Nuclear Magnetic Resonance Tools Research Articles

High‐Resolution Direct Push NMR Tools for Groundwater Investigations

AbstractA small‐diameter nuclear magnetic resonance (NMR) technology optimized for use with direct push (DP) and cone penetrometer test (CPT) drilling has been developed. The DP NMR tool can be deployed through 2.25‐in. diameter DP and CPT drilling rods allowing high‐resolution NMR logging measurements to be acquired during retraction of drill rods. DP NMR technology runs from a person‐portable battery‐powered control unit and provides significantly higher resolution in both the spatial (vertical) dimension and in the time domain of the NMR measurement than previously available NMR technology. In this study, we summarize the development of two different DP NMR tools and demonstrate their application at different sites within the United States. We believe that this technology can provide a leap forward in adoption of NMR technology for high‐resolution hydrological and geophysical investigations in groundwater resources and environmental remediation applications.

A novel approach of 19F NMR based sensor

Reliable and precise methods are to be applied ranging from biological field to diagnosis and quality control to identify target analytes in samples. Nuclear magnetic resonance (NMR) is a strongly recommended process that is suitable for collecting data multidimensionally at molecular and atomic levels. Information obtained from the NMR technique provides molecular structures, molecular interactions, dynamic and diffusional properties of molecules. Overlapping of NMR signals of each component makes it difficult to interpret data and low sensitivity makes it unfitting for many samples with a low concentration of analytes. These limitations can be rectified by adding heteronuclear specially designed sensors, inventive transduction mechanism and strong pulse sequences. 19F NMR tool is extensively accepted method to detect the interactions among a variety of biological substrates with 19F-isotopic species. This review includes the detection of biomolecules, mainly enzymes and enzymatic reactions based on sensor applicability.

Chemical constituents variation of seed oil of the Chinese tallow tree (Sapium sebiferum (L.) Roxb) at different harvesting time

Sapium sebiferum (L.) Roxb, has a long history of being used as an oil-producing plant due to its high oil content of the seeds. In recent years, the seed oil of this tree has gained considerable interest as an ideal material to produce biodiesel. To optimize the harvesting time of the seed, we tracked the variation of chemical constituents of seed oil harvested in different days (from October 1, 2021 to November 30, 2021). Firstly, the chemical constituents and fatty acid profile of external wax and internal kernel oil were studied, using nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS) as structure elucidation tools. Secondly, the constituent variation of external wax and kernel oil from different harvesting time was analyzed by 1H NMR and chemometrics tool. The results showed that unsaturated fatty acids in the kernel oil accumulated during harvesting time, while the external wax was progressively oxidized to formic acid due to exposure to air. Since the kernel oil was seal off from oxygen, no oxidation process was observed in it. Considering for the quality and total weight of lipids for biodiesel manufacturing, we suggest that the optimal harvesting time for seeds of S. sebiferum should be early November, when the fruit undergo complete cracking and the seeds are initially exposure to air. This information is practically helpful for optimizing the production of biodiesel from S. sebiferum and other similar oil-producing plants.

On Design Challenges of Portable Nuclear Magnetic Resonance System

This article studies the optimal design approach for a portable nuclear magnetic resonance (NMR) system for use in non-destructive flow measurement applications. The mechanical and electromagnetic design procedures were carried out using the Ansys Maxwell finite-element analysis (FEA) software tool. The proposed procedure considered homogeneity and strength constraints while ensuring the desired functionality of the intended device for a given application. A modified particle swarm optimization (MPSO) algorithm was proposed as a reference design framework for optimization stages. The optimally designed NMR tool was prototyped, and its functionality was validated via several case studies. To assess the functionality of the prototyped device, Larmor frequency for hydrogen atom was captured and compared with theoretical results. Furthermore, the functionality and accuracy of the prototyped NMR tool is compared to the off-the-shelf NMR tool. Results demonstrated the feasibility and accuracy of the prototyped NMR tool constrained by factors, such as being lightweight and compact.

