Surface Nuclear Magnetic Resonance Research Articles

Envelope Extraction Algorithm for Magnetic Resonance Sounding Signals Based on Adaptive Gaussian Filters

Magnetic resonance sounding is a geophysical method for quantitatively determining the state for groundwater storage that has gained international attention in recent years. However, the practical acquisition of magnetic resonance sounding signals, which are on the nanovolt scale, is susceptible to various types of interference, such as power-line harmonics, random noise, and spike noise. Such interference can degrade the quality of magnetic resonance sounding signals and, in severe cases, be completely drowned out by noise. This paper introduces an adaptive Gaussian filtering algorithm that is well-suited for handling intricate noise signals due to its adaptive solving characteristics and iterative sifting approach. Notably, the algorithm can process signals without relying on prior knowledge. The adaptive Gaussian filtering algorithm is applied for the envelope extraction of noisy magnetic resonance sounding signals, and the reliability and effectiveness of the method are rigorously validated. The simulation results reveal that, even under strong noise interference (with original signal-to-noise ratios ranging from −7 dB to −25 dB), the magnetic resonance sounding signal obtained after algorithmic processing is compared to the ideal signal, with 16 sets of data statistics, and the algorithm ensures an initial amplitude uncertainty within 4nV and restricts the uncertainty of the relaxation time within a 6 ms range. The signal-to-noise ratio can be boosted by up to 53 dB. The comparative assessments with classical algorithms such as empirical mode decomposition and the harmonic modeling method confirm the superior performance of the adaptive Gaussian filtering algorithm. The processing of the field data also fully proved the practical application effects of the algorithm.

Groundwater recharge is diffuse in semi-arid African drylands: Evidence from highly instrumented observatories

We use two comprehensively instrumented field observatories to understand groundwater recharge processes in African drylands. The observatories are located on crystalline basement geology in semi-arid parts of Ghana and Burkina Faso, aridity indices 0.43 and 0.29, respectively, and we report 2017–2019 observations. Groundwater recharge was quantified by inverse water table fluctuation models using specific yield estimates derived from magnetic resonance soundings. Evidence for recharge drivers and mechanisms comes from high resolution meteorological observations, soil moisture (logged hourly and weekly along hillslope transects), overland flow plots, river stage, and stable isotopes of O and H in rainfall events and groundwater. Groundwater recharge varied between 87 and 175 mm/y, i.e. 7–15 % of annual rainfall. Rainfall was twice the volume of water lost via actual evapotranspiration across the four peak months (Jun-Sep) of the monsoon. This seasonal water surplus of ∼ 350 mm/y is not characterised by the annual scale of the aridity index. Overland flow was rare and soil moisture deficits were overcome at all monitoring locations. Large rainfall events only produced appreciable recharge when the antecedent soil moisture was close to field capacity, yet always produced large responses in river stage. Stable isotopes of O and H in groundwater indicate no evidence of evapotranspiration prior to infiltration and their composition is akin to depleted isotopic rainfall at the monsoon peak. Stable isotopes indicate recharge season timing and not a relationship between intense rainfall and groundwater recharge. We contend that the mechanism for groundwater recharge is predominantly diffuse in these semi-arid African settings.

Non-invasive geophysical methods for monitoring the shallow aquifer based on time-lapse electrical resistivity tomography, magnetic resonance sounding, and spontaneous potential methods

The Ningdong coalfield has played a pivotal role in advancing local economic development and meeting national energy. Nevertheless, mining operations have engendered ecological challenges encompassing subterranean water depletion, land desertification, and ground subsidence, primarily stemming from the disruption of coal seam roof strata. Consequently, the local ecosystem has incurred substantial harm. Water-preserved coal mining presently constitutes the pivotal technology in mitigating this problem. The primary challenge of this technique lies in identifying critical aquifer layers and understanding the heights of water-conducting fracture zones. To obtain a precise comprehension of the seepage patterns within the upper coal seam aquifer during mining, delineate the extent of water-conducting fracture zones, non-invasive geophysical techniques such as time-lapse electrical resistivity tomography (TL-ERT), magnetic resonance sounding (MRS), and spontaneous potential (SP) have been employed to monitor alterations within the shallow coalfield’s aquifer throughout the mining process in the Ningdong coalfield. By conducting meticulous examinations of fluctuations in resistivity, moisture content, and self-potential within the superjacent strata during coal seam extraction, the predominant underground water infiltration strata were ascertained, concurrently enabling the estimation of the development elevation of water-conducting fracture zones. This outcome furnishes a geophysical underpinning for endeavors concerning local water-preserved coal mining and ecological rehabilitation.

