Assessment of NMR Logging for Estimating Hydraulic Conductivity in Glacial Aquifers

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.

Evaluation of Models for Estimating Hydraulic Conductivity in Glacial Aquifers with NMR Logging

“…Other studies have used coupled NMR and hydraulic measurements to determine the optimal empirically calibrated parameters so as to obtain accurate estimates of K . These studies have acquired NMR and hydraulic data in glacio‐fluvial and lacustrine deposits in Wisconsin (Kendrick et al 2021), fluvial sediments in Kansas and Washington (Walsh et al 2013; Knight et al 2016; Maurer and Knight 2016), and in the un/semi‐consolidated sediments of the High Plains aquifer in Nebraska (Dlubac et al 2013). The important findings from these studies include: (1) when the NMR‐ K models are calibrated at a site to an independent measurement of K , K can typically be predicted from the NMR data to within an order of magnitude; (2) values of the empirically calibrated parameters determined for unconsolidated sediments differ substantially from the standard values used in the petroleum industry for sedimentary rocks; and (3) values of the empirically calibrated parameters were consistent for some sites, but varied between others.…”

“…Given the importance of this aquifer system as a source of groundwater and its vulnerability (Warner and Arnold 2005), there is tremendous interest in finding efficient ways of accurately estimating K so as to inform sustainable groundwater management and protection. In the summer of 2018, NMR data were acquired at two field sites in Wisconsin glacial aquifers (Kendrick et al 2021): the Adams County site in the Central Wisconsin sand and gravel aquifer (CWSGA) located on a former lake bed (Hart et al 2014), and the Plainfield Lake site, 40 km away, located on the Hancock terminal moraine in a tunnel channel (Clayton et al 1999). From two locations about 17 m apart at the Adams County site and two locations about 9 m apart at the Plainfield Lake site, NMR logging measurements were made every 3 min per 0.25‐m intervals in ∼20 m deep Geoprobe‐installed wells using the Dart NMR logging tool manufactured by Vista Clara Inc. (Walsh et al 2013).…”

“…The sets of measurements at the two sites yielded many NMR‐DPP data pairs, constructed by pairing each NMR measurement with the closest DPP measurement of K . NMR and DPP measurements are described in detail in Kendrick et al (2021).…”

“…In the initial analysis of Kendrick et al (2021), the widely adopted Schlumberger‐Doll Research (SDR) model was used to estimate K . This model yielded NMR estimates of K that were within a factor of 2 of the DPP K measurements for most of the NMR‐DPP data pairs.…”

Simple Fully Automatic Testing Method of Seepage Indices for Low-Permeability Materials

“…Monitoring analysis methods can obtain the seepage indices of materials as a function of the relevant parameters of permeability of the soil and rock bodies tested using sensors [11,16]. Indirect testing methods reflect the permeability of rock and soil to indirectly measure the seepage indices; these include the acoustic emission method [17], nuclear magnetic resonance method [18,19], and near-infrared method [20]. For field tests, the overwhelming influencing factors make it difficult to accurately evaluate and determine the results, in addition to generating a heavy test workload.…”