Hydrological Characterization and Petrophysical Analysis of Saturated and Unsaturated Soils from Electrical Response Measurements

通过电响应测量对饱和和非饱和土壤进行水文表征和岩石物理分析

• 批准号: 0309626
• 负责人: Fred Boadu
• 金额: --
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0309626&HistoricalAwards=false
• 关键词: Hydrological; Characterization; Petrophysical; Analysis; Saturated

0309626BoaduSubsurface characterization whether in the saturated or unsaturated zone for the purposes of aquifer characterization, transport of contaminants and design of contaminant remediation strategies, demand accurate and reliable prediction of the petrophysical and hydraulic properties. The primary goal of the proposed research is to develop an integrated approach, which incorporates physico-chemically based model developments, laboratory measurements and interpretational tools using artificial neural networks, to predict saturated or unsaturated hydraulic conductivity, porosity and moisture content of the earth's subsurface from frequency dependent resistivity measurements. Models describing the frequency dependent resistivity of soils based on physico-chemical principles will be developed that will include hydraulic and petrophysical parameters as primary variables. In the first two years, laboratory experiments will be designed to measure frequency dependent resistivity as well as the petrophysical and hydraulic properties of over 100 soil samples from different geological environments. The soil samples will be fully characterized by measuring their hydraulic conductivity, porosity, density, moisture content and particle size distribution (clay and organic matter content) in the laboratory. Acceptable Pedo-transfer functions will be used to provide useful information on both saturated or unsaturated hydraulic conductivities. In the final year, the capabilities of artificial neural networks (ANN) to adapt, generalize and identify non-linearities in relationships among complex and coupled variables, will be explored to determine the functional relationships between the spectral electrical response of soils and their hydraulic and petrophysical properties. Uncertainties in the predicted variables in the proposed prediction method due to noise and model parameter misrepresentations and inefficiencies in the training method will be assessed.

0309626 Boadu地下表征无论是在饱和或非饱和区的含水层表征的目的，污染物的运输和污染物修复策略的设计，要求准确和可靠的预测岩石物理和水力特性。 拟议的研究的主要目标是开发一种综合方法，它结合了物理化学为基础的模型开发，实验室测量和解释工具，使用人工神经网络，预测饱和或不饱和的水力传导率，孔隙度和水分含量的地球的地下频率依赖电阻率测量。将开发基于物理化学原理的土壤频率相关电阻率模型，其中包括水力和岩石物理参数作为主要变量。在头两年，将设计实验室实验来测量频率相关的电阻率以及来自不同地质环境的100多个土壤样品的岩石物理和水力特性。将在实验室测量土壤样品的导水率、孔隙率、密度、含水量和颗粒大小分布（粘土和有机物含量），以充分确定土壤样品的特性。可接受的土壤传递函数将用于提供有关饱和或非饱和水力传导率的有用信息。在最后一年，人工神经网络（ANN）的能力，以适应，概括和识别复杂和耦合变量之间的关系的非线性，将探讨确定土壤的光谱电响应和它们的水力和岩石物理特性之间的函数关系。将评估由于噪声和模型参数误报以及训练方法效率低下而导致的拟议预测方法中预测变量的不确定性。