Gradient-based surface nuclear magnetic resonance for groundwater investigation

In medical magnetic resonance imaging, spatial localization (imaging) is based upon the application of controlled magnetic field gradients on top of the main magnetic field to spatially modulate the frequency and/or phase of the nuclear magnetic resonance (NMR) signal across the volume of investigation. In this work, we have applied similar physical principles to produce controlled magnetic field gradients during surface NMR-based groundwater investigations. In this approach, a gradient pulse of variable amplitude or duration is applied immediately after the excitation pulse to cause predictable phase encoding of the NMR signal as a function of depth. This approach is also applicable to emerging surface NMR detection methods that use a prepolarization field with fast nonadiabatic turn-off to generate detectable NMR signals from the shallow subsurface. In this case, the gradient pulse is applied after terminating the prepolarization field and provides a heretofore unavailable means of localizing the NMR response as a function of depth. The application of gradients can also be combined with tip-angle-based modulation to yield higher imaging resolution than can be achieved through either gradient- or tip-angle-based imaging alone. We implemented this new gradient-based capability into a surface NMR gradient generation accessory that is compatible with the GMR-Flex instrument and developed surface NMR-specific forward modeling and linear inverse models. We validated the accuracy of this novel gradient-based sNMR technology using computer simulations, experiments using a small pool filled with a discrete layer of bulk water, and field experiments at well-characterized groundwater test sites along Ebey Island, WA, and Larned, KS. The gradient-based sNMR imaging observations were compared with high-resolution direct push NMR results observed at these sites. The results of computer simulations and field experiments indicate improvements in both the detection (signal-to-noise ratio) and spatial resolution of shallow subsurface water content using gradient-based surface NMR, compared with traditional surface NMR imaging methods.

Impacts of hydrofacies geometry designed from seismic refraction tomography on estimated hydrogeophysical variables

Abstract. Understanding the critical zone processes related to groundwater flows relies on subsurface structure knowledge and its associated parameters. We propose a methodology to draw the patterns of the subsurface critical zone at the catchment scale from seismic refraction data and show its interest for hydrological modelling. The designed patterns define the structure of a physically based distributed hydrological model applied to a mountainous catchment. With that goal, we acquired 10 seismic profiles covering the different geomorphology zones of the studied catchment. We develop a methodology to analyse the geostatistical characteristics of the seismic data and interpolate them over the whole catchment. The applied geostatistical model considers the scale variability of the subsurface structures observed from the seismic data analysis. We use compressional seismic wave velocity thresholds to identify the depth of the soil and saprolite bottom boundaries. Assuming that such porous compartments host the main part of the active aquifer, their patterns are embedded in a distributed hydrological model. We examine the sensitivity of classical hydrological data (piezometric heads) and geophysical data (magnetic resonance soundings) to the applied velocity thresholds used to define the soil and saprolite boundaries. Different sets of hydrogeological parameters are used in order to distinguish general trends or specificities related to the choice of parameter values. The application of the methodology to an actual catchment illustrates the interest of seismic refraction in constraining the structure of the critical zone subsurface compartments. The sensitivity tests highlight the complementarity of the analysed hydrogeophysical data sets.

An investigation of factors affecting the depths of steady-state surface nuclear magnetic resonance signals

Recent developments in surface nuclear magnetic resonance (NMR) data transmit schemes, called steady-state measurements, involve the acquisition of the NMR signal during a train of closely spaced identical pulses, and indicate great promise to enhance the measurement’s signal-to-noise ratio. The steady-state signal displays a complex dependence on a range of experimental parameters, such as the strength of the individual pulse and the separation between the pulses, as well as subsurface parameters, such as the relaxation times controlling the time dependence of the NMR signals. It is imperative to understand the role that each of these parameters plays in controlling the depth of origin for steady-state signals so as to enable optimization of a suite of measurements consisting of the fewest possible measurements delivering satisfactory resolution. A range of synthetic studies are conducted to gain insights into controls on steady-state signals’ depths of origin. Relaxation times, duty cycle, and pulse train timing are all observed to influence the signal’s depth, in addition to the pulse duration and current strength. A discussion of whether high-duty cycle steady-state sequences may enhance depth penetration is given, along with the presentation of a field data set composed of a nontraditional depth sounding approach, where repetition times are varied to encode depth sensitivity.

