1. Bootstrap Calibration and Uncertainty Estimation of Downhole NMR Hydraulic Conductivity Estimates in an Unconsolidated Aquifer
- Author
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Elliot Grunewald, James J. Butler, Dave Walsh, Andrew D. Parsekian, Rosemary Knight, and Katherine Dlubac
- Subjects
Geologic Sediments ,geography ,Magnetic Resonance Spectroscopy ,geography.geographical_feature_category ,Petroleum engineering ,Uncertainty ,Aquifer ,Soil science ,Kansas ,Hydraulic conductivity ,Calibration ,Hydrodynamics ,Range (statistics) ,Computers in Earth Sciences ,Porosity ,Groundwater ,Water content ,Geology ,Water Science and Technology - Abstract
Characterization of hydraulic conductivity (K) in aquifers is critical for evaluation, management, and remediation of groundwater resources. While estimates of K have been traditionally obtained using hydraulic tests over discrete intervals in wells, geophysical measurements are emerging as an alternative way to estimate this parameter. Nuclear magnetic resonance (NMR) logging, a technology once largely applied to characterization of deep consolidated rock petroleum reservoirs, is beginning to see use in near-surface unconsolidated aquifers. Using a well-known rock physics relationship-the Schlumberger Doll Research (SDR) equation--K and porosity can be estimated from NMR water content and relaxation time. Calibration of SDR parameters is necessary for this transformation because NMR relaxation properties are, in part, a function of magnetic mineralization and pore space geometry, which are locally variable quantities. Here, we present a statistically based method for calibrating SDR parameters that establishes a range for the estimated parameters and simultaneously estimates the uncertainty of the resulting K values. We used co-located logging NMR and direct K measurements in an unconsolidated fluvial aquifer in Lawrence, Kansas, USA to demonstrate that K can be estimated using logging NMR to a similar level of uncertainty as with traditional direct hydraulic measurements in unconsolidated sediments under field conditions. Results of this study provide a benchmark for future calibrations of NMR to obtain K in unconsolidated sediments and suggest a method for evaluating uncertainty in both K and SDR parameter values.
- Published
- 2014
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