Hydraulic Conductivity from Nuclear Magnetic Resonance Logs in Sediments with Elevated Magnetic Susceptibilities |
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| Authors: | Heather Crow Daniel Paradis Elliot Grunewald Xiao Xia Liang Hazen AJ Russell |
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| Institution: | 1. Geological Survey of Canada, 601 Booth Street, Ottawa, Ontario, Canada, K1A 0E8;2. Geological Survey of Canada, Québec, Quebec, Canada;3. Vista Clara Inc., Mukilteo, Washington |
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| Abstract: | This study examined the application of slim-hole nuclear magnetic resonance (NMR) tools to estimate hydraulic conductivity (KNMR) in an unconsolidated aquifer that contains a range of grain sizes (silt to gravel) and high and variable magnetic susceptibilities (MS) (10−4 to 10−2 SI). A K calibration dataset was acquired at 1-m intervals in three fully screened wells, and compared to KNMR estimates using the Schlumberger-Doll research (SDR) equation with published empirical constants developed from previous studies in unconsolidated sediments. While KNMR using published constants was within an order of magnitude of K, the agreement, overprediction, or underprediction of KNMR varied with the MS distribution in each well. An examination of the effects of MS on NMR data and site-specific empirical constants indicated that the exponent on T2ML (n-value in the SDR equation, representing the diffusion regime) was found to have the greatest influence on KNMR estimation accuracy, while NMR porosity did not improve the prediction of K. KNMR was further improved by integrating an MS log into the NMR analyses. A first approach detrended T2ML for the effects of MS prior to calculating KNMR, and a second approach introduced an MS term into the SDR equation. Both were found to produce similar refinements of KNMR in intervals of elevated MS. This study found that low frequency NMR logging with short echo times shows promise for sites with moderate to elevated MS levels, and recommends a workflow that examines parameter relationships and integrates MS logs into the estimation of KNMR. |
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