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.

Magnetic Resonance Sounding Data Denoising based on Successive Dn-ResUnet Models with Noise Pre-Detection Using Support Vector Machine

Magnetic Resonance Sounding Data Denoising based on Successive Dn-ResUnet Models with Noise Pre-Detection Using Support Vector Machine

A Multipulsed Power Source With Rectangularity Improvement for Magnetic Resonance Sounding

A Multipulsed Power Source With Rectangularity Improvement for Magnetic Resonance Sounding

Study on aquifer characterization using surface nuclear magnetic resonance

Study on aquifer characterization using surface nuclear magnetic resonance

Synthetic Opals or Versatile Nanotools-A One-Step Synthesis of Uniform Spherical Silica Particles.

Synthetic opals, a composition of homogeneous silica spheres in the mesoscale size range, have attracted the attention of scientists due to their favorable chemical and physical properties. Their chemical inertness and stability, biocompatibility, homogeneity, elevated specific surface area, and ease of functionalization of their surfaces make them a versatile nanotool. In the present study, the Stöber process was used to investigate the effect of parameters, such as reagent concentration and synthesis temperature, on the resulting silica particle size and structure. The optimal conditions for successfully obtaining homogeneous particles in the mesoscale range with high reproducibility were investigated. Several synthesis procedures and their dependence on the reaction temperature were presented to allow the selection of the assumed diameter of silica spheres. The numerous samples obtained were examined for size, homogeneity, structure, and specific surface area. On the basis of specific surface area measurements and nuclear magnetic resonance studies, the internal hierarchical structure of the spherical silica was confirmed as consisting of a solid core and layers of secondary spheres covered by a solid shell. Structural studies (X-ray Spectroscopy, X-ray Absorption Near-Edge Structure, and nuclear magnetic resonance), together with infrared vibrational spectroscopy, showed no dependence of the structure of the obtained mesospheres on the concentration of reagents and the size of the obtained particles.

Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance – three Danish case studies

Abstract. Groundwater is an essential part of the water supply worldwide, and the demands on this water source can be expected to increase in the future. To satisfy the need for resources and to ensure sustainable use of resources, increasingly detailed knowledge of groundwater systems is necessary. However, it is difficult to directly map groundwater with well-established geophysical methods as these are sensitive to both lithology and pore fluid. Surface nuclear magnetic resonance (SNMR) is the only method with a direct sensitivity to water, and it is capable of non-invasively quantifying water content and porosity in the subsurface. Despite these attractive features, SNMR has not been widely adopted in hydrological research, the main reason being an often-poor signal-to-noise ratio, which leads to long acquisition times and high uncertainty in terms of results. Recent advances in SNMR acquisition protocols based on a novel steady-state approach have demonstrated the capability of acquiring high-quality data much faster than previously possible. In turn, this has enabled high-density groundwater mapping with SNMR. We demonstrate the applicability of the new steady-state scheme in three field campaigns in Denmark, where more than 100 SNMR soundings were conducted with a depth of investigation of approximately 30 m. We show how the SNMR soundings enable us to track water level variations at the regional scale, and we demonstrate a high correlation between water levels obtained from SNMR data and water levels measured in boreholes. We also interpret the SNMR results jointly with independent transient electromagnetic (TEM) data, which allows us to identify regions with water bound in small pores. Field practice and SNMR acquisition protocols were optimized during the campaigns, and we now routinely measure high-quality data at 8 to 10 sites per day with a two-person field crew. Together, the results from the three surveys demonstrate that, with steady-state SNMR, it is now possible to map regional variations in water levels with high-quality data and short acquisition times.

Bloch–Siegert Effect for Surface Nuclear Magnetic Resonance Sounding Experiments in the Unsaturated Zone

The Bloch–Siegert effect is relevant for NMR experiments where components of the excitation pulse other than the circularly polarized component have an influence on the evolution of the magnetization of the spin system under consideration. For linearly polarized excitation fields this happens at amplitudes higher than roughly one tenth of the magnitude of the static magnetic field. Since surface nuclear magnetic resonance (SNMR) experiments, also called magnetic-resonance-soundings (MRS), are conducted in the relatively low local field of the earth, the Bloch–Siegert effect can quickly become relevant. This is especially the case for SNMR experiments in the unsaturated zone, where due to short relaxation times fast pulses of high intensity must be used. To describe the Bloch–Siegert effect, we use the average Hamiltonian approximation obtained by the Magnus expansion of up to fifth order, as well as the solution of the Bloch equations. The results of these approximations are tested against the Bloch simulations and it is shown that they are only valid for limited ranges of the excitation field amplitude. The influence of the Bloch–Siegert effect on sensitivity kernels is described and verified with experimental data obtained with a small scale SNMR sensor on water containers.

