North-Central Section - 54th Annual Meeting - 2020

Paper No. 18-3
Presentation Time: 2:10 PM

ASSESSMENT OF NMR LOGGING FOR ESTIMATING HYDRAULIC CONDUCTIVITY IN GLACIAL AQUIFERS


KENDRICK, Alex1, KNIGHT, Rosemary1, JOHNSON, Carole D.2, LIU, Gaisheng3, HUNT, Randall J.4 and BUTLER Jr., James J.3, (1)Geophysics, Stanford Univ, Mitchell Building, Room 360, Stanford, CA 94305, (2)Hydrogeophysics Branch, U.S. Geological Survey, Storrs, CT 06269, (3)Kansas Geological Survey, University of Kansas, 1930 Constant Avenue, Lawrence, KS 66047, (4)Upper Midwest Water Science Center, U. S. Geological Survey, 8505 Research Way, Middleton, WI 53562

Glacial aquifers are an important source of groundwater in the United States and require accurate characterization of aquifer properties to make informed management decisions. One parameter that is crucial for understanding the movement of water within an aquifer is hydraulic conductivity, K. Nuclear magnetic resonance (NMR) logging could provide an effective way to estimate K at submeter resolution, but the models that relate NMR measurements to K require calibration. At each site, we collected two NMR logs, and obtained independent measurements of K in their immediate vicinity using a direct-push permeameter. After using a bootstrap algorithm to calibrate four different NMR-K models, we were able to estimate K to within an order of magnitude of the DPP measurements. After analyzing the NMR data from this study in Wisconsin, as well as from previous studies in Kansas, Washington and Nebraska, we found the NMR calibration parameters for estimating K varied with K. This observed variation suggests NMR measurements or existing NMR-K models are unable to fully quantify properties of the pore space that vary with K. When calibrating NMR-K models, the range of K measured in an aquifer may need to be considered during calibration. This study establishes NMR logging as an effective and potentially transferable tool for estimating K in glacial aquifers.