Surface NMR Data Research Articles

An Efficient Algorithm to Retrieve Multiple Fundamental Frequencies of Harmonic Interference in Surface-NMR Measurements

Summary The successful recovery of hydrogeophysical parameters through surface-NMR measurements depends on the quality of the signal, which can be significantly degraded by harmonics from multiple noise sources with different fundamental frequencies in urban areas. Accurate estimation of the fundamental frequencies of harmonics is the main step in harmonic noise cancellation-based methods. The existing 1D and 2D model-based approaches involve a computationally expensive process that sets limits for processing of large surface-NMR data sets. In addition, the classical Nyman, Gaiser, and Saucier estimation (NGSE) algorithm, despite its fast implementation, may not accurately recover harmonic components when there is no prior knowledge of the expected value of the frequency offset between the true fundamental frequencies and their nominal values. This lack of knowledge can make it difficult to accurately estimate the maximum number of harmonics and, consequently, result in an incorrect recovery of the fundamental frequency. To surmount these limitations, we propose an enhanced version of the NGSE approach based on an efficient maximum number of harmonics search approach to process surface-NMR signals corrupted by powerline harmonics with both single and multiple frequency content. We verify the efficiency of our algorithm on a synthetic dataset embedded in simulated powerline harmonic signals, and real electromagnetic noise recordings, as well as a real surface-NMR data set. Our numerical experiments confirm that the proposed algorithm can retrieve the multiple fundamental frequencies simultaneously with a significant speedup ranging from 4 to 87 times, depending on whether the signal has single, dual, or triple frequency content, in the overall computation time compared to the model-based methods.

Observation of spikelets in steady-state surface nuclear magnetic resonance data

Spikelets in nuclear magnetic resonance (NMR) data occur at predictable frequencies dependent on the repetition time of the excitation sequence. Although spikelets are well documented in other NMR fields, we report their presence in steady-state surface NMR data for the first time. These observations are accompanied by analytical developments to understand and predict their behavior, which follow directly from existing steady-state surface NMR modeling. We show that spikelets represent copies of the surface NMR signal occurring at multiple locations in the frequency domain, including locations that are distinct from the Larmor frequency. These features are shown to be detectable without requiring additional effort in the field and are shown to be readily processed and modeled with only minor modifications to the processing and modeling workflows. Finally, field spikelet data are also inverted to demonstrate that these data can be fit using subsurface models consistent with a reference surface NMR inversion.

Non-remote reference noise cancellation - using reference data in the presence of surface-NMR signals

Surface-NMR measurements commonly suffer from low signal-to-noise ratios. In recent years, with the introduction of multi-channel surface-NMR instruments, the technique of remote-reference noise cancellation (RNC) was developed and significantly improved the applicability of surface-NMR. The current formulation of RNC requires a reference loop to be placed a remote distance from the transmitter loop such that no NMR signal is recorded. Reference loops placed at non-remote distances have been envisaged to provide both improved noise cancellation performance and field efficiency; however, the concept has not been previously applied because the theoretical framework was missing. In this paper, the theoretical framework is presented. It is demonstrated that reference loops placed at non-remote distances provide superior noise cancellation performance. Considerations for placing the reference loop relative to the transmitter loop are provided, and the theoretical framework is evaluated based on a semi-synthetic example using real field noise and synthetic surface-NMR data.

Inverting surface NMR free induction decay data in a voltage-time data space

Envelope detection is an integral step of the surface NMR data processing workflow. A promising approach to produce high signal-to-noise ratio envelopes involves a scheme referred to as spectral analysis (SA) envelope detection – a scheme based upon a series of discrete Fourier transforms for sliding windows of observed NMR data. This method has the advantage that it naturally handles the narrow-band character of the NMR signal without corrupting the early portion of the time-series – both of which are challenges confronting traditional surface NMR processing schemes. However, SA estimated envelopes are weighted by the NMR relaxation time during processing and the envelopes have units of volt-seconds, whereas the unit of the data space employed by traditional surface NMR forward models is volts. To better integrate the SA envelope detection scheme within the surface NMR workflow, we propose to modify the surface NMR forward model such that it predicts data directly in the voltage-time data space. Synthetic and field data inversions, as well as a parameter resolution study, are presented to demonstrate advantages of pairing the SA envelope detection scheme with a forward model that works in the voltage-time data space. The method is shown to improve parameter resolution and does not require significant modifications to existing surface NMR inversion platforms.