A surface NMR forward in a dot product

SUMMARY The computation required to simulate surface nuclear magnetic resonance (SNMR) data increases proportionally with the number of sequences and number of pulses in each sequence. This poses a particular challenge to modelling steady-state SNMR, where suites of sequences are acquired, each of which require modelling 10–100 s of pulses. To model such data efficiently, we have developed a reformulation of surface NMR forward model, where the geometry of transmit and receive fields are encapsulated into a vector (or set of vectors), which we call B1-volume-receive (BVR) curves. Projecting BVR curve(s) along complimentary magnetization solutions for a particular sequence amounts to computing the full SNMR forward model. The formulation has the additional advantage that computations for increased transmitter current amounts to a relative translation between the BVR and magnetization solutions. We generate 1-D kernels using BVR curves and standard integration techniques and find the difference is within 2 per cent. Using BVR curves, a typical suite of steady-state kernels can be computed two orders of magnitude faster than previous approaches.

Acquisition and correction for early surface nuclear magnetic resonance signal based on multi-turn small air-core coil sensors

Surface nuclear magnetic resonance (SNMR) with multi-turn small air-core coil sensor (ACS) has considerable potential for the detection of shallow soil water or oil. However, loss of the early free induced decay signal and the distortion of the recorded signal arising from the ACS, make it difficult to quantitatively evaluate hydrological information. To address this problem, we propose an early signal acquisition and correction method. A fast-switching unit is applied to acquire the early signal. And a correction method based on the mathematical model of the ACS is proposed. Finally, the performance of the proposed method is evaluated by simulation experiments. Results show that the proposed method overcomes the signal attenuation caused by the ACS, while the fitting error of key parameters decreases from about 15% to 2%. Comparative test results of the existing method in an electromagnetically shielded laboratory further demonstrate the effectiveness of the proposed method.

Advanced surface coil layout with intrinsic noise cancellation properties for surface-NMR applications

A recent study demonstrated that in small-scale prepolarized surface nuclear magnetic resonance (SNMR-PP) measurements with a footprint of a few square meters, customized PP switch-off ramps can serve as an efficient excitation mechanism, eliminating the requirement for a conventional oscillating excitation pulse. This approach enables the detection of short relaxation signals from the unsaturated soil zone and can, therefore, be used to directly provide soil moisture and pore geometry information. Because ultimately such small-scale SNMR-PP setups are intended for a mobile application, it is necessary to develop strategies that allow for speedy measurement progress and do not require noise cancellation protocols based on reference stations. Hence, we developed a new concentric figure-of-eight (cFOE) loop layout that combines the direction independence of a circular loop with the intrinsic noise cancellation properties of a classical FOE-loop. This approach significantly decreases the measurement time because suitable signal-to-noise ratios are reached much faster compared to a classical circular loop and will bring us one step further toward fast and non-invasive soil moisture mapping applications.

Synergy in the Microbial Cyclic Lipopeptide/Petroleum-Derived Surfactant Mixture Can Reduce the Total Surfactant Consumption

We report the synergistic effect of the addition of a microbial cyclic lipopeptide, surfactin (SF), to the most common petroleum-derived surfactant, sodium dodecyl sulfate (SDS). The addition of a small amount of SF (0.1 mol %) to an aqueous solution of SDS reduces the critical micelle concentration (CMC) of SDS from 10–3 to 10–6 M order. The addition of SF to SDS at various ratios lowered the surface tension at the CMC of SDS, indicating CMC reduction and, thus, the minimization of total SDS consumption without loss of surface activity. Surface tension measurement and nuclear magnetic resonance spectroscopy were conducted to analyze the synergy between SDS and SF in aqueous solutions as a function of composition. The interaction parameters of the mixed monolayer and mixed micelles were negative, indicating the occurrence of attractive interactions between SDS and SF, which were stronger than those among the individual surfactants. Moreover, the surface tension at the CMC, area occupied per surfactant molecule, difference in the interaction parameter, and 1H NMR chemical shift values of the SDS/SF mixtures as a function of their composition exhibited an extremum at a mole fraction of 0.7. These results suggest that SF has the peculiarities of encapsulation of the anionic surfactant of SDS within the inner cavity and can screen the electrostatic repulsion of SDS via the formation of their inclusion complex at SDS:SF = 2:1, which facilitates the formation of mixed monolayers and micelles in a more stable state.

