Internal magnetic field gradients in porous materials, if sufficiently large, can be a source of error in nuclear magnetic resonance (NMR) measurements of the transverse relaxation time [Formula: see text] and the diffusion coefficient [Formula: see text]. Given that these measurements can provide information about the pore fluid and the pore geometry, it is important to determine the magnitude of internal gradients and assess their potential impact. We estimated the effective internal gradients in aquifer sediment samples using three methods. We used a 2D NMR method to map the distribution of internal gradients versus [Formula: see text] and found gradients up to [Formula: see text] with peak gradient values in the range of [Formula: see text] for most of the samples. The average effective gradient values, calculated from the slope of the mean log relaxation rate versus the squared echo time, typically fell above the peak gradient values in the 2D distributions, with a range from 12 to 230 G/cm. The maximum effective gradients, calculated from the magnetic susceptibility of the samples, were found to be the upper bounds for most of the gradient distributions. The mean gradient was found to increase with increasing magnetic susceptibility of the sample; however, pore size was also found to impact gradient magnitudes. Given that the distribution of internal gradient magnitudes is determined by the properties of the sediment and by the magnitude of the background field, our results have implications for the acquisition of logging and surface NMR data. We expect the internal gradients in many aquifer sediments to impact NMR logging measurements; this should be considered when selecting logging parameters and interpreting NMR logging data. In contrast, we expect internal gradients to have a negligible impact on surface NMR measurements because of the much smaller magnitude of the background magnetic field.
Measurements of the nuclear magnetic resonance (NMR) signal’s behavior with time provide powerful noninvasive insight into the pore-scale environment. The time dependence of the NMR signal, which is a function of parameters called relaxation times, is intimately linked to the geometry of the pore space and has been used successfully to estimate pore size and permeability. The basis for the pore size and permeability estimates is that interactions occurring at the grain surface often function as the primary mechanism controlling the time dependence of the NMR signal. In this limit, called the fast diffusion limit, and when each pore can be considered to be isolated, the measured relaxation times are often interpreted as representative of pore sizes. In heterogeneous media, where the NMR signal is described by a distribution of relaxation times, the measured relaxation time distribution is often interpreted as representative of the underlying pore-size distribution. We have explored a scenario in which an additional relaxation mechanism, which arises due to magnetic field inhomogeneity across the pore space, violates the assumption that interactions occurring at the grain surface are the dominant relaxation mechanism. Using both synthetic and laboratory studies, we demonstrate that magnetic field inhomogeneity can lead to a complex relationship between the measured relaxation time distribution and the underlying pore-size distribution. Magnetic field inhomogeneity is observed to lead to a spatially heterogeneous magnetization density across the pore space requiring multiple eigenmodes to describe the evolution of the magnetization within a single pore during the NMR experiment. This results in a breakdown of the validity of the interpretation of the relaxation time distribution as representative of the underlying pore-size distribution for sediments with high magnetic susceptibility.
In a field study conducted in Pine Ridge, South Dakota, nuclear magnetic resonance (NMR) logging measurements were used to investigate an area of hydrocarbon contamination from leaking underground storage tanks. The NMR logging measurements are directly sensitive to hydrogen-bearing fluids in the sediments surrounding a well and can be used to estimate in situ fluid volumes. The relaxation time [Formula: see text] and diffusion coefficient [Formula: see text] of the fluids may be used to differentiate between signal from water and signal from contaminant, enabling the estimation of the hydrocarbon volume. In this study, NMR measurements were collected in two PVC-cased monitoring wells, with [Formula: see text] and [Formula: see text] measurements used together to detect a contaminant smear zone at both the wells. Although the contrast in [Formula: see text] between the fluids was found to be inadequate for fluid typing, the [Formula: see text] contrast between the contaminant and water in silt enabled the estimation of contaminant volumes. Using this technique, the vertical extent of the smear zone was found to be more than 3 m with up to 5 vol% contaminant in the sediments at one well and up to 9.5 vol% at the other well. Our work reveals that NMR logging can, under certain circumstances, be used to detect and quantify in situ contamination, but it also highlights the significant limitation that sediment and contaminant properties at many sites may result in insufficient contrast in [Formula: see text] and [Formula: see text].
We have conducted proton nuclear magnetic resonance (NMR) measurements of relaxation times [Formula: see text] and [Formula: see text] as well as the diffusion coefficient [Formula: see text] to detect and quantify gasoline, diesel, crude oil, and trichloroethylene (TCE) in sediment samples containing water. The sediment samples were coarse sand, fine sand, and a sand-clay mixture. We found that water, gasoline, diesel, and crude oil all exhibited similar signal amplitudes per unit volume, whereas TCE exhibited one-tenth the signal. The ability to use [Formula: see text] measurements to distinguish the contaminant signal from the water signal depended on the bulk-fluid properties as well as the sediment texture and grain size. In the [Formula: see text] distributions for samples containing equal volumes of contaminant and water, the contaminant signal could be resolved for crude oil in sand and for gasoline and TCE in the sand-clay mixture. Adding the diffusion measurement, using either pulsed or static gradients, made it possible to distinguish diesel and crude oil in all of the samples due to the large differences between the [Formula: see text] of the contaminants and water. From the diffusion measurements, we were able to accurately quantify diesel and crude oil volumes ranging from 1% to 17% of the total sample volume. These methods could be applied in the field using NMR logging tools to quantify and monitor subsurface contamination.
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