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Assessment of NMR Logging for Estimating Hydraulic Conductivity in Glacial Aquifers
Authors:Alexander K Kendrick  Rosemary Knight  Carole D Johnson  Gaisheng Liu  Steven Knobbe  Randall J Hunt  James J Butler Jr
Institution:1. Department of Geophysics, Stanford University, 397 Panama Mall, Stanford, CA, 94305 USA;2. U.S. Geological Survey, 11 Sherman Place, Unit 5015, Storrs, CT, 06269 USA;3. Kansas Geological Survey, University of Kansas, 1930 Constant Ave., Lawrence, KS, 66047 USA;4. U.S. Geological Survey, Upper Midwest Water Science Center, 8505 Research Way, Middleton, WI, 53562 USA
Abstract:Glacial aquifers are an important source of groundwater in the United States and require accurate characterization to make informed management decisions. One parameter that is crucial for understanding the movement of groundwater is hydraulic conductivity, K. Nuclear magnetic resonance (NMR) logging measures the NMR response associated with the water in geological materials. By utilizing an external magnetic field to manipulate the nuclear spins associated with 1H, the time-varying decay of the nuclear magnetization is measured. This logging method could provide an effective way to estimate K at submeter vertical resolution, but the models that relate NMR measurements to K require calibration. At two field sites in a glacial aquifer in central Wisconsin, we collected a total of four NMR logs and obtained measurements of K in their immediate vicinity with a direct-push permeameter (DPP). Using a bootstrap algorithm to calibrate the Schlumberger-Doll Research (SDR) NMR-K model, we estimated K to within a factor of 5 of the DPP measurements. The lowest levels of accuracy occurred in the lower-K (K < 10−4 m/s) intervals. We also evaluated the applicability of prior SDR model calibrations. We found the NMR calibration parameters varied with K, suggesting the SDR model does not incorporate all the properties of the pore space that control K. Thus, the expected range of K in an aquifer may need to be considered during calibration of NMR-K models. This study is the first step toward establishing NMR logging as an effective method for estimating K in glacial aquifers.
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