Nuclear magnetic resonance at the laboratory and field scale as a tool for detecting redox fronts in aquifers

Surface nuclear magnetic resonance (NMR) provides information not only on the lithology and water transport characteristics of aquifer systems but also on the state of iron mineralization within the pore space. This feature makes surface NMR a potential tool for the observation of changing redox conditions in the aquifer, which control the type and oxidation state of iron minerals and, relatedly, the buffering or release of pollutants that may pose a threat to drinking water resources. Our study aims on testing this potential and focuses on pyrite contained in the matrix of a sandy aquifer that serves as a natural denitrification buffer in a drinking water catchment area with intensive agricultural use. We observe a significant change in the surface-NMR relaxation times related to the pyrite content in the subsurface, which is most obvious at the transition from the pyrite-free oxic zone and the pyrite-bearing reducing zone. Complementary laboratory experiments using core material from the study site, including laboratory NMR and geochemical analyses, verify that the influence of pyrite content predominates the NMR relaxation behavior rather than pore size, porosity, or carbon content. The mean relaxation times measured in the sediment without pyrite exceed those with pyrite by approximately 20%–100%. We conclude that surface NMR can serve as a capable tool to locate and monitor the pyrite-based denitrification buffer. However, for general applicability within the given framework, more research is needed to address the natural ambiguity among iron content, its redox state and speciation, and pore size.

Enhanced piroctone olamine retention from shampoo for superior anti-dandruff efficacy.

Dandruff is a pervasive chronic condition which negatively impacts quality of life. Effective treatment requires efficient delivery of scalp benefit agents that control commensal scalp Malassezia levels. Delivery of benefit agents from shampoos requires balancing many technical parameters to achieve the desired outcome without sacrificing secondary parameters, such as cosmetic attributes. To develop formulation technologies that increase the shampoo delivery efficiency of the scalp benefit agent piroctone olamine (PO). Increased delivery should result in increased anti-dandruff efficacy. Micellar Stability and Association parameters were quantified via dynamic surface tension and nuclear magnetic resonance (NMR) diffusion parameters, respectively. PO delivery has been assessed in vivo both on the scalp surface and follicular infindibula using extraction procedures and analytical analysis. Clinical anti-dandruff efficacy was assessed for an advanced delivery technology prototype in comparison to standard delivery technology. Shampoo prototypes have been developed that increase the delivery efficiency of PO. Both surfactant and polymer coacervate-based approaches have been developed. Decreased micellar stability results in weaker association between PO and micelles, resulting in more efficient PO retention on the scalp surface and delivery to the infundibula. Increased charge density of cationic polymers optimizes coacervation enabling improved PO delivery as well. Increased PO delivery has been shown clinically to result in higher anti-dandruff efficacy as measured by both visible flakes and underlying biomarkers. Increased efficiency PO delivery shampoos have been developed by optimization of both surfactant and coacervate parameters. The increased deposition efficiency results in significantly more products with significantly greater anti-dandruff efficacy.

Multitype Noise Suppression in Magnetic Resonance Sounding Data Based on a Time–Frequency Fully Convolutional Neural Network

Magnetic resonance sounding (MRS) is one of the technical applications of nuclear magnetic resonance (NMR) used to directly detect and quantify groundwater content. MRS suffers from a low signal-to-noise ratio (SNR) due to the low amplitude of free induction decay (FID) signals and an inability to shield environmental noise. In this paper, a time-frequency fully convolutional neural network (TFCN) was proposed to suppress random, harmonic, and spike noise from MRS data. The TFCN parameters were trained with the time-frequency spectrum obtained by the short-time Fourier transform (STFT) of the MRS datasets as the input and the noise-free FID signals as the output. Based on the results of synthetic and field data experiments, the TFCN was compared with existing denoising methods. The results showed that the TFCN extracted the envelope of the FID signals from low-SNR random noise with higher accuracy than other methods. Moreover, the TFCN simultaneously suppressed multiple types of noise and exhibited high computational efficiency.