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.

The pore-size distribution (PSD) of geologic materials is an important rock parameter to understand the flow of water in the subsurface. PSDs can be obtained from sieving analyses, mercury porosimetry measurements, and imaging techniques, but none of these methods is available for in situ measurements. Nuclear magnetic resonance (NMR) measurements are controlled by rock parameters such as the surface-area to porevolume ratio. NMR is available for in situ measurements. State-of-the-art NMR relaxation time measurements need a calibration of the surface relaxivity ρ to extract pore-size information. State-of-the-art NMR diffusion measurements avoid the calibration of ρ but are limited to small pores. We developed an approach that estimates the average pore size without calibrating ρ by means of incorporating higher order modes into the signal interpretation of NMR relaxation times. We conducted forward-modeling studies using an analytic solution for cylindrical tubes, 2D finite-element simulations to incorporate fractal pore spaces, and laboratory experiments on synthetic and natural samples. Our experimental data indicated that relaxation can occur outside the fast-diffusion regime not only for coarse-grained materials, but also for fine-to medium-grained unconsolidated sandy materials due to high surface relaxivities. We found that the rock-fluid interface's roughness had a significant impact on the diffusion regime and led to an apparent increase in ρ, which may cause intermediate or slow diffusion. The methodology was limited to materials with a narrow PSD and uniform distribution of ρ because we assumed multiexponential decay due to diffusion in single isolated pores.

Surface nuclear magnetic resonance (NMR) is a noninvasive geophysical method that is primarily used in hydrological investigations of shallow aquifers. An important parameter in surface-NMR experiments is the relaxation time T1. Information on pore structure and even hydraulic permeability/conductivity may be inferred from accurate estimates of this parameter. Estimates of T1 are usually obtained by evaluating the spin response of groundwater molecules to excitation by two sequential electromagnetic pulses, the second of which is delayed and phase-shifted by π relative to the first. We have discovered that variations of the excitation field with distance from the transmitter and common imperfections in the transmitted pulses introduce considerable bias in estimates of T1 (e.g., errors as large as 50%). We assess the significance of these problems via numerical simulations based on the Bloch equation. As a result of this assessment, we propose a novel yet simple modification to the T1 acquisition method that resolves the identified problems. Our new scheme involves applying two types of double-pulse sequence, one in which the second pulse is phase-shifted by π relative to the first (i.e., the current procedure) and one in which the second pulse is in phase with the first. Subtracting the voltage responses measured after each of the two double-pulse experiments eliminates the bias, thus allowing T1 to be reliably estimated under general surface-NMR conditions.

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