Hydraulic Conductivity Calibration of Logging NMR in a Granite Aquifer,Laramie Range,Wyoming

In granite aquifers, fractures can provide both storage volume and conduits for groundwater. Characterization of fracture hydraulic conductivity (K) in such aquifers is important for predicting flow rate and calibrating models. Nuclear magnetic resonance (NMR) well logging is a method to quickly obtain near-borehole hydraulic conductivity (i.e., K_NMR) at high-vertical resolution. On the other hand, FLUTe flexible liner technology can produce a K profile at comparable resolution but requires a fluid driving force between borehole and formation. For three boreholes completed in a fractured granite, we jointly interpreted logging NMR data and FLUTe K estimates to calibrate an empirical equation for translating borehole NMR data to K estimates. For over 90% of the depth intervals investigated from these boreholes, the estimated K_NMR are within one order of magnitude of K_FLUTe. The empirical parameters obtained from calibrating the NMR data suggest that “intermediate diffusion” and/or “slow diffusion” during the NMR relaxation time may occur in the flowing fractures when hydraulic aperture are sufficiently large. For each borehole, “intermediate diffusion” dominates the relaxation time, therefore assuming “fast diffusion” in the interpretation of NMR data from fractured rock may lead to inaccurate K_NMR estimates. We also compare calibrations using inexpensive slug tests that suggest reliable K_NMR estimates for fractured rock may be achieved using limited calibration against borehole hydraulic measurements.     

Effects of Improper Characterization of Aquifer Thickness on Estimates of Hydraulic Conductivity from Pumping Tests

Pumping test data for surficial aquifers are commonly analyzed under the assumption that the base of the aquifer corresponds to the bottom of the test wells (i.e., the aquifer is truncated). This practice can lead to inaccurate hydraulic conductivity estimates, resulting from the use of low saturated thickness values with transmissivity estimates, and not accounting for the effects of partially penetrating wells. Theoretical time-drawdown data were generated at an observation well in a hypothetical unconfined aquifer for various values of saturated thickness and were analyzed by standard curve-matching techniques. The base of the aquifer was assumed to be the bottom of the pumping and observation wells. The overestimation of horizontal hydraulic conductivity was found to be directly proportional to the error in assumed saturated thickness, and to the (actual) ratio of vertical to horizontal hydraulic conductivity (K_v/K_h). Inaccurately high estimates of hydraulic conductivity obtained by aquifer truncation can lead to overestimates of ground water velocity and contaminant plume spreading, narrow capture zone configuration estimates, and overestimates of available ground water resources.     

Bootstrap Calibration and Uncertainty Estimation of Downhole NMR Hydraulic Conductivity Estimates in an Unconsolidated Aquifer

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.     

Comparison of Hydraulic Conductivity Values Obtained from Aquifer Pumping Tests and Conservative Tracer Tests

Afield site was established in an area of glacial outwash near Des Moines, Iowa. Hydraulic conductivity (K) of the outwash was measured in various ways including six pumping tests and two natural-gradient Cl^- tracer tests. The velocity of the conservative tracer was converted to K using measured gradients and effective porosity determined from two radial-convergent Cl^- tracer tests.
K values measured from the conservative tracer tests are approximately one-tenth to one-twentieth the average pumping-test value. Thus the K relevant to solute transport does not reflect the K measured by pumping tests. This discrepancy may be caused by the different scale and dimensionality of the two test types. Dispersion may prevent solutes from flowing exclusively within smaller high-conductivity paths which strongly affect the K measured by pumping tests.     

Near Surface Electrical Characterization of Hydraulic Conductivity: From Petrophysical Properties to Aquifer Geometries—A Review

