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In this work, the aim is to assess the relative import ance of the impact of diffusional coupling on NMR measurements of saturated laminated sandstone numerically at the layer scale to assess the feasibility of NMR rock-typing approaches. We use two 3D model structures based on a Boolean particle process, providing a range of structural to diffusion length ratios to explore the relationships between pore geometry, surface magnetic properties, and NMR transverse relaxation time. The influence of surface relaxivity and bulk susceptibility contrast on T2 relaxation responses is tested for layered structures to improve the rock-typing methodology. An escalation in pore coupling is observed with decreasing bed thickness as well as decreasing bulk susceptibility contrast and surface relaxivity the latter ones reducing the time available for pore coupling by reducing the effective relaxation rate. When pore coupling is strong, the T2 distribution clearly misrepresents the underlying bimodal distribution of the different morphologies. Consequently, the bimodal relaxation time becomes merged and the relative amplitude of the peaks fails to reflect the true morphologies of the models. Furthermore, we observed that in low noise conditions of numerical simulation the effect of diffusional coupling on transverse relaxation may be misinterpreted for the regularization effect on ILT solution. In such cases, careful selection of Laplace inversion method is essential for effective rock-typing by NMR.

Monitoring the T1 relaxation of wetland clog matter has previously been identified as a gauge of its clogged state [1]. Magnetic resonance (MR) sensors explored in other work have typically been of a bore-whole configuration, which may not be ideal in a wetland environment where the sensitive volume of the sensor may become physically clogged and therefore inoperable. This work investigates two open-geometry sensor designs and a short study is presented to determine the suitability of the sensors for monitoring the clog state of wetlands. It was shown that a bar magnet geometry has a higher stray field than that of the four magnet surface sensor also presented, leading to a prohibitively short T2 eff. This means that the T1 values collected are notably shorter and not useful for distinguishing between clog state for the single magnet sensor. By contrast the four magnet surface sensor has a longer T2 eff, making it more suitable for T1 measurements; where T1= 915 ± 212 ms for a very thinly clogged sample, and T1= 127 ± 27 ms for a heavily clogged sample. This offers a clearly resolvable difference in the T1 values allowing the clogging state to be easily determined and making this sensor the desirable choice for long-term embedding.

Nuclear Magnetic Resonance (NMR) spectrometry has proved to be a good technique for determining the petrophysical properties of reservoir rocks; such as porosity and pore size distribution. We investigated how pore water rich in divalent ions affect the NMR signal from chalk with two different depositional textures. We compared two cases. The first experiments on outcrop chalk with high salinity brines showed that saturation with divalent ions (Mg2+, Ca2+ and SO4 2-) cause major shifts in the T2 distribution curve, probably due to precipitation in the pore space. In a second set of experiments, fluid samples where precipitation takes place were found to show shifts in the T2 relaxation curve due to the creation of crystals. We were able to identify how differences in the rock texture and precipitants within the pore space may affect the transverse relaxation time by altering the surface-to-volume ratio of the pore space. The results of this work could benefit the ongoing study on the optimization of the water composition for Enhanced Oil Recovery (EOR) methods and shed light on how it can affect the mechanical and physical properties of the rock.