MRSmatlab is a manufacturer-independent software tool for processing, modeling, and inversion of surface nuclear magnetic resonance data. Intended as an open platform, MRSmatlab has been growing over the past few years by connecting researchers and making the latest research available to the community. We have developed insights into yet unpublished numerical implementations of signal processing and complex inversion. In addition, we have evaluated a field example demonstrating the need to carefully inspect all the steps of handling surface nuclear magnetic resonance data. MRSmatlab can be obtained by contacting the authors.
Under favorable conditions, the surface nuclear-magnetic-resonance (NMR) technique can provide direct quantitative estimates of subsurface water variations and indirect information on pore size and hydraulic conductivity. The technique is based on various exponential relaxation processes that become measurable after the intrinsic spin magnetic moments of groundwater protons have been rotated out of equilibrium by a pulse of alternating electromagnetic (EM) field generated at the surface. An implicit assumption in previous surface NMR studies is that relaxation processes need to be considered only after the EM pulse has been extinguished. Although this approximation is valid for short EM pulses, neglecting relaxation during the pulse (RDP) can result in significant errors for the generally long pulses used in surface NMR investigations. Because the influence of RDP cannot be isolated and quantified using field-scale approaches, this study is based on sample-scale NMR experiments and numerical simulations (Bloch equations) that mimic field practices and conditions. The results demonstrate that standard surface NMR methods that ignore the effects of RDP may yield significantly erroneous estimates of water volume (RDP-related errors of 25% are possible) and the key relaxation parameter (RDP-related errors of 50% are possible) that supplies information on pore size and hydraulic conductivity. Fortunately, the study also demonstrates that relatively simple interpretational approaches can reduce the RDP-related errors to less than 2%.
[1] A talik is a layer or body of unfrozen ground that occurs in permafrost due to an anomaly in thermal, hydrological, or hydrochemical conditions. Information about talik geometry is important for understanding regional surface water and groundwater interactions as well as sublacustrine methane production in thermokarst lakes. Due to the direct measurement of unfrozen water content, surface nuclear magnetic resonance (NMR) is a promising geophysical method for noninvasively estimating talik dimensions. We made surface NMR measurements on thermokarst lakes and terrestrial permafrost near Fairbanks, Alaska, and confirmed our results using limited direct measurements. At an 8 m deep lake, we observed thaw bulb at least 22 m below the surface; at a 1.4 m deep lake, we detected a talik extending between 5 and 6 m below the surface. Our study demonstrates the value that surface NMR may have in the cryosphere for studies of thermokarst lake hydrology and their related role in the carbon cycle. Citation: Parsekian, A.
Surface nuclear magnetic resonance (NMR) is a noninvasive geophysical tool used to investigate groundwater reservoirs. The relevant physical process in surface NMR is the nuclear spin of hydrogen protons in liquid water. Standard single-pulse surface NMR experiments provide estimates of water content in the shallow subsurface. Under favorable conditions, pore-structure and even hydraulic-conductivity information can be extracted from double-pulse surface NMR data. One crucial issue in surface NMR experiments is the resonance condition: the frequency of the excitation field should closely match the Larmor frequency of the protons, which is controlled by the local magnitude of the earth’s magnetic field. Although the earth’s field can be measured accurately by an on-site magnetometer, several effects impede perfect matching of the frequencies. These include temporal variations of the earth’s field, instrumental imperfections, and the magnetic susceptibility of the underlying rocks. We assess the impact of violating the resonance condition on surface NMR experiments. Our investigation involves numerical simulations and measurements using a sample-scale earth-field NMR device and a surface NMR acquisition system. For frequency offsets up to 5 Hz, we find that relatively standard single-pulse surface NMR recording procedures are likely to produce reliable water-content estimates as long as the pulse moments are small to moderate or the aquifer is relatively deep. If strong pulse moments are required or shallow aquifers are probed, off-resonance conditions can lead to anomalous increases in recorded amplitudes that can be mistakenly interpreted in terms of deepwater occurrences. Double-pulse surface NMR experiments are particularly sensitive to off-resonance effects, such that the results may be highly biased even for the small-frequency offsets commonly encountered in field situations.
With the changing precipitation patterns and melting of mountain glaciers and permafrost that result from global warming, information on the distribution of groundwater in mountainous terrains is becoming increasingly important for developing prudent resource and hazard management strategies. Obtaining this information across topographically craggy and variably frozen ground in a cost-effective and nonintrusive manner is challenging. We introduce a modified 2D surface nuclear magnetic resonance (NMR) tomographic technique that allows us to account for substantial variations in surface topography in locating and quantifying groundwater occurrences in rugged mountains. Because contact with the ground is not necessary, it is a rare geophysical technique not affected by sensor-to-ground coupling problems common in high mountain environments. To demonstrate the efficacy of the tomographic imaging scheme, we invert a large multioffset surface NMR data set collected across a partially ice-cored proglacial terminal moraine in the Canadian Rocky Mountains. Our preferred model contains a 2- to 5-m-thick water layer, the top of which has practically the same elevation as the surface of a nearby lake and the bottom of which coincides with bedrock resolved in companion seismic and ground-penetrating radar studies.
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