and spatial correlation. Fluvial bounding surfaces are hierarchical in nature and it has been observed that, in general, the higher the order of the bounding surface, the higher the probability that the surface separates regions with different mean permeability. The regions of different mean permeability in turn are the dominant control on modality and spatial correlation structure of the statistical models of heterogeneity. With regard to the spatial variation of aquifer chemical properties, very little fi eld data on the spatial patterns of variability. This research will obtain important data on the nature of chemical heterogeneity and its relationship to the geological processes of deposition. The primary objectives of the proposed research are to: 1) empirically investigate the relationship between the correlation structure of permeability and the spatial distribution of hierarchical bounding surfaces; 2) investigate the relationship between the spatial variation of chemical properties and geologic features; and 3) develop an algorithm for coding sedimentological information of depositional environment for the simulation of the physical and chemical heterogeneity. The first phase will investigate the spatial variation of both permeability and chemical properties (mineralogy, grain coatings, surface area, porosity, and cation-exchange capacity) of deposits exposed in New England gravel pits. The results of the field work will be used to develop an algorithm of simulating aquifer heterogeneity. It is anticipated that the algorithm will treat different scales of heterogeneity separately using the indicator formalism and Bayesian statistics. Each geologic setting is unique and any particular outcrop study will not be directly transportable to other sites. However, if the physical and chemical heterogeneity can be related to general geologic properties and sedimentological features, the results of this research will enable much more portability between different geologic settings.

当今水文地质学家面临的主要挑战之一是预测地下溶质的运动。人们普遍认为，含水层渗透率的空间变化是污染物羽流演化的主要控制因素之一。此外，最近的研究表明，含水层化学性质的空间变化也可能影响溶质的运动。一种非常有前途的量化地下变化和相关污染物输送的方法是地质统计学方法。地质统计学或随机模型用空间相关随机场表示含水层性质。近年来，文献中提出了各种各样的统计模型来表示渗透率的空间变化。其中一些模型也被应用于化学性质的空间变化。一般来说，每个模型都基于不同的方法来数学表示或计算生成空间相关的随机变量，并且每个模型在外观上都表现出总体差异。本研究探讨了各种统计模型与沉积地质过程的关系，以及如何利用地质信息来选择和参数化最合适的模型。前人的研究结果表明，河流边界面的沉积学特征与模态和空间相关的地统计学性质之间存在着可量化的关系。河流边界面在本质上是分层的，一般来说，边界面的阶数越高，表面分离出平均渗透率不同区域的概率就越高。不同平均渗透率区域对非均质性统计模型的模态和空间相关结构具有主导控制作用。关于含水层化学性质的空间变异，很少有野外资料反映其空间变异格局。这项研究将获得有关化学非均质性及其与沉积地质过程关系的重要资料。本文的主要研究目标是：1)实证研究渗透率的相关结构与分层边界面的空间分布之间的关系；2)研究化学性质的空间变化与地质特征的关系；3)开发了一种用于模拟沉积环境物理和化学非均质性的沉积学信息编码算法。第一阶段将调查新英格兰砾石坑中暴露矿床的渗透率和化学性质（矿物学、颗粒涂层、表面积、孔隙度和阳离子交换能力）的空间变化。现场工作的结果将用于开发模拟含水层非均质性的算法。预计该算法将使用指标形式化和贝叶斯统计分别处理不同规模的异质性。每个地质环境都是独特的，任何特定的露头研究都不能直接转移到其他地点。然而，如果物理和化学非均质性可以与一般地质性质和沉积学特征联系起来，则本研究的结果将使不同地质环境之间的可移植性大大提高。