This paper reviews the recent geophysical literature addressing the estimation of saturated hydraulic conductivity (K) from static low frequency electrical measurements (electrical resistivity, induced polarization (IP) and spectral induced polarization (SIP)). In the first part of this paper, research describing how petrophysical relations between electrical properties and effective (i.e. controlling fluid transport) properties of (a) the interconnected pore volumes and interconnected pore surfaces, have been exploited to estimate K at both the core and field scale is reviewed. We start with electrical resistivity measurements, which are shown to be inherently limited in K estimation as, although resistivity is sensitive to both pore volume and pore surface area properties, the two contributions cannot be separated. Efforts to utilize the unique sensitivity of IP and SIP measurements to physical parameters that describe the interconnected pore surface area are subsequently introduced and the incorporation of such data into electrical based Kozeny–Carman type models of K estimation is reviewed. In the second part of this review, efforts to invert geophysical datasets for spatial patterns of K variability (e.g. aquifer geometries) at the field-scale are considered. Inversions, based on the conversion of an image of a geophysical property to a hydrological property assuming a valid petrophysical relationship, as well as joint/constrained inversion methods, whereby multiple geophysical and hydrological data are inverted simultaneously, are briefly covered. This review demonstrates that there currently exists an opportunity to link, (1) the petrophysics relating low frequency electrical measurements to effective hydraulic properties, with (2) the joint inversion strategies developed in recent years, in order to obtain more meaningful estimates of spatial patterns of K variability than previously reported.     

Measuring a Low Horizontal Hydraulic Gradient in a High Transmissivity Aquifer

High transmissivity aquifers typically have low hydraulic gradients (i.e., a flat water table). Measuring low gradients using water levels can be problematic because measurement error may be greater than the true difference in water levels (i.e., a low signal-to-noise ratio). In this study, the feasibility of measuring a hydraulic gradient in the range of 10⁻⁶ to 10⁻⁵ m/m was demonstrated. The study was performed at a site where the depth to water from land surface ranged from 40.1 to 94.2 m and the aquifer transmissivity was estimated at 41,300 m²/d (hydraulic conductivity of 18,800 m/d). The goals of the study were to reduce measurement error as much as practicable and assess the importance of factors affecting water level measurement accuracy. Well verticality was the largest source of error (0.000 to 0.168 m; median of 0.014 m), and geodetic survey of casing elevations was the next most important source of error (0.002 to 0.013 m; median of 0.005 m). Variability due to barometric pressure fluctuations was not an important factor at the site. Hydraulic heads were measured to an accuracy of ±0.0065 m, and the average hydraulic gradient was estimated to be 8.0 × 10⁻⁶ (±0.9 × 10⁻⁶) m/m. The improvement in accuracy allowed for two reversals in the groundwater flow direction to be identified, after which the gradient averaged 2.5 × 10⁻⁵ (±0.4 × 10⁻⁵) m/m. This study showed it is possible to sufficiently control sources of error to measure hydraulic gradients in the 10⁻⁶ to 10⁻⁵ m/m range.     

Surfactant-Induced Reductions in Soil Hydraulic Conductivity

Surfactant solutions are being proposed for in situ flushing of organic contaminants from soils and aquifers. The feasibility of surfactant additives in remediation may depend in large part on how these chemicals affect the hydraulic conductivity of the porous media. While there is evidence in the literature of conductivity loss during surfactant flushing (Miller et al. 1975; Nash et al. 1987), there has been little research on quantifying the process for unconsolidated sediments. Surfactant-affected hydraulic conductivity reductions were measured in two soils (Teller loam and Daugherty sand). Testing was done with eight surfactants at a variety of concentrations (10^-5 to 10^-l mole/kg), surfactant mixtures, and added solution electrolytes. The Teller was also tested with its organic matter removed. Maximum hydraulic conductivity decreases were 47 percent for the sand and more than two orders of magnitude for the loam. Surfactant concentrations, surfactant mixtures, soil organic content, and added solution electrolytes all affected the degree of conductivity reduction. Results indicate that surfactant-affected hydraulic conductivity losses should be considered prior to in situ remediation and may preclude surfactant use in some fine grain soils.     

Estimating Tortuosity Coefficients Based on Hydraulic Conductivity

While the tortuosity coefficient is commonly estimated using an expression based on total porosity, this relationship is demonstrated to not be applicable (and thus is often misapplied) over a broad range of soil textures. The fundamental basis for a correlation between the apparent diffusion tortuosity coefficient and hydraulic conductivity is demonstrated, although such a relationship is not typically considered. An empirical regression for estimating the tortuosity coefficient based on hydraulic conductivity for saturated, unconsolidated soil is derived based on results from 14 previously reported diffusion experiments performed with a broad range of soil textures. Analyses of these experimental results confirm that total porosity is a poor predictor for the tortuosity coefficient over a large range of soil textures. The apparent diffusion tortuosity coefficient is more reliably estimated based on hydraulic conductivity.