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The relationship between the hydrogeologic properties and sedimentary fades of shallow Pennsylvanian bedrock aquifers was examined using detailed sedimentologic descriptions, aquifer (slug) tests, and gamma ray logs. The main goal of the study was to determine if it was possible to reliably estimate near‐well hydraulic conductivities using core descriptions and logging data at a complex field site, based on assignment of consistent conductivity indicators to individual facies. Lithologic information was gathered from three sources: core descriptions, simplified lithologic columns derived from the core descriptions, and drillers’ logs. Gamma ray data were collected with a conventional logging instrument. Slug tests were conducted in all wells containing screened zones entirely within the Pennsylvanian facies of interest. Simplified subsets of sedimentologic facies were assembled for classification of subsurface geology, and all rocks within the screened intervals of test wells were assigned to individual facies based on visual descriptions. Slug tests were conducted to determine the bulk hydraulic conductivity (a spatial average within the screened interval) in the immediate vicinity of the wells, with measured values varying from 10−4 m/s to 10−8 m/s. Gamma ray logs from these wells revealed variations in raw counts above about 1.5 orders of magnitude. Data were combined using simple linear and nonlinear inverse techniques to derive relations between sedimentologic facies, gamma ray signals, and bulk hydraulic conductivities. The analyses suggest that facies data alone, even those derived from detailed core descriptions, are insufficient for estimating hydraulic conductivity in this setting to better than an order of magnitude. The addition of gamma ray data improved the estimates, as did selective filtering of several extreme values from the full data set. Better estimates might be obtained through more careful field measurements and reduction of associated errors, collection and incorporation of some form of continuous porosity log, or use of spatial statistics or more sophisticated inversion techniques. The utility of the approach remains to be tested through modeling and additional direct measurements.

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