Design Scheme of Proximal Adaptive Noise Cancellation in Shallow Hydrological Monitoring Using a Multichannel Nuclear Magnetic Resonance Logging Tool

Small diameter nuclear magnetic resonance (NMR) logging tools are used to detect hydrologic characteristics, soil moisture, and migration of petroleum hydrocarbon contaminants near-surface in the existing hydrologic monitoring wells. However, the majority of hydrologic monitoring wells are located in densely populated areas with high electromagnetic noise levels, seriously affecting the monitoring accuracy. Consequently, decreasing electromagnetic noise is a critical component in expanding the use of small-diameter NMR logging tools. In this study, a proximal adaptive noise cancellation (PANC) method was introduced for a small-diameter NMR tool. A simulation model is used to evaluate the performance of various ANC algorithms in different conditions. The effect of coil size and position on the PANC method was then analyzed. Subsequently, a static experiment is conducted to demonstrate the validity of the method. The results show that the PANC method achieves 55% noise energy suppression without affecting the target signal intensity and bandwidth.

Mechanically oscillating sample under magnetic field gradients: MOS-NMR

Nuclear Magnetic Resonance (NMR) has been widely used in Petroleum Science and Engineering to study geological formations (porous media) in laboratories or under well-logging conditions. In both cases, NMR is still evolving to provide more accurate data on well productivity. In well-logging, NMR is one of the main tools used in determining the economic viability of an oil well due to the reliability of measurements of fluid types, porosity, pore size, and permeability of the reservoir under analysis. There are two kinds of NMR well-logging techniques: Wireline and Logging While Drilling (LWD). In the latter, due to the drilling process, measurements are made with the NMR tool translating, vibrating and, in some cases, rotating relatively to the geological formation. To understand the behavior of NMR signals measured under LWD conditions, not yet including displacement and drill vibration, we have recently developed a single-sided magnet, probes, and a mechanical system that emulates a relative sinusoidal motion between the sample and the applied magnetic field. This equipment was used to emulate a LWD tool operating under normal pressure and temperature conditions.

Challenges and advances in measuring sap flow in agriculture and agroforestry: A review with focus on nuclear magnetic resonance.

Sap flow measurement is one of the most effective methods for quantifying plant water use.A better understanding of sap flow dynamics can aid in more efficient water and crop management, particularly under unpredictable rainfall patterns and water scarcity resulting from climate change. In addition to detecting infected plants, sap flow measurement helps select plant species that could better cope with hotter and drier conditions. There exist multiple methods to measure sap flow including heat balance, dyes and radiolabeled tracers. Heat sensor-based techniques are the most popular and commercially available to study plant hydraulics, even though most of them are invasive and associated with multiple kinds of errors. Heat-based methods are prone to errors due to misalignment of probes and wounding, despite all the advances in this technology. Among existing methods for measuring sap flow, nuclear magnetic resonance (NMR) is an appropriate non-invasive approach. However, there are challenges associated with applications of NMR to measure sap flow in trees or field crops, such as producing homogeneous magnetic field, bulkiness and poor portable nature of the instruments, and operational complexity. Nonetheless, various advances have been recently made that allow the manufacture of portable NMR tools for measuring sap flow in plants. The basic concept of the portal NMR tool is based on an external magnetic field to measure the sap flow and hence advances in magnet types and magnet arrangements (e.g., C-type, U-type, and Halbach magnets) are critical components of NMR-based sap flow measuring tools. Developing a non-invasive, portable and inexpensive NMR tool that can be easily used under field conditions would significantly improve our ability to monitor vegetation responses to environmental change.

