NMR Logging to Estimate Hydraulic Conductivity in Unconsolidated Aquifers

Nuclear magnetic resonance (NMR) logging provides a new means of estimating the hydraulic conductivity (K) of unconsolidated aquifers. The estimation of K from the measured NMR parameters can be performed using the Schlumberger‐Doll Research (SDR) equation, which is based on the Kozeny–Carman equation and initially developed for obtaining permeability from NMR logging in petroleum reservoirs. The SDR equation includes empirically determined constants. Decades of research for petroleum applications have resulted in standard values for these constants that can provide accurate estimates of permeability in consolidated formations. The question we asked: Can standard values for the constants be defined for hydrogeologic applications that would yield accurate estimates of K in unconsolidated aquifers? Working at 10 locations at three field sites in Kansas and Washington, USA, we acquired NMR and K data using direct‐push methods over a 10‐ to 20‐m depth interval in the shallow subsurface. Analysis of pairs of NMR and K data revealed that we could dramatically improve K estimates by replacing the standard petroleum constants with new constants, optimal for estimating K in the unconsolidated materials at the field sites. Most significant was the finding that there was little change in the SDR constants between sites. This suggests that we can define a new set of constants that can be used to obtain high resolution, cost‐effective estimates of K from NMR logging in unconsolidated aquifers. This significant result has the potential to change dramatically the approach to determining K for hydrogeologic applications.     

Uniform and lateral preferential flows under flood irrigation at field scale

Flood irrigation is globally one of the most used irrigation methods. Typically, not all water that is applied during flood irrigation is consumed by plants or lost to evaporation. Return flow, the portion of applied water from flood irrigation that returns back to streams either via surface or subsurface flow, can constitute a large part of the water balance. Few studies have addressed the connection between vertical and lateral subsurface flows and its potential role in determining return flow pathways due to the difficulty in observing and quantifying these processes at plot or field scale. We employed a novel approach, combining induced polarization, time‐lapse electrical resistivity tomography, and time‐lapse borehole nuclear magnetic resonance, to identify flow paths and quantify changes in soil hydrological conditions under nonuniform application of flood irrigation water. We developed and tested a new method to track the wetting front in the subsurface using the full range of inverted resistivity values. Antecedent soil moisture conditions did not play an important role in preferential flow path activation. More importantly, boundaries between lithological zones in the soil profile were observed to control preferential flow pathways with subsurface run‐off occurring at these boundaries when saturation occurred. Using the new method to analyse time‐lapse resistivity measurements, we were able to track the wetting front and identify subsurface flow paths. Both uniform infiltration and preferential lateral flows were observed. Combining three geophysical methods, we documented the influence of lithology on subsurface flow processes. This study highlights the importance of characterizing the subsurface when the objective is to identify and quantify subsurface return flow pathways under flood irrigation.     

Geostatistical Rock Physics Inversion for Predicting the Spatial Distribution of Porosity and Saturation in the Critical Zone

Mathematical Geosciences - Understanding the subsurface structure and function in the near-surface groundwater system, including fluid flow, geomechanical, and weathering processes, requires...     

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.     

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.     

The effect of peat structure on the spatial distribution of biogenic gases within bogs

Northern peatlands are a large source of atmospheric methane (CH₄) and both a source and a sink of atmospheric carbon dioxide (CO₂). The rate and temporal variability in gas exchanges with peat soils is directly related to the spatial distribution of these free‐phase gases within the peat column. In this paper, we present results from surface and borehole ground‐penetrating radar surveys – constrained with direct soil and gas sampling – that compare the spatial distribution of gas accumulations in two raised bogs: one in Wales (UK), the other in Maine (USA). Although the two peatlands have similar average thickness, physical properties of the peat matrix differ, particularly in terms of peat type and degree of humification. We hypothesize that these variations in physical properties are responsible for the differences in gas distribution between the two peatlands characterized by (1) gas content up to 10.8% associated with woody peat and presence of wood layers in Caribou Bog (Maine) and (2) a more homogenous distribution with gas content up to 5.7% at the surface (i.e. <0.5 m deep) in Cors Fochno (Wales). Our results highlight the variability in biogenic gas accumulation and distribution across peatlands and suggest that the nature of the peat matrix has a key role in defining how biogenic gas accumulates within and is released to the atmosphere from peat soils. © 2015 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.     

