Seismic refraction methods are used in environmental and engineering studies to image the shallow subsurface. We present a blind test of inversion and tomographic refraction analysis methods using a synthetic first-arrival-time dataset that was made available to the community in 2010. The data are realistic in terms of the near-surface velocity model, shot-receiver geometry and the data's frequency and added noise. Fourteen estimated models were determined by ten participants using eight different inversion algorithms, with the true model unknown to the participants until it was revealed at a session at the 2011 SAGEEP meeting. The estimated models are generally consistent in terms of their large-scale features, demonstrating the robustness of refraction data inversion in general, and the eight inversion algorithms in particular. When compared to the true model, all of the estimated models contain a smooth expression of its two main features: a large offset in the bedrock and the top of a steeply dipping low-velocity fault zone. The estimated models do not contain a subtle low-velocity zone and other fine-scale features, in accord with conventional wisdom. Together, the results support confidence in the reliability and robustness of modern refraction inversion and tomographic methods.
We present a method of aquifer characterization that is able to utilize multiple sources of conditioning data to build a more realistic model of heterogeneity. This modeling approach (InMod) uses geophysical data to delineate bounding surfaces within sedimentary deposits. The depositional volumes between bounding surfaces are identified automatically from the geophysical data by a region growing algorithm. Simple geometric rules are used to constrain the growth of the regions in 3-D. The nodes within the depositional volume are assigned to categorical lithologies using geostatistical realizations and a dynamic lookup routine that can be conditioned to field data. The realizations created with this method preserve geologically expected features and produces sharp juxtapositions of high and low hydraulic conductivity lithologies along bounding surfaces. The realizations created with InMod also have higher variance than models created only with geostatistics and honor the
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