Learnings From a New Slimhole LWD NMR Technology

This paper presents recent results obtained from a new 4.75-in. logging-while-drilling (LWD) nuclear magnetic resonance (NMR) tool. Data from several wells provided real-time operational insight and new petrophysical learnings. The new LWD technology offers an innovative capability to simultaneously measure NMR T1 and T2 distributions with reduced sensitivity to drilling mud conductivity and a real-time sensor motion-warning system. The real-time T1 and T2 spectra compare favorably with the data set retrieved from the tool memory. The LWD NMR measurements were followed by wireline (WL) NMR logging for comparison in three wells. In carbonate reservoirs, the main objective was to evaluate the new NMR tool’s capability in resolving carbonate pore size with slow NMR relaxation rates. Another set of NMR logs contained time-lapse repeat passes in a well drilled with oil-based mud (OBM) that traversed a clastic reservoir. The sequence of measurements identified rock types and provided a unique insight into the mud filtrate invasion process. In a carbonate reservoir, the LWD NMR real-time partial porosity estimates were in excellent agreement with the core-calibrated WL micro-, meso-, and macropore volumes. Another carbonate formation contained high-permeability layers embedded in a microporous rock, where the real-time LWD NMR logs successfully located the high-quality rock zones, later verified by WL logging. In the clastic reservoir, the while-drilling LWD NMR data indicated native light hydrocarbons, whereas the subsequent LWD reaming and WL NMR passes showed a displacement of native hydrocarbons by oil-based mud filtrate (OBMF). The native hydrocarbon signature observed by the LWD NMR tool was in good agreement with the mud gas log. OBMF invasion occurred shortly after drilling, indicated by the differences observed in the LWD NMR relogged data acquired several hours after the while-drilling pass. The WL NMR data, logged about 4 days after drilling, showed advanced stages of OBMF invasion, including formation water displacement and wettability changes in intermediate and large pores. Finally, the environmental noise remained low in the LWD NMR data set acquired in a well in which the mud salinity changed by several folds, indicating that mud salinity had little effect on the quality of LWD NMR logs in slim holes. The new slimhole LWD NMR technology demonstrated its robust capability to provide T1 and T2 logs through several examples. For the first time, a time-lapse comparison of NMR logs showed that OBMF invasion could occur in silty sands with high capillary-bound fluid fractions.

Formation Evaluation Using NMR, Mud Gas, and Triple-Combo Data – A Norwegian Logging-While-Drilling Case History

The presence of gas in hydrocarbon reservoirs has a distinct effect on commonly used porosity logging measurements such as density, neutron, and nuclear magnetic resonance (NMR). Although the effect of gas on NMR measurements is well understood, it remains difficult to estimate true formation porosity and hydrocarbon (HC) saturation exclusively from NMR data in gas-bearing formations. The hydrogen index (HI) of gas is much smaller than one and causes an underestimation of the measured NMR porosity. Unless temperature, pressure, HC composition, and saturation in the volume sensed by NMR are known accurately, compensating for the effect of gas is not easily accomplished. This paper compares different approaches for NMR gas zone analysis, and it introduces a new method integrating NMR logging data with a HI curve derived from mud gas surface logging. The results are connected to a full and consistent petrophysical reservoir description. Data and results from two wells drilled in a North Sea clastic reservoir are presented. The reservoir is dominated by thick units of sandstone, deposited in a submarine turbidite fan, with high porosity and high permeability. The wells were logged with triple-combo (i.e., gamma ray, density, neutron, and resistivity), NMR, and formation tester (FT) tools while drilling across gas, oil, and water intervals. Basic mud gas data are available from surface logging. Uncorrected NMR porosity shows an average porosity underestimation of 6 p.u. in the gas zone compared to triple-combo computer-processed interpretation (CPI) processing. The standalone evaluation of NMR data by a T2 cutoff approach and dual wait-time (DTW) data processing reduces the average porosity mismatch but results in zones of under- and overcorrection of the gas effect. Combining NMR DTW data with density improves the results and reduces the average porosity mismatch to less than 2 p.u. Compositional information from the mud gas data validates an inferred trend of fluid property variation in gas and oil zones across the reservoir and is used to derive a continuous HI log for further improving porosity and gas saturation estimation. Complementary to the results of the integrated data evaluation, we show independent results from mud gas data evaluation using a recently implemented method that provides independent porosity, permeability, and saturation indexes. Adverse conditions for the different approaches, including invasion, variations in mineralogy, and the limited vertical resolution of mud gas data, are discussed. Finally, the benefits and potential of combining NMR, mud gas, and triple-combo data are summarized.