Expansion rate and geometry of floating vegetation mats on the margins of thermokarst lakes,northern Seward Peninsula,Alaska, USA

Investigations on the northern Seward Peninsula in Alaska identified zones of recent (<50 years) permafrost collapse that led to the formation of floating vegetation mats along thermokarst lake margins. The occurrence of floating vegetation mat features indicates rapid degradation of near‐surface permafrost and lake expansion. This paper reports on the recent expansion of these collapse features and their geometry is determined using geophysical and remote sensing measurements. The vegetation mats were observed to have an average thickness of 0.57 m and petrophysical modeling indicated that gas content of 1.5–5% enabled floatation above the lake surface. Furthermore, geophysical investigation provides evidence that the mats form by thaw and subsidence of the underlying permafrost rather than terrestrialization. The temperature of the water below a vegetation mat was observed to remain above freezing late in the winter. Analysis of satellite and aerial imagery indicates that these features have expanded at maximum rates of 1–2 m yr^‐1 over a 56 year period. Including the spatial coverage of floating ‘thermokarst mats’ increases estimates of lake area by as much as 4% in some lakes. Copyright © 2011 John Wiley & Sons, Ltd.     

Geophysical and Hydrochemical Identification of Flow Paths with Implications for Water Quality at an ARR Site

Two key challenges regarding the design and operation of aquifer recharge and recovery (ARR) systems are evaluating aquifer heterogeneity and understanding hydrochemical interactions. Uncertainty in this respect can impact the volume of recoverable water and the improvement in water quality. The objective of this research is to leverage the advantages of geophysical measurements and hydrochemical sampling to reveal the properties of an ARR site to inform current ARR system operations and future design decisions. Electrical resistivity tomography was used to image the subsurface below two key infiltration/extraction areas of an ARR site in Colorado, USA. Hydrochemical measurements on transects intersecting the geophysical measurements resolved bulk parameters (i.e., total organic carbon, nitrate, and major cations and anions) and trace organic chemicals (e.g., pharmaceuticals, personal care products). Conservative tracers were also used to estimate degrees of mixing and water travel times and to better assess the performance of the ARR site regarding water quality changes and water recovery. The electrical resistivity measurements suggest that certain areas of the infiltration basins have hydraulic connections to the extraction wells through preferential flow paths, compared with other infiltration basins that are separated by fine‐grained materials from their respective extraction wells. The hydrochemical results indicate that consistent improvements in water quality can be achieved in these preferential flow paths within relatively short travel times (<5 d) at this ARR site.     

Characterizing Heterogeneity in Infiltration Rates During Managed Aquifer Recharge

Infiltration rate is the key parameter that describes how water moves from the surface into a groundwater aquifer during managed aquifer recharge (MAR). Characterization of infiltration rate heterogeneity in space and time is valuable information for MAR system operation. In this study, we utilized fiber optic distributed temperature sensing (FO‐DTS) observations and the phase shift of the diurnal temperature signal between two vertically co‐located fiber optic cables to characterize infiltration rate spatially and temporally in a MAR basin. The FO‐DTS measurements revealed spatial heterogeneity of infiltration rate: approximately 78% of the recharge water infiltrated through 50% of the pond bottom on average. We also introduced a metric for quantifying how the infiltration rate in a recharge pond changes over time, which enables FO‐DTS to be used as a method for monitoring MAR and informing maintenance decisions. By monitoring this metric, we found high‐spatial variability in how rapidly infiltration rate changed during the test period. We attributed this variability to biological pore clogging and found a relationship between high initial infiltration rate and the most rapid pore clogging. We found a strong relationship (R² = 0.8) between observed maximum infiltration rates and electrical resistivity measurements from electrical resistivity tomography data taken in the same basin when dry. This result shows that the combined acquisition of DTS and ERT data can improve the design and operation of a MAR pond significantly by providing the critical information needed about spatial variability in parameters controlling infiltration rates.     

Correction: Geostatistical Rock Physics Inversion for Predicting the Spatial Distribution of Porosity and Saturation in the Critical Zone

Mathematical Geosciences -