Constructing the Apparent Geological Model by Fusing Surface Resistivity Survey and Borehole Records.

We constructed an apparent geological model with resistivity data from surface resistivity surveys. We developed a data fusion approach by integrating dense electrical resistivity measurements collected with Schlumberger arrays and wellbore logs. This approach includes an optimization algorithm and a geostatistic interpolation method. We first generated an apparent formation factor model from the surface resistivity measurements and groundwater resistivity records with an inverse distance method. We then converted the model into a geology model with the optimized judgment criteria from the algorithms relating the apparent formation factors to the borehole geology. We also employed a non-parametric bootstrap method to analyze the uncertainty of the predicted sediment types, and the predictive uncertainties of clay, gravel, and sand were less than 5%. Overall, our model is capable of capturing the spatial features of the sediment types. More importantly, this approach can be arranged in a self-updated sequence to enable adjustments to the model to accommodate newly collected core records or geophysical data. This approach yields a more detailed apparent geological model for use in future groundwater simulations, which is of benefit to multi-discipline studies.

Assessment of uncertainty in discrete fracture network modeling using probabilistic distribution method.

There have been widespread concerns about solute transport problems in fractured media, e.g. the disposal of high-level radioactive waste in geological fractured rocks. Numerical simulation of particle tracking is gradually being employed to address these issues. Traditional predictions of radioactive waste transport using discrete fracture network (DFN) models often consider one particular realization of the fracture distribution based on fracture statistic features. This significantly underestimates the uncertainty of the risk of radioactive waste deposit evaluation. To adequately assess the uncertainty during the DFN modeling in a potential site for the disposal of high-level radioactive waste, this paper utilized the probabilistic distribution method (PDM). The method was applied to evaluate the risk of nuclear waste deposit in Beishan, China. Moreover, the impact of the number of realizations on the simulation results was analyzed. In particular, the differences between the modeling results of one realization and multiple realizations were demonstrated. Probabilistic distributions of 20 realizations at different times were also obtained. The results showed that the employed PDM can be used to describe the ranges of the contaminant particle transport. The high-possibility contaminated areas near the release point were more concentrated than the farther areas after 5E6 days, which was 25,400 m2.

One-dimensional analytical solution for hydraulic head and numerical solution for solute transport through a horizontal fracture for submarine groundwater discharge.

Submarine groundwater discharge (SGD) has been recognized as a major pathway of groundwater flow to coastal oceanic environments. It could affect water quality and marine ecosystems due to pollutants and trace elements transported through groundwater. Relations between different characteristics of aquifers and SGD have been investigated extensively before, but the role of fractures in SGD still remains unknown. In order to better understand the mechanism of groundwater flow and solute transport through fractures in SGD, one-dimensional analytical solutions of groundwater hydraulic head and velocity through a synthetic horizontal fracture with periodic boundary conditions were derived using a Laplace transform technique. Then, numerical solutions of solute transport associated with the given groundwater velocity were developed using a finite-difference method. The results indicated that SGD associated with groundwater flow and solute transport was mainly controlled by sea level periodic fluctuations, which altered the hydraulic head and the hydraulic head gradient in the fracture. As a result, the velocity of groundwater flow associated with SGD also fluctuated periodically. We found that the pollutant concentration associated with SGD oscillated around a constant value, and could not reach a steady state. This was particularly true at locations close to the seashore. This finding of the role of fracture in SGD will assist pollution remediation and marine conservation in coastal regions.

An Application of Hydraulic Tomography to a Large-Scale Fractured Granite Site, Mizunami, Japan.

While hydraulic tomography (HT) is a mature aquifer characterization technology, its applications to characterize hydrogeology of kilometer-scale fault and fracture zones are rare. This paper sequentially analyzes datasets from two new pumping tests as well as those from two previous pumping tests analyzed by Illman et al. (2009) at a fractured granite site in Mizunami, Japan. Results of this analysis show that datasets from two previous pumping tests at one side of a fault zone as used in the previous study led to inaccurate mapping of fracture and fault zones. Inclusion of the datasets from the two new pumping tests (one of which was conducted on the other side of the fault) yields locations of the fault zone consistent with those based on geological mapping. The new datasets also produce a detailed image of the irregular fault zone, which is not available from geological investigation alone and the previous study. As a result, we conclude that if prior knowledge about geological structures at a field site is considered during the design of HT surveys, valuable non-redundant datasets about the fracture and fault zones can be collected. Only with these non-redundant data sets, can HT then be a viable and robust tool for delineating fracture and fault distributions over kilometer scales, even when only a limited number of boreholes are available. In essence, this paper proves that HT is a new tool for geologists, geophysicists, and engineers for mapping large-scale fracture and fault zone distributions.

Hydraulic tomography for detecting fracture zone connectivity.

Fracture zones and their connectivity in geologic media are of great importance to ground water resources management as well as ground water contamination prevention and remediation. In this paper, we applied a recently developed hydraulic tomography (HT) technique and an analysis algorithm (sequential successive linear estimator) to synthetic fractured media. The application aims to explore the potential utility of the technique and the algorithm for characterizing fracture zone distribution and their connectivity. Results of this investigation showed that using HT with a limited number of wells, the fracture zone distribution and its connectivity (general pattern) can be mapped satisfactorily although estimated hydraulic property fields are smooth. As the number of wells and monitoring ports increases, the fracture zone distribution and connectivity become vivid and the estimated hydraulic properties approach true values. We hope that the success of this application may promote the development and application of the new generations of technology (i.e., hydraulic, tracer, pneumatic tomographic surveys) for mapping fractures and other features in geologic media.

Analysis of karst aquifer spring flows with a gray system decomposition model.

There are approximately 470,000 km(2) of karst aquifers that feed many large springs in North China. Turbulent flow often exists in these karst aquifers, which means that the classical ground water model based on Darcy's law cannot be applied here. Ground water data are rare for these aquifers. As a consequence, it is difficult to quantitatively investigate ground water flow in these karst systems. The purpose of this study is to develop a parsimonious model that predicts karst spring discharge using gray system theory. In this theory, a white color denotes a system that is completely characterized and a black color represents a system that is totally unknown. A gray system thus describes a complex system whose characteristics are only partially known or known with uncertainty. Using this theory, we investigated the karst spring discharge time series over different time scales. First, we identified three specific components of spring discharge: the long-term trend, periodic variation, and random fluctuation. We then used the gray system model to simulate the long-term trend and obtain periodic variation and random fluctuation components. Subsequently, we developed a predictive model for karst spring discharge. Application of the model to Liulin Springs, a representative example of karst springs in northern China, shows that the model performs well. The predicted results suggest that the Liulin Springs discharge will likely decrease over time, with small fluctuations.