Research Project


Laboratory and Numerical Studies of the NMR Response of Near-Surface Materials


The Problem

Surface and logging NMR can be used to obtain information about pore-scale properties that govern the storage and flow of water. Of specific interest in our research are the NMR relaxation time, which can be measured with logging and surface NMR, and the diffusion coefficient of the pore water which can be measured with logging NMR. These two parameters are related to the surface-area-to-volume ratio of the pore space, an estimate of which can be used to determine permeability or hydraulic conductivity. Questions remain, however, about the interpretation of these NMR measurements in unconsolidated or weakly consolidated aquifer materials.

Our Approach

We investigate the NMR response of materials through numerical modeling and laboratory experiments. Numerical modeling is conducted on grain packs where the physical and chemical parameters are easily assigned and we are able to simulate the NMR measurement. Laboratory measurements are made on well-characterized samples where we can control and/or determine the relevant physical and chemical properties. In the laboratory, by varying the amount of iron coating on the surface of the samples, we are able to vary the strength of the surface relaxation parameter, which controls the link between NMR relaxation measurements and permeability/hydraulic conductivity. We are also analyzing samples from a variety of near-surface sites to understand the natural variability in surface relaxivity and its influence on the NMR measurements. Samples with a range of magnetic grain content are being used to explore the effect of internal magnetic field gradients on NMR diffusion measurements.

It is commonly assumed, in the interpretation of NMR relaxation data, that one pore space is sampled in the time-scale of the experiment.

Project Lead/Contact

Emily Fay, Katherine Dlubac, Rosemary Knight

Project Collaborators

Elliot Grunewald (Vista Clara, Inc.), David Walsh (Vista Clara, Inc.), Kristina Keating (Rutgers University)

Project Products

Project Sponsors

National Science Foundation, Grant Opportunities for Academic Liaison with Industry (GOALI)
Department of Energy, Small Business Innovation Research (SBIR)