Synthesizing Nuclear Magnetic Resonance (NMR) Outputs for Clastic Rocks Using Machine Learning Methods, Examples from North West Shelf and Perth Basin, Western Australia

A nuclear magnetic resonance (NMR) logging tool can provide important rock and fluid properties that are necessary for a reliable reservoir evaluation. Pore size distribution based on T2 relaxation time and resulting permeability are among those parameters that cannot be provided by conventional logging tools. For wells drilled before the 1990s and for many recent wells there is no NMR data available due to the tool availability and the logging cost, respectively. This study used a large database of combinable magnetic resonance (CMR) to assess the performance of several well-known machine learning (ML) methods to generate some of the NMR tool’s outputs for clastic rocks using typical well-logs as inputs. NMR tool’s outputs, such as clay bound water (CBW), irreducible pore fluid (known as bulk volume irreducible, BVI), producible fluid (known as the free fluid index, FFI), logarithmic mean of T2 relaxation time (T2LM), irreducible water saturation (Swirr), and permeability from Coates and SDR models were generated in this study. The well logs were collected from 14 wells of Western Australia (WA) within 3 offshore basins. About 80% of the data points were used for training and validation purposes and 20% of the whole data was kept as a blind set with no involvement in the training process to check the validity of the ML methods. The comparison of results shows that the Adaptive Boosting, known as AdaBoost model, has given the most impressive performance to predict CBW, FFI, permeability, T2LM, and SWirr for the blind set with R2 more than 0.9. The accuracy of the ML model for the blind dataset suggests that the approach can be used to generate NMR tool outputs with high accuracy.

Urinary Metabolites as Predictors of Acute Mountain Sickness Severity.

Individuals sojourning at high altitude (≥2,500m) often develop acute mountain sickness (AMS). However, substantial unexplained inter-individual variability in AMS severity exists. Untargeted metabolomics assays are increasingly used to identify novel biomarkers of susceptibility to illness, and to elucidate biological pathways linking environmental exposures to health outcomes. This study used untargeted nuclear magnetic resonance (NMR)-based metabolomics to identify urine metabolites associated with AMS severity during high altitude sojourn. Following a 21-day stay at sea level (SL; 55m), 17 healthy males were transported to high altitude (HA; 4,300m) for a 22-day sojourn. AMS symptoms measured twice daily during the first 5days at HA were used to dichotomize participants according to AMS severity: moderate/severe AMS (AMS; n=11) or no/mild AMS (NoAMS; n=6). Urine samples collected on SL day 12 and HA days 1 and 18 were analyzed using proton NMR tools and the data were subjected to multivariate analyses. The SL urinary metabolite profiles were significantly different (p≤0.05) between AMS vs. NoAMS individuals prior to high altitude exposure. Differentially expressed metabolites included elevated levels of creatine and acetylcarnitine, and decreased levels of hypoxanthine and taurine in the AMS vs. NoAMS group. In addition, the levels of two amino acid derivatives (4-hydroxyphenylpyruvate and N-methylhistidine) and two unidentified metabolites (doublet peaks at 3.33ppm and a singlet at 8.20ppm) were significantly different between groups at SL. By HA day 18, the differences in urinary metabolites between AMS and NoAMS participants had largely resolved. Pathway analysis of these differentially expressed metabolites indicated that they directly or indirectly play a role in energy metabolism. These observations suggest that alterations in energy metabolism before high altitude exposure may contribute to AMS susceptibility at altitude. If validated in larger cohorts, these markers could inform development of a non-invasive assay to screen individuals for AMS susceptibility prior to high altitude sojourn.