3D block QT inversion of surface nuclear magnetic resonance data

Surface nuclear magnetic resonance (surface NMR) has up to now rarely been applied to 3D subsurface modeling. Inversion approaches currently in use are smooth inversion techniques that are not useful for identifying sharp geologic boundaries. Although they are already computationally expensive, the resulting models are restricted to imaging the subsurface water content distribution and do not deliver relaxation times [Formula: see text] based on the QT inversion scheme established elsewhere. We have developed a method of 3D block QT inversion that uses horizontal smoothness constraints to resolve sharp boundaries in the vertical direction and the distributions of the water content and relaxation time [Formula: see text]. We have improved the computational efficiency, i.e., the ability to perform the inversion using a common desktop computer, by gating the surface NMR data, reducing the model space to monoexponential decays within the subsurface bodies, and inverting based on blocklike structures instead of smooth distributions. We have developed a synthetic study to assess the effectiveness of our block QT inversion technique in imaging 3D water content distributions, and we compared the results with those of a smooth inversion. Furthermore, we evaluated results from a field survey conducted on the frozen surface of an artificial lake. We found that our block QT inversion approach provides results that are superior to those of smooth inversion and consistent with the available construction plan of the lake. We expect that 3D block QT inversion will be a useful approach also in other geologic settings, such as buried valleys, because it overcomes the current limitations of applying 3D surface NMR inversion.

Model-based subtraction of spikes from surface nuclear magnetic resonance data

Surface nuclear magnetic resonance (surface NMR) has progressed significantly in recent years due to advances in instrumentation. In particular, the introduction of multichannel surface NMR instruments has been effective in improving the signal-to-noise ratio. The current methodology for noise reduction with multichannel instruments is, however, inadequate in complex noise environments, and there is a need for improved signal processing. We have evaluated a study of impulsive noise (spikes) in surface NMR data acquired with a Numis Poly instrument. We have determined how the spectral content can be used to classify spikes as originating from electric fences or sferics. Measurements of spikes from two electric fences were evaluated. The spikes were highly deterministic and can be modeled as impulsive excitations of the band-pass filter in the surface NMR receiver system. We investigated the feasibility of a model-based approach for subtraction of electric fence spikes. Model-based subtraction was shown to be possible, but it is limited by accidental fitting of the NMR signal in its current embodiment. We evaluated an example of a surface NMR data set in which subtraction of powerline harmonic noise and electric fence spike noise removed all coherence in the multichannel data, and the consequences for further noise reduction using multichannel methods were developed.

Processing of surface-nuclear magnetic resonance data from sites with high noise levels

The applicability of surface nuclear magnetic resonance (NMR) in investigations of groundwater is often limited by high noise levels in many areas of interest. We have evaluated measurements from a high-noise-level area in Ristrup, Denmark, recorded with a Numis Poly instrument. Standard multichannel filtering techniques for noise reduction are inadequate for several data sets acquired in this area, and surface-NMR signals cannot be resolved from the acquired data. Based on a careful assessment of the frequency content of the data, we have determined how a model-based noise reduction approach can be generalized and used to subtract two harmonic noise components from the data. Reliable surface-NMR data can be extracted from the noise-reduced data. Moreover, we have determined the impact of the proposed processing approaches on our inversion results, and we have also developed an example in which the proposed methodology allowed us to reveal and avoid an otherwise overlooked contamination of the reference coil signals with a surface-NMR signal. No borehole data were available for the investigated sites, and the validity of the noise reduction approach was instead verified using a synthetic five-layer model embedded in noise-only records from Ristrup. Our results have determined that a careful processing of the recorded data made it possible to extract surface-NMR data in more places of interest.

