Kristina Keating

A laboratory study to determine the effect of iron oxides on proton NMR measurements

Using laboratory methods, we investigate the effect of the presence and mineralogic form of iron on measured proton nuclear magnetic resonance (NMR) relaxation rates. Five samples of quartz sand were coated with ferrihydrite, goethite, hematite, lepidocrocite, and magnetite. The relaxation rates for these iron-oxide-coated sands saturated with water were measured and compared to the relaxation rate of quartz sand saturated with water. We found that the presence of the iron oxides led to increases in the relaxation rates by increasing the surface relaxation rate. The magnitude of the surface relaxation rate was different for the various iron-oxide minerals because of changes in both the surface-area-to-volume ratio of the pore space, and the surface relaxivity. The relaxation rate of the magnetite-coated sand was further increased because of internal magnetic field gradients caused by the presence of magnetite. We conclude that both the concentration and mineralogical form of iron can have a significant impact on NMR relaxation behavior.

A Review of the Principles and Applications of the NMR Technique for Near-Surface Characterization

Abstract This paper presents a comprehensive review of the recent advances in nuclear magnetic resonance (NMR) measurements for near-surface characterization using laboratory, borehole, and field technologies. During the last decade, NMR has become increasingly popular in near-surface geophysics due to substantial improvements in instrumentation, data processing, forward modeling, inversion, and measurement techniques. This paper starts with a description of the principal theory and applications of NMR. It presents a basic overview of near-surface NMR theory in terms of its physical background and discusses how NMR relaxation times are related to different relaxation processes occurring in porous media. As a next step, the recent and seminal near-surface NMR developments at each scale are discussed, and the limitations and challenges of the measurement are examined. To represent the growth of applications of near-surface NMR, case studies in a variety of different near-surface environments are reviewed and, as examples, two recent case studies are discussed in detail. Finally, this review demonstrates that there is a need for continued research in near-surface NMR and highlights necessary directions for future research. These recommendations include improving the signal-to-noise ratio, reducing the effective measurement dead time, and improving production rate of surface NMR (SNMR), reducing the minimum echo time of borehole NMR (BNMR) measurements, improving petrophysical NMR models of hydraulic conductivity and vadose zone parameters, and understanding the scale dependency of NMR properties.

A laboratory study of the effect of Fe(II)-bearing minerals on nuclear magnetic resonance (NMR) relaxation measurements

A laboratory study was conducted to measure the effect of the mineralogic form and concentration of iron(II) [Fe(II)] minerals on nuclear magnetic resonance (NMR) relaxation rates of water-saturated sand mixtures. We measured mixtures of quartz sand and three common Fe(II)-bearing minerals in granular form: siderite (FeC O3 ) , pyrite (Fe S2 ) , and pyrrhotite ( Fe1−x S ; 0<x<0.2 ) at two concentrations of iron by weight. The NMR response of these samples was used to calculate four transverse relaxation rates for each Fe(II) mineral mixture: total mean log, bulk fluid, diffusion, and surface relaxation rates. The surface area of the samples was used to calculate the surface relaxivity of the sample and the magnetically active surface. For each iron mineral, the mean log and surface relaxation rates were greater for samples with higher Fe(II) concentration. For the siderite,pyrrhotite, and high-concentration pyrite mixtures, surface relaxation was the dominant relaxation mechanism. Bulk fluid relaxation co...

Direct geoelectrical evidence of mass transfer at the laboratory scale

[1] Previous field-scale experimental data and numerical modeling suggest that the dual-domain mass transfer (DDMT) of electrolytic tracers has an observable geoelectrical signature. Here we present controlled laboratory experiments confirming the electrical signature of DDMT and demonstrate the use of time-lapse electrical measurements in conjunction with concentration measurements to estimate the parameters controlling DDMT, i.e., the mobile and immobile porosity and rate at which solute exchanges between mobile and immobile domains. We conducted column tracer tests on unconsolidated quartz sand and a material with a high secondary porosity: the zeolite clinoptilolite. During NaCl tracer tests we collected nearly colocated bulk direct-current electrical conductivity (� b) and fluid conductivity (� f) measurements. Our results for the

Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties

The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.