Rapid modeling of borehole measurements of nuclear magnetic resonance via spatial sensitivity functions

Borehole measurements of nuclear magnetic resonance (NMR) are routinely used to estimate in situ rock and fluid properties. Conventional NMR interpretation methods often neglect bed-boundary and layer-thickness effects in the calculation of fluid volumetric concentrations and NMR relaxation-diffusion correlations. Such effects introduce notable spatial averaging of intrinsic rock and fluid properties across thinly bedded formations or in the vicinity of boundaries between layers exhibiting large property contrasts. Forward modeling and inversion methods can mitigate the aforementioned effects and improve the accuracy of true layer properties in the presence of mud-filtrate invasion and borehole environmental effects across spatially complex formations. We have developed a fast and accurate algorithm to simulate borehole NMR measurements using the concept of spatial sensitivity functions (SSFs) that honor NMR physics and incorporate tool, borehole, and formation geometry. Tool sensitivity maps are derived from a 3D multiphysics forward model that couples NMR tool properties, magnetization evolution, and electromagnetic propagation. In addition, a multifluid relaxation model based on Brownstein-Tarr’s equation is introduced to estimate layer NMR porosity decays and relaxation-diffusion correlations from pore-size-dependent rock and fluid properties. The latter model is convolved with the SSFs to reproduce borehole NMR measurements. The results indicate that NMR spatial sensitivity is controlled by porosity, electrical conductivity, excitation pulse duration, and tool geometry. We benchmark and verify the SSF-derived forward approximation against 3D multiphysics simulations for a series of synthetic cases with variable bed thickness and petrophysical properties, and in the presence of mud-filtrate invasion in a vertical well. Results indicate that the approximation can be executed in a few seconds in a central processing unit, by a factor of 1000 times faster than rigorous multiphysics calculations, with maximum root-mean-square errors of 1%.

The Contribution of NMR Spectroscopy in Understanding Perovskite Stabilization Phenomena.

Although it has been exploited since the late 1900s to study hybrid perovskite materials, nuclear magnetic resonance (NMR) spectroscopy has only recently received extraordinary research attention in this field. This very powerful technique allows the study of the physico-chemical and structural properties of molecules by observing the quantum mechanical magnetic properties of an atomic nucleus, in solution as well as in solid state. Its versatility makes it a promising technique either for the atomic and molecular characterization of perovskite precursors in colloidal solution or for the study of the geometry and phase transitions of the obtained perovskite crystals, commonly used as a reference material compared with thin films prepared for applications in optoelectronic devices. This review will explore beyond the current focus on the stability of perovskites (3D in bulk and nanocrystals) investigated via NMR spectroscopy, in order to highlight the chemical flexibility of perovskites and the role of interactions for thermodynamic and moisture stabilization. The exceptional potential of the vast NMR tool set in perovskite structural characterization will be discussed, aimed at choosing the most stable material for optoelectronic applications. The concept of a double-sided characterization in solution and in solid state, in which the organic and inorganic structural components provide unique interactions with each other and with the external components (solvents, additives, etc.), for material solutions processed in thin films, denotes a significant contemporary target.

A novel approach for studying receptor-ligand interactions on living cells surface by using NUS/T1ρ-NMR methodologies combined with computational techniques: The RGDechi15D-αvβ5 integrin complex.

Structural investigations of receptor-ligand interactions on living cells surface by high-resolution Nuclear Magnetic Resonance (NMR) are problematic due to their short lifetime, which often prevents the acquisition of experiments longer than few hours. To overcome these limitations, we developed an on-cell NMR-based approach for exploring the molecular determinants driving the receptor-ligand recognition mechanism under native conditions. Our method relies on the combination of high-resolution structural and dynamics NMR data with Molecular Dynamics simulations and Molecular Docking studies. The key point of our strategy is the use of Non Uniform Sampling (NUS) and T1ρ-NMR techniques to collect atomic-resolution structural and dynamics information on the receptor-ligand interactions with living cells, that can be used as conformational constraints in computational studies. In fact, the application of these two NMR methodologies allows to record spectra with high S/N ratio and resolution within the lifetime of cells. In particular, 2D NUS [1H-1H] trNOESY spectra are used to explore the ligand conformational changes induced by receptor binding; whereas T1ρ-based experiments are applied to characterize the ligand binding epitope by defining two parameters: T1ρ Attenuation factor and T1ρ Binding Effect. This approach has been tested to characterize the molecular determinants regulating the recognition mechanism of αvβ5-integrin by a selective cyclic binder peptide named RGDechi15D. Our data demonstrate that the developed strategy represents an alternative in-cell NMR tool for studying, at atomic resolution, receptor-ligand recognition mechanism on living cells surface. Additionally, our application may be extremely useful for screening of the interaction profiling of drugs with their therapeutic targets in their native cellular environment.

