Determining the 3-D spatial distribution of subsurface properties is a critical part of managing the clean-up of contaminated sites. Most standard hydrologic methods sample small regions immediately adjacent to wells or testing devices. This provides data which are not representative of the entire region of interest. Furthermore, at many contaminated sites invasive methods are not acceptable, due to the risks associated with contacting and spreading the contaminants. To address these issues, I have developed a minimally invasive technology that provides information about the 3-D distribution of electrical conductivity. This new technique, cone-based electrical resistivity tomography (C-bert), integrates the existing technologies of resistivity cone penetration testing (RCPT) with electrical resistivity tomography. Development of this tool included the creation of new software and modeling algorithms, the design of field equipment, field testing, and processing and interpretation of the resulting data.; I present a 2.5-D forward modeling algorithm that incorporates an effective correction for the errors caused by boundary effects and source singularities. The algorithm includes an optimization technique for acquiring the Fourier coefficients required for the solution. A 3-D inversion algorithm is presented that has two major improvements over existing algorithms. First, it includes a 3-D version of the boundary correction/source singularity correction developed for the 2.5-D problem. Second, the algorithm can handle any type of acquisition geometry; this was a requirement for the development of C-bert.; C-bert involves placing several permanent current electrodes in the subsurface and using electrodes mounted on a cone penetrometer and at the surface to measure the resultant potential field. In addition to these measurements, we obtain the standard suite of RCPT data, including high resolution resistivity logs. The RCPT data can be used to generate a realistic starting model for the inversion. Furthermore, the resistivity logs can be used as constraints in the inversion of the potential field data. Effective incorporation of resistivity logs into the inversion process, however, requires an understanding the spatial averaging that occurs during logging. I developed a forward modeling and inversion algorithm that allows us to understand and remove the averaging that is present in the logs. A successful field test of C-bert was conducted at the Kidd2 site in Richmond, British Columbia, leading me to conclude that C-bert is a promising new way to image the subsurface.
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