Nuclear magnetic resonance relaxation measurements as a means of monitoring iron mineralization processes

[1] In this laboratory study, we assessed the measurement of nuclear magnetic resonance (NMR) relaxation times as a means of monitoring iron mineralization processes. We conducted experiments in which columns containing ferrihydrite-coated quartz sand reacted with aqueous Fe(II) solutions to form goethite, lepidocrocite and magnetite. An observed increase in the volume of water relaxing with long relaxation times in the NMR relaxation time distribution corresponds to the formation of goethite and lepidocrocite; a decrease in the average (mean log) relaxation time, and a broadening of the relaxation time distribution, corresponds to the formation of magnetite. These results indicate that NMR relaxation times are sensitive to changes in iron mineralogy and illustrate the potential use of NMR for monitoring iron mineralization processes. Citation: Keating, K., R. Knight, and K. J. Tufano (2008), Nuclear magnetic resonance relaxation measurements as a means of monitoring iron mineralization processes, Geophys. Res. Lett., 35, L19405,

A numerical study of the relationship between NMR relaxation and permeability in sands and gravels

The accuracy of NMR-derived permeability estimates in sands and gravels are examined through simulations on numerical grain packs composed of uniform spherical grains. The packs consisted of randomly packed grains, with grain sizes set to represent a range corresponding to sands and gravels. The material properties for each pack were quantified through numerical analysis and the NMR response was simulated for a range of surface relaxivity values. The agreement between the numerically-derived permeability estimates and the permeability estimates derived using the Schlumberger-Doll Research (SDR) and Seevers equations was evaluated. Use of the SDR equation assumes that the relaxation of the bulk pore fluid can be neglected. The NMR-derived permeability estimates were calculated using each equation for the cases where relaxation was assumed to occur in one of the two major diffusion regimes. We found that permeability is most accurately estimated in all packs through use of the Seevers equation with the empirical constant n set equal to 1. We showed that the contribution of bulk fluid relaxation should be accounted for in materials with grain radii greater than 1.2e-4m (fine sand) and surface relaxivity values less than 1.0e-3 m s-1. In practice, this range of surface relaxivity values and grain sizes corresponds to situations where the measured relaxation time T2 is greater than approximately one-third the value of the bulk fluid relaxation time T2B.

A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

We estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multi-salinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty-five sandstone cores collected from fifteen different formations, we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time (R2 of 0.69 and 0.39 and normalized root mean square errors (NRMSE) of 0.16 and 0.20, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE=0.23). We demonstrate that that permeability estimates from the joint-NMR-CC model (NRMSE=0.13) compare favorably to estimates from the Katz and Thompson model (NRMSE=0.074). This model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.

A laboratory study to determine the effect of surface area and bead diameter on NMR relaxation rates of glass bead packs

A laboratory study was conducted to explore the relationship between pore size, pore surface-areato-volume ratio and NMR relaxation rates and to determine which geometric parameter best predicts the average NMR relaxation rate. NMR relaxation measurements were collected on watersaturated glass beads with controlled sets of bead diameters and surface areas. Four sets of beads were used with average diameters ranging from 55–1125 μm. The surface areas of the glass beads were altered by chemically treating the beads with a weak acid, a strong base and a cream commonly used to etch glass surfaces. Following the chemical treatments, the surface areas of the beads were quantified with krypton BET gas adsorption measurements. It was found that, for the range of bead diameters used in this study, relaxation did not strictly occur in the fast diffusion regime and, as such, the relaxation time associated with the peak of the largest mode in the distribution was found to more accurately represent the pore-scale geometry than the mean log relaxation time. Using the relaxation time associated with this peak, the results from this study show that the pore surface-area-to-volume ratio is a significantly better predictor of the surface relaxation rate than the mean grain radius (p = 0.014).

On Permeability Prediction From Complex Conductivity Measurements Using Polarization Magnitude and Relaxation Time

Geophysical length scales determined from complex conductivity (CC) measurements can be used to estimate permeability k when the electrical formation factor F is known. Two geophysical length scales have been proposed: (1) the specific polarizability cp normalized by the imaginary conductivity r00 and (2) the time constant s multiplied by a diffusion coefficient D1. The parameters cp and D1 account for the control of fluid chemistry and/or varying minerology on the geophysical length scale. We evaluated the predictive capability of two CC permeability models: (1) an empirical formulation based on r00 or normalized chargeability mn and (2) a mechanistic formulation based on s. The performance of the CC models was evaluated against measured k; and further compared against that of well-established k estimation equations that use geometric length scales. Both CC models predict permeability within one order of magnitude for a database of 58 sandstone samples, with the exception of samples characterized by high pore volume normalized surface area Spor . Variations in cp and D1 likely contribute to the poor model performance for the high Spor samples, which contain significant dolomite. Two observations favor the implementation of the r00-based model over the s-based model for field-scale k estimation: (1) a limited range of variation in cp relative to D1 and (2) r00 field measurements are less time consuming to acquire relative to s. The need for a reliable field-estimate of F limits application of either model, in particular the r00 model due to a high power law exponent associated with F.