Design of a new LWD NMR tool with high mechanical reliability

Nuclear magnetic resonance (NMR) provides useful information for formation evaluation on pore size and pore volume. Depending on field operations, there are two types of borehole NMR: wireline logging and logging-while-drilling (LWD). The latter type is more convenient. But due to the high mechanical failure risk caused by insufficient mechanical strength of the tool and vibrations during measurement, the quality of LWD NMR measurements are severely affected. In this paper, to enable high reliability and vibration tolerance, we propose a new design and implement a new LWD NMR tool, whose features includes a double hollow cylindric magnet (DHCM) structure and a solenoid-optimized antenna. The DHCM structure greatly reduces the proportion of the magnet in the cross-section of the tool without reducing B0 field strength. Thus, the mechanical strength and the reliability of the tool is greatly improved. The antenna is improved by optimizing the parameters of each coil of the solenoid for finding the generated B1 distribution best matching B0. The new design has a saddle sensing area in the axial and radial plane with a width greater than 50 mm, which is wide enough to ensure the validity of the T2 measurement under strong vibrations. We had demonstrated that this new tool performs well when TE = 0.6 ms, ensuring the measurement richness is suitable for LWD prospecting for unconventional oil and gas reservoirs. Besides, this design is suitable for that in slim holes.

Inside-out azimuthally selective NMR tool using array coil and capacitive decoupling

Inside-out nuclear magnetic resonance (NMR) is a unique technique for investigating large in-situ objects outside of tools, to provide pore structure and pore-bearing fluids properties. However, in borehole, objects towards azimuthal orientations pose different properties, referred to as azimuthal spatial heterogeneity. This may lead to ambiguous evaluations by utilizing present inside-out NMR measurement, which hardly resolves azimuthal information and loses the location information of oil/gas. In this paper, we for the first time design and construct an innovative tool to investigate the heterogeneity of large in-situ samples. The most key component, array coil, which performs with azimuthal selection, measurement consistency and interactive isolation, configured in this novel tool to capture heterogeneity information. Whereas, strong coupling between neighboring coil elements largely decrease the coil sensitivity. Capacitive decoupling network is bridged into adjacent ports without segmenting coils to be decoupled and could be easily adjusted by electrical relays. The coil model and numerical simulation are firstly given to demonstrate the array coil configuration, B1 field map and mutual coupling effects on coil sensitivity. Capacitive network is then introduced to be theoretically and practically analyzed to minimize coupling effects. Simulation and experimental results demonstrate that these coil elements have excellent consistency and independence to feasibly acquire the azimuthal NMR data.

Synthesis and photophysical studies on a new fluorescent phenothiazine-based derivative.

A new typical phenothiazine compound functionalized with thienyl-indandione derivative (PTZTID) was synthesized and characterized using spectral analysis (ultraviolet-visible (UV-vis) light, infrared (IR), 1 H nuclear magnetic resonance (NMR) and 13 C NMR tools). The UV-vis absorption spectra of the PTZTID solution in 1,4-dioxane showed two absorption bands attributed to localized aromatic π-π* transitions of conjugated aromatic moieties and intramolecular charge transfer with the characteristics of a π-π* transition. The fluorescence spectra exhibited a maximum emission wavelength at 580 nm. The effect of concentration on photophysical properties took the form of a minor hypsochromic shift, which was attributed to some extent to the occurrence of H-type aggregation of the PTZTID derivative. Binary solvent effects on the spectroscopic behaviour of PTZTID were measured at different H2 O/1,4-dioxane ratios. Similarly, when increasing the water content, a hypsochromic shift was observed that resulted from H-type aggregation. Furthermore, geometry and electronic configurations of PTZTID were studied at density functional theory /B3LYP level and indicated that the compound had a nonplanar (butterfly structure).

