Motional relativity and industrial NMR sensors

Real-time oil-saturation monitoring in rock cores with low-field NMR

Nuclear magnetic resonance (NMR) provides a powerful suite of tools for studying oil in reservoir core plugs at the laboratory scale. Low-field magnets are preferred for well-log calibration and to minimize magnetic-susceptibility-induced internal gradients in the porous medium. We demonstrate that careful data processing, combined with prior knowledge of the sample properties, enables real-time acquisition and interpretation of saturation state (relative amount of oil and water in the pores of a rock). Robust discrimination of oil and brine is achieved with diffusion weighting. We use this real-time analysis to monitor the forced displacement of oil from porous materials (sintered glass beads and sandstones) and to generate capillary desaturation curves. The real-time output enables in situ modification of the flood protocol and accurate control of the saturation state prior to the acquisition of standard NMR core analysis data, such as diffusion-relaxation correlations. Although applications to oil recovery and core analysis are demonstrated, the implementation highlights the general practicality of low-field NMR as an inline sensor for real-time industrial process control.

Determining object boundaries from MR images with sub-pixel resolution: towards in-line inspection with a mobile tomograph

This work evaluates the performance of edge-detection algorithms to determine the sample geometry with high spatial accuracy from low-resolution MR images. In particular, we show that by applying such numerical methods it is possible to reconstruct the internal and external contours of the object with a spatial precision that surpasses the nominal spatial resolution of the image by more than one order of magnitude. Special attention is paid to find the spatial resolution and signal-to-noise ratio required by the described numerical methodology to achieve a desired spatial accuracy. Finally, we discuss the potential application of this image processing approach for in-line quality control of extruded rubber materials, where micrometer spatial precision has to be achieved from images measured in short experimental times. The results presented here prove that the sensitivity of mobile MRI sensors is enough to achieve the spatial accuracy required to proof check the production of extruded rubber fittings in acceptable experimental times.