CHARACTERIZING HYDROGEOLOGIC HETEROGENEITY USING GEOPHYSICAL METHODS: FROM LABORATORY-SCALE OBSERVATIONS TO FIELD-SCALE APPLICATIONS

One of the key challenges, in many hydrogeologic studies, is obtaining the data required to develop a model of the subsurface that captures the spatial heterogeneity in hydrologic properties. While standard methods, involving drilling and direct sampling, can provide accurate information at the sampled location, they are inherently limited in terms of the volume and density of the sampling. Geophysical methods provide ways of non-invasively sampling the subsurface over large regions, and can yield high-resolution geophysical images. The challenge is retrieving, from the imaged geophysical properties, information about the subsurface properties of interest. The focus of our research is the sensitivity of the electromagnetic properties of Earth materials to the presence of fluids, and to the material properties that govern their movement.

Laboratory studies of the dielectric constant, electrical conductivity, and proton-NMR response of rocks and soils are providing a growing understanding of the relationships between these geophysical properties, all of which can be measured remotely, and material properties such as water content, salinity, clay content, surface area, and permeability. Using these relationships as the basis for field-scale applications, in the acquisition and interpretation of geophysical data, requires unraveling the complex interaction between the physics of the geophysical measurement, and the spatial heterogeneity of the subsurface. We can use geophysical methods to map out interfaces between regions with dissimilar properties, but there is a need for controlled field experiments to develop an improved understanding of which interfaces are captured, and why, in a geophysical image. Data acquired with geophysical methods can be used to obtain information about the magnitude and correlation structure of subsurface properties, but the scale of the geophysical measurement has a significant impact on the derived information, and must be accounted for. Building on laboratory observations to advance field-scale applications requires exploring new ways of acquiring, inverting, and transforming geophysical field data.