Integration of surface and logging NMR data to map hydraulic conductivity

Geophysical NMR measurements yield direct detection of groundwater and provide sensitivity to hydraulic conductivity (K) via the measured NMR water content and relaxation times. The aim of this work is to map hydraulic conductivity over wide areas by leveraging complementary aspects of surface and logging NMR measurements. Surface NMR measurements have the advantage of being non-invasive and can image the basic NMR response of the subsurface over wide areas. NMR logging measurements, on the other hand, provide data at higher resolution and detail, but can only be acquired at sparse locations where boreholes are available. In practice, deriving robust estimates of K from either of these measurements is improved using site-specific calibration and comparison with hydrogeologic K measurements. We have developed a framework for calibrating and integrating these measurements, and this framework has been tested at three field sites in the United States. The framework can be divided into three components: (1) establishing the relationship between the logging NMR measurement and hydrogeologic measured K; (2) establishing the relationship between the logging NMR and surface NMR measurement; and (3) relating the surface NMR measurement to K and extending surface acquisition over a wide area. The data include an extensive collection of slug-tests, NMR logs, and surface NMR measurements, supplemented further by (DP) technologies, including a pressure/flow sensor DP-K tool and novel DP-NMR tool. Our results demonstrate the viability of this approach as well as the need for appropriate site- or region-specific calibration. Specifically, the relationship between the NMR logging measurement and surface NMR measurement can vary significantly in the presence of magnetic geology. We have also established that the method of well installation and logging can influence the estimated relationship between the NMR log and K measurement.

Surface NMR instrumentation and methods for detecting and characterizing water in the vadose zone

ABSTRACTA commercially available surface NMR instrument was modified to address the challenges of using earth’s field surface NMR to detect and characterize water in the unsaturated (or vadose) zone. The modified instrument incorporates faster switching electronics to achieve an instrument dead time of 2.8 ms, and higher output power electronics to enable a maximum coil voltage of 8000 volts and coil current of 800 amps. The instrument was used to collect and interpret surface NMR data at several active vadose zone investigation sites in the western US. A 6‐week surface NMR experiment was conducted at a managed aquifer storage and recovery facility in Arizona, to explore the measurement capabilities and limitations of the instrument, during a managed infiltration event. The resulting time lapse surface NMR data were used to map zones of held water prior to the flood event, image the influx of water through the top 15 metres of the subsurface during and after the event, quantify the spatial and temporal distribution of infiltrating water throughout the event, and characterize the distribution of water in different relative pore sizes throughout the event. Data obtained at pseudo‐static vadose zone investigation sites indicate that the surface NMR instrument can detect and image some forms of water held in unconsolidated vadose zone formations, at depths up to 30 metres. Complementary NMR logging data indicate that the surface NMR instrument does not detect all of the water held in these pseudo‐static formations, but that the non‐invasive surface NMR data may yield valuable information nonetheless.

The inversion of surface-NMR T1 data for improved aquifer characterization

A crucial component in sustainable freshwater management is the reliable and cost-effective characterization of groundwater aquifers. A technique that allows noninvasive characterization of shallow ([Formula: see text]) aquifers is surface nuclear magnetic resonance (surface NMR). The measured parameter longitudinal relaxation time [Formula: see text] provides a link to pore-scale properties and can be used to estimate the hydraulic conductivity of the sampled region. The recent development of an optimized acquisition scheme, phase-cycled pseudosaturation recovery (pcPSR), has significantly advanced our ability to acquire surface-NMR [Formula: see text] data. Building on these findings, we developed an inversion scheme that can reconstruct the depth-distribution of [Formula: see text] from pcPSR data. To stabilize the inversion, we took a staggered approach: We first determined the distribution of water content and effective transverse relaxation time [Formula: see text], and then we resolved the [Formula: see text] structure. We tested the capability of the inversion in a synthetic study using models containing an unconfined and confined aquifer under conditions of low and high levels of ambient electromagnetic noise. The results allowed us to optimize the design of pcPSR experiments, finding that acquiring pcPSR data at three interpulse delay times is the best choice when acquiring surface-NMR data in an area with no prior information. We have verified our inversion approach in a field study in Nebraska, USA, where we had access to borehole lithologic information and logging-NMR [Formula: see text] measurements. Although the structural details ([Formula: see text]) detected in logging NMR were not resolved in surface NMR — highlighting the general resolution limitation of surface NMR — the two methods consistently revealed a zone of elevated [Formula: see text] corresponding to a sand and gravel unit, overlying a zone of lower [Formula: see text] corresponding to a sand/sandstone unit. Our developed inversion scheme is an important step toward the reliable interpretation of surface-NMR [Formula: see text] data for aquifer characterization.

