Hydrogeological Parameter Estimation Using Low-Field Proton Nuclear Magnetic Resonance: Lessons from the Laboratory

Thursday, 18 December 2014: 2:50 PM
Kristina Keating, Sam Falzone, Gordon K Osterman and David Samuel Wallace, Rutgers University Newark, Newark, NJ, United States
Geophysical methods can provide a non-invasive method for estimating spatial variability in hydrogeological parameters such as water content, hydraulic conductivity, and matric potential. Proton nuclear magnetic resonance (NMR) is unique amongst geophysical methods in that it is directly sensitive to water, via the initial signal magnitude, and thus provides a robust estimate of water content. In addition, the NMR relaxation time is sensitive to pore geometry, allowing it to be used to predict the hydraulic conductivity and to determine water retention curves. While NMR measurements are considered a mature technology in the petroleum industry, the strength of NMR data for hydrogeophysical studies is still being realized. The major ongoing challenge is to generate a functional mapping of the relationship between pore geometry and relaxation time, while accounting for pore chemistry. In our research, we are developing and refining quantitative petrophysical models that relate NMR parameters to hydrogeological parameters.

Here we present laboratory measurements that highlight our recent successes in using NMR measurements to estimate several hydrogeological parameters and overcome the limitations of the standard petrophysical models. We examine these relationships by collecting NMR measurements on synthetic and geologic materials with carefully controlled or quantified pore properties, i.e., pore surface-area-to-volume ratio (S/V), pore size and surface iron concentration, and relate these variables to hydrogeological parameters including water content, hydraulic conductivity, and/or the water retention curve. Our major results include developing a relationship between the NMR relaxation times and water saturation across diverse chemical environments, and showing that for materials with rough surfaces, S/V, and not average pore diameter, is the relevant parameter in the interpretation of NMR data. Despite the many challenges in interpreting the measurements, valuable information about hydrogeological parameters can be obtained from NMR relaxation data, and we conclude by outlining pathways for improving the interpretation of NMR data for hydrogeophysical investigations.