The prediction of hydraulic conductivity [Formula: see text] from nuclear magnetic resonance (NMR) measurements has been performed primarily in sandstones. In hydrogeological applications, however, unconsolidated material is more prevalent. Compared to sandstones, unconsolidated sediments can show pore sizes up to several millimeters. The known (semi-)empiric relations to estimate [Formula: see text] from NMR have been applied on this material, but the underlying assumptions are not valid for large pores. We formulated a new model, called the Kozeny-Godefroy model. It is based on capillary pores with a single pore radius, and accounts for bulk water relaxation and relaxation in porous media under fast- and slow-diffusion conditions. The bulk-water relaxation and slow-diffusion conditions significantly affect the NMR measurements on coarse material. If the impact of the bulk-water relaxation is well known and small, a maximum [Formula: see text] can be derived from NMR measurements by accounting for the slow-diffusion case. The model replaces the empirical factors in known relations with physical, structural, and intrinsic NMR parameters. Focusing the calibration on material-specific NMR parameters improves the prediction of [Formula: see text] for similar material. Measurements on well-sorted glass beads and natural sands with different grain sizes are used for evaluation. These measurements confirm the applicability of the new model and, for coarse material, show the limit of the fast-diffusion-based Seevers and Schlumberger-Doll-Research equations. The application of our model is limited to (1) simple pore geometries, and (2) materials with a small range of pore sizes.

The technique of magnetic resonance sounding (MRS) has shown several improvements in data processing, inversion and interpretation during the last years. Along with these improvements, detailed innovations on instrumentation have been demanded to support their use. Latest developments in surface nuclear magnetic resonance (NMR) instrumentation promise to fulfil these hardware requirements such as decreased dead time, improved digital signal detection, multi‐channel capabilities and improved reference techniques with the second generation surface NMR instruments. In this paper, we compare data from two generations of instruments and assess the impact of the improvements on practical issues, i.e., the increased accuracy of data due to shorter dead times and new noise reduction approaches and the feasibility for efficient 2D measuring schemes. Well‐known and documented test sites and synthetic considerations are used to evaluate these developments. First, the relaxation signals of different devices using the same loop match each other. The inversion results coincide within the range of data errors. Decay time estimation appears to be more stable for the new generation instrument. Second, the potential of shorter effective dead times (considering a relaxation of the protons during the pulse) is investigated using statistical analysis of synthetic data sets with different decay times and noise levels. The additionally measured data at early times significantly improve the scope and accuracy of the determined parameters initial amplitude and T2* time and thus extend the range of formations to be characterized. A field example comparing an effective dead time of 18 ms and 45 ms is presented. Two different reference techniques were successfully applied for noise cancellation at the very noisy test site Nauen. We observed an equivalent signal improvement using the software‐based and hardware‐based technique. However, software noise cancellation approaches are easily adaptable and extendable. Finally, considerations are given how to efficiently carry out 2D surveys using multi‐channel instruments. A 2D field data set using the GMR demonstrates that 2D surveys can already be realized in moderate measuring times. The new generation of instruments provides comparable results and improved capabilities that will enable surface NMR measurements to be applied in a wider range of applications.

No abstract

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.

SUMMARY Surface nuclear magnetic resonance (SNMR) is a well-established technique for the hydrogeological characterization of the subsurface up to depths of about 150 m. Recently, SNMR has been adapted to investigate also the shallow unsaturated zone with small surface loop setups. Due to the decreased volume, a pre-polarization (PP) field prior to the classical spin excitation is applied to enhance the measured response signal. Depending on the strength and orientation of the applied PP-field, the enhancement can often reach several orders of magnitude in the vicinity of the PP-loop. The theoretically achievable enhancement depends on the assumption of an adiabatic, that is perfect, switch-off of the corresponding PP-field. To study the effect of imperfect switch-off, we incorporate full spin dynamics simulations into the SNMR forward modelling. The affected subsurface volume strongly depends on the chosen PP switch-off ramp and the geometry of the loop setup. Due to the imperfect switch-off, the resulting SNMR sounding curves can have significantly decreased signal amplitudes. For comparison, the signal amplitudes of either a 1 ms exponential or linear switch-off ramp are reduced by 17 and 65 per cent, respectively. Disregarding this effect would therefore yield an underestimation of the corresponding subsurface water content of similar magnitude.

