Kansas Geological Survey, Open-file Report 96-47
C. D. McElwee and J. J. Butler Jr.
KGS Open File Report 96-47
Prepared for presentation at The American Geophysical Union Fall Meeting in San Francisco, CA, Dec. 17, 1996
Slug tests are widely used to characterize the hydraulic conductivity of a formation. Theoretical models that are linear in form are usually applied to analyze data from slug tests. However, we have observed slug test data at some of our research sites in coarse sand and gravel aquifers that exhibit dependence on initial head and show a systematic lack of fit when analyzed with traditional linear models. In order to analyze these data, we have developed a model (McElwee and Zenner, 1993) that is nonlinear (which explains the dependence on initial head) and allows analysis of data in the underdamped, critically damped, and overdamped regions with no significant lack of fit. The purpose of this paper is to report the application of this model to experimental data that cover a wide range of hydraulic conductivities and a wide range of experimental conditions. We find that the proposed model performs quite suitably over these wide ranges, while reducing to traditional linear models (linear oscillatory, Hvorslev, etc.) when appropriate. This model is of particular use in conditions where traditional linear methods simply can not be meaningfully applied. The proposed model has three parameters: β which is related to radius changes in the water column, A which is related to the nonlinear head losses, and K the hydraulic conductivity which is inversely related to the linear head losses. We find that the model is quite robust in its estimates of K over varying conditions. Although, β and A are somewhat empirical and can not be characterized by basic physics as completely as would be desired, we have enough experimental data to understand the basic controls on these two parameters. In summary, this model will allow a wide range of slug test data to be analyzed with a greater accuracy than traditional linear methods.
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Kansas Geological Survey, Geohydrology
Placed online May 3, 2012
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