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Simultaneous Gaussian and exponential inversion for improved analysis of shales by NMR relaxometry

December 1, 2014

Nuclear magnetic resonance (NMR) relaxometry is commonly used to provide lithology-independent porosity and pore-size estimates for petroleum resource evaluation based on fluid-phase signals. However in shales, substantial hydrogen content is associated with solid and fluid signals and both may be detected. Depending on the motional regime, the signal from the solids may be best described using either exponential or Gaussian decay functions. When the inverse Laplace transform, the standard method for analysis of NMR relaxometry results, is applied to data containing Gaussian decays, this can lead to physically unrealistic responses such as signal or porosity overcall and relaxation times that are too short to be determined using the applied instrument settings. We apply a new simultaneous Gaussian-Exponential (SGE) inversion method to simulated data and measured results obtained on a variety of oil shale samples. The SGE inversion produces more physically realistic results than the inverse Laplace transform and displays more consistent relaxation behavior at high magnetic field strengths. Residuals for the SGE inversion are consistently lower than for the inverse Laplace method and signal overcall at short T2 times is mitigated. Beyond geological samples, the method can also be applied in other fields where the sample relaxation consists of both Gaussian and exponential decays, for example in material, medical and food sciences.

Publication Year 2014
Title Simultaneous Gaussian and exponential inversion for improved analysis of shales by NMR relaxometry
DOI 10.1016/j.jmr.2014.10.015
Authors Kathryn E. Washburn, Endre Anderssen, Sarah J. Vogt, Joseph D. Seymour, Justin E. Birdwell, Catherine M. Kirkland, Sarah L. Codd
Publication Type Article
Publication Subtype Journal Article
Series Title Journal of Magnetic Resonance
Index ID 70135048
Record Source USGS Publications Warehouse
USGS Organization Central Energy Resources Science Center