Nuclear Magnetic Resonance T1–T2 Spectra in Heavy Oil Reservoirs

Low-field nuclear magnetic resonance (NMR) has been widely used in the petroleum industry for reservoir evaluation. Fluid properties and petrophysical parameters can be determined from NMR spectra, obtained from processing echo data measured from the NMR tool. The more accurate NMR spectra are, the higher the reliability of reservoir evaluation based on NMR logging is. The purpose of this paper is to obtain more precise T1–T2 spectra in heavy oil reservoirs, with focus on the T1–T2 data acquisition and inversion. To this end, four inversion algorithms were tested on synthetic T1–T2 data, their precision was evaluated and the optimal inversion algorithm was selected. Then, the sensitivity to various acquisition parameters (wait time and echo spacing) was evaluated with T1–T2 experiments using a disordered accumulation of glass beads with a diameter of 45 μm saturated with heavy oil and distilled water. Finally, the sensitivity to various inversion parameters (convergence tolerance, maximum number of iterations and regularization parameter) was evaluated using the optimal inversion algorithm. The results showed that the inverted T1–T2 spectra loss some relaxation information when the number of echo train is less than 7. The peak of the heavy oil signal gradually moves along the direction of increase in the T2 and the intensity of the heavy oil signal gradually decreases with increasing echo spacing. The echo spacing should be as small as possible for T1–T2 measurements in heavy oil reservoirs on the premise that the NMR instrument operates normally. A convergence tolerance that is too large or a maximum number of iterations that is too small may result in exiting the iteration prematurely during the inversion. A convergence tolerance of 1 × 10−7 and a maximum number of iterations of 30,000 are recommended for the inversion of the T1–T2 spectra. An appropriate regularization parameter is an important factor for obtaining accurate T1–T2 spectra from the optimal inversion algorithm.

Recent Advancements and Applications of Logging and Surface Magnetic Resonance for Groundwater Investigations

Enhancing groundwater investigations, nuclear magnetic resonance (NMR) geophysics allows direct measurement of hydrogen in pore fluids and characterization of groundwater flow and storage parameters, including porosity, pore size, and permeability. In the field, NMR can be applied both downhole, with logging NMR tools, and non-invasively with surface NMR methods. We present recent technical advancements in logging and surface NMR, all of which are aimed to improve measurement flexibility, efficiency, and accuracy. These advancements include hardware development as well as adaptation of survey methodologies. We present applications of current logging and surface NMR technology from a range of international sites as part of practical groundwater investigations. Applications considered include characterization of the vadose zone, determination of aquifer hydrogeologic properties, detection of hydrocarbon contaminants, and imaging of thaw water in artic environments.

Recent Advances in NMR: Aggregation, Solvation, and Dynamics of Selected Organolithium Compounds

Nuclear magnetic resonance (NMR) spectroscopy is the most widely used analytical technique to study the structure and dynamics of organolithium compounds, which are the most popular reagents in organic synthesis due to their great diversity and high reactivity. The main strength of this method is that it allows direct analysis in solution of the aggregation, dynamic, and solvation state of reactive intermediates. In this review, we present the NMR tools (nD) involving the 6Li isotope and DOSY experiments with internal references and illustrate their contribution in the structural and dynamic characterization of organolithium compounds in solution through some selected example.1 Introduction2 Advantages of the 6Li isotope3 NMR Experiments Involving the 6Li Isotope4 Diffusion Ordered NMR Experiments5 Application of NMR to the Structural Characterization of Organolithium Species6 Conclusion