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. The capability of nuclear magnetic resonance (NMR)relaxometry to characterise hydraulic properties of iron-oxide-coated sandand gravel was evaluated in a laboratory study. Past studies have shown thatthe presence of paramagnetic iron oxides and large pores incoarse sand and gravel disturbs the otherwise linear relationship betweenrelaxation time and pore size. Consequently, the commonly applied empiricalapproaches fail when deriving hydraulic quantities from NMR parameters.Recent research demonstrates that higher relaxation modes must be taken intoaccount to relate the size of a large pore to its NMR relaxation behaviourin the presence of significant paramagnetic impurities at its pore wall. Weperformed NMR relaxation experiments with water-saturated natural andreworked sands and gravels, coated with natural and synthetic ferric oxides(goethite, ferrihydrite), and show that the impact of the higher relaxationmodes increases significantly with increasing iron content. Since theinvestigated materials exhibit narrow pore size distributions, and can thusbe described by a virtual bundle of capillaries with identical apparent poreradius, recently presented inversion approaches allow for estimation of aunique solution yielding the apparent capillary radius from the NMR data. Wefound the NMR-based apparent radii to correspond well to the effectivehydraulic radii estimated from the grain size distributions of the samplesfor the entire range of observed iron contents. Consequently, they can beused to estimate the hydraulic conductivity using the well-knownKozeny–Carman equation without any calibration that is otherwise necessarywhen predicting hydraulic conductivities from NMR data. Our future researchwill focus on the development of relaxation time models that consider pore size distributions. Furthermore, we plan to establish ameasurement system based on borehole NMR for localising iron clogging andcontrolling its remediation in the gravel pack of groundwater wells.

Hydraulic characterisation of iron-oxide-coated sand and gravel based on nuclear magnetic resonance relaxation mode analyses