Development in instrumentation and data analysis of surface nuclear magnetic resonance has recently moved on from one-dimensional (1D) soundings to two-dimensional (2D) surveys, opening the method to a larger field of hydrological applications. Current analysis of 2D data sets, however, does not incorporate relaxation times and is therefore restricted to the water content distribution in the subsurface.We present a robust 2D inversion scheme, based on the qt approach, which jointly inverts for water content and relaxation time by taking the complete data set into account. The spatial distribution of relaxation time yields structural information of the subsurface and allows for additional petrophysical characterization. The presented scheme handles separated loop configurations for increased lateral resolution. Assuming a mono-exponential relaxation in each model cell, using irregular meshes, and gate-integrating the signal, the size of the inverse problem is significantly reduced and can be handled on a standard personal computer.A synthetic study shows that contrasts in both the quantities -water content and relaxation time -can be imaged. Inversion of a field data set outlines a buried glacial valley and allows the distinguishing of two aquifers with different grain sizes, which can be concisely interpreted together with a resistivity profile. The impact of the anisotropic weighting factor and subsurface resistivity on the inversion result are shown and discussed. A comparison of the results obtained by the previously used initial value and time-step inversion approaches illustrates the improved stability and resolution capabilities of the 2D qt inversion scheme. ferred to the field to estimate T 1 (Legchenko et al. 2004;Walbrecker et al. 2011b) or T 2 (Legchenko et al.

The noninvasive detection and characterization of subsurface aquifer structures demands geophysical techniques. Surface nuclear magnetic resonance (SNMR) is the only technique that is directly sensitive to hydrogen protons and, therefore, allows for unambiguous detection of subsurface water. Traditionally, SNMR utilizes large surface coils for both transmitting excitation pulses and recording the groundwater response. Recorded data are thus a voltage induced by the time derivative of the secondary magnetic field. For the first time, we demonstrate that the secondary magnetic field in a SNMR experiment can be directly detected using a superconducting quantum interference device magnetometer. Conducting measurements at a test site in Germany, we demonstrate not only the ability to detect SNMR signals on the order of femtoTesla but also we are able to satisfy the observed data by inverse modeling. This is expected to open up completely new applications for this exciting technology.

Geophysical methods can characterize aquifer systems non-invasively and are particularly helpful to image the complex depositional structure of the subsurface.Among these, ground-penetrating radar (GPR) is an effective tool for detailed investigations of shallow subsurface geometry, but provides only limited information on hydraulic properties.Magnetic resonance tomography (MRT) provides the parameters such as water content (porosity) and relaxation time/hydraulic conductivity, but suffers from resolution limits. Furthermore, it requires knowledge of subsurface electrical resistivity, which can be obtained by electrical resistivity tomography (ERT) also suffering from resolution limits.To overcome the limitations in resolution, we incorporate GPR reflectors as structural information into the ERT and MRT data inversion.We test the methodology on a synthetic example and show improved imaging properties compared to standard inversion, particularly at larger depth, where resolution is limited.We apply the methodology to a test site that is characterized by a complex depositional structure. The Quaternary deposits consist of interbedded meltwater deposits (aquifers) and till (aquitards), overlain by aeolian deposits. To image the subsurface depositional structure in 3D, a 200 m × 250 m area was surveyed by GPR.The use of GPR constraints clearly improves the resolution and zonation of the subsurface image which is validated by drill-core analyses. We suggest a workflow to combine GPR, MRT and ERT, leading the way to high-resolution hydrogeological models that can be used for groundwater studies.