On the sensitivity of surface NMR in the presence of electrical conductivity anomalies

The surface-NMR tomography technique is based on the principles of electromagnetic induction and proton spin dynamics. Electromagnetic fields emitted by large surface current-driven loops are employed to locate and quantify groundwater reservoirs. The oscillating magnetic fields interact with proton spins of water molecules in the electrically conductive subsurface. To study the influence of changing subsurface electrical properties on the nuclear spin response, we consider the spin magnetization as a virtual magnetic dipole receiver. The numerical solutions for the electric and magnetic fields of the transmitter and the virtual receiver in 3-D heterogeneous ground are based on the finite-element method. We explicitly compute the frequency-domain electromagnetic sensitivities for separate spin magnetizations in a groundwater aquifer to study the distortion of the NMR response because of electrical heterogeneities in the medium. Analyses of entire pulse moment sequences yield the cumulative sensitivities to electrical conductivity and water-content variations in the subsurface. We illustrate the influence of conductivity on NMR responses using a limited number of models. From these models we found that electrical conductivity anomalies in the shallow subsurface (<50 m) having values =0.1 S m-1 and volumes with linear dimensions in the order of our loop size (i.e. edge length 100 m) can have a strong influence on the NMR response and ought to be taken into account in the inversion of surface-NMR data. The effect increases non-linearly with increased body size, increased conductivity contrast and decreased anomaly depth.

Field experiment provides ground truth for surface nuclear magnetic resonance measurement

The need for sustainable management of fresh water resources is one of the great challenges of the 21st century. Since most of the planet's liquid fresh water exists as groundwater, it is essential to develop non‐invasive geophysical techniques to characterize groundwater aquifers. A field experiment was conducted in the High Plains Aquifer, central United States, to explore the mechanisms governing the non‐invasive Surface NMR (SNMR) technology. We acquired both SNMR data and logging NMR data at a field site, along with lithology information from drill cuttings. This allowed us to directly compare the NMR relaxation parameter measured during logging,T2, to the relaxation parameter T2* measured using the SNMR method. The latter can be affected by inhomogeneity in the magnetic field, thus obscuring the link between the NMR relaxation parameter and the hydraulic conductivity of the geologic material. When the logging T2data were transformed to pseudo‐T2* data, by accounting for inhomogeneity in the magnetic field and instrument dead time, we found good agreement with T2* obtained from the SNMR measurement. These results, combined with the additional information about lithology at the site, allowed us to delineate the physical mechanisms governing the SNMR measurement. Such understanding is a critical step in developing SNMR as a reliable geophysical method for the assessment of groundwater resources.

Optimal Design Features of Camelized Human Single-domain Antibody Libraries

We have constructed a human V(H) library based on a camelized V(H) sequence. The library was constructed with complete randomization of 19 of the 23 CDR3 residues and was panned against two monoclonal antibody targets to generate V(H) sequences for determination of the antigen contact residue positions. Furthermore, the feasibility and desirability of introducing a disulfide bridge between CDR1 and CDR3 was investigated. Sequences derived from the library showed a bias toward the use of C-terminal CDR3 residues as antigen contact residues. Mass spectrometric analyses indicated that CDR1-CDR3 disulfide formation was universal. However, surface plasmon resonance and NMR data showed that the CDR3 constraint imposed by the disulfide bridge was not always desirable. Very high yields of soluble protein products and lack of protein aggregation, as demonstrated by the quality of the (1)H-(15)N HSQC spectra, indicated that the V(H) sequence for library construction was a good choice. These results should be useful in the design of V(H) libraries with optimal features.

Evidence for self-aggregation of the ionophore lasalocid free anion in aqueous solution

Surface tension, conductivity and NMR data for tetraaikylammonium salts of lasalocid in water show that they behave as surfactants; their high solubility thus involves lasalocid anion self-aggregation.