Evaluation of surface nuclear magnetic resonance-estimated subsurface water content

Details Evaluation of surface nuclear magnetic resonance-estimated subsurface water content Evaluation of surface nuclear magnetic resonance-estimated subsurface water content

Sep 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011njph...13i5002m&link_type=abstract

New Journal of Physics, Volume 13, Issue 9, pp. 095002 (2011).

Physics

1

Scientific paper

The technique of nuclear magnetic resonance (NMR) has found widespread use in geophysical applications for determining rock properties (e.g. porosity and permeability) and state variables (e.g. water content) or to distinguish between oil and water. NMR measurements are most commonly made in the laboratory and in boreholes. The technique of surface NMR (or magnetic resonance sounding (MRS)) also takes advantage of the NMR phenomenon, but by measuring subsurface rock properties from the surface using large coils of some tens of meters and reaching depths as much as 150 m. We give here a brief review of the current state of the art of forward modeling and inversion techniques.
In laboratory NMR a calibration is used to convert measured signal amplitudes into water content. Surface NMR-measured amplitudes cannot be converted by a simple calibration. The water content is derived by comparing a measured amplitude with an amplitude calculated for a given subsurface water content model as input for a forward modeling that must account for all relevant physics.
A convenient option to check whether the measured signals are reliable or the forward modeling accounts for all effects is to make measurements in a well-defined environment. Therefore, measurements on top of a frozen lake were made with the latest-generation surface NMR instruments. We found the measured amplitudes to be in agreement with the calculated amplitudes for a model of 100 % water content. Assuming then both the forward modeling and the measurement to be correct, the uncertainty of the model is calculated with only a few per cent based on the measurement uncertainty.

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