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

Journal of Magnetic Resonance
By: , and 

Links

Abstract

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 type Article
Publication Subtype Journal Article
Title Simultaneous Gaussian and exponential inversion for improved analysis of shales by NMR relaxometry
Series title Journal of Magnetic Resonance
DOI 10.1016/j.jmr.2014.10.015
Volume 250
Year Published 2014
Language English
Publisher Academic Press
Publisher location San Diego, CA
Contributing office(s) Central Energy Resources Science Center
Description 10 p.
First page 7
Last page 16
Online Only (Y/N) N
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details