Ground-penetrating radar (GPR) attenuation-difference analysis can be a useful tool for studying fluid transport in the subsurface. Surface-based reflection attenuation-difference tomography poses a number of challenges that are not faced by crosshole attenuation surveys. We create and analyze a synthetic attenuation-difference GPR data set to determine methods for processing amplitude changes and inverting for conductivity differences from reflection data sets. Instead of using a traditional grid-based inversion, we use a data-driven adaptive-meshing algorithm to alter the model space and to create a more even distribution of resolution. Adaptive meshing provides a method for improving the resolution of the model space while honoring the data limitations and improving the quality of the attenuation difference inversion. Comparing inversions on a conventional rectangular grid with the adaptive mesh, we find that the adaptively meshed model reduces the inversion computation time by an average of 75 with an improvement in the root mean square error of up to 15. While the sign of the conductivity change is correctly reproduced by the inversion algorithm, the magnitude varies by as much as much as 50 from the true values. Our heterogeneous conductivity model indicates that the attenuation difference inversion algorithm effectively locates conductivity changes, and that surface-based reflection surveys can produce models as accurate as traditional crosshole surveys.
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