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

Area of Science:

• Geophysics
• Petroleum Geoscience
• Materials Science

Background:

• Nuclear magnetic resonance (NMR) relaxometry is crucial for estimating porosity and pore size in petroleum exploration, primarily using fluid-phase signals.
• Shale samples present challenges due to significant hydrogen content from both solid and fluid signals, complicating standard NMR analysis.
• Traditional inverse Laplace transform methods struggle with Gaussian decay components in NMR data, leading to inaccurate porosity and relaxation time estimations.

Purpose of the Study:

• To develop and validate a novel simultaneous Gaussian-Exponential (SGE) inversion method for NMR relaxometry data analysis in shales.
• To address the limitations of the inverse Laplace transform in accurately characterizing complex NMR signals from shales.
• To improve the physical realism and consistency of NMR-derived parameters, such as porosity and pore-size distribution.

Main Methods:

• Application of a new simultaneous Gaussian-Exponential (SGE) inversion technique to analyze NMR relaxometry data.
• Testing the SGE method using both simulated NMR data and experimental measurements from diverse oil shale samples.
• Comparison of SGE inversion results against the conventional inverse Laplace transform method.

Main Results:

• The SGE inversion method yielded more physically realistic results compared to the inverse Laplace transform for shale samples.
• SGE inversion demonstrated more consistent relaxation behavior, particularly at high magnetic field strengths.
• Lower residuals and mitigation of signal overcall at short T2 times were observed with the SGE method.

Conclusions:

• The simultaneous Gaussian-Exponential (SGE) inversion is a superior method for analyzing NMR relaxometry data in shales, offering improved accuracy and reliability.
• This advanced method overcomes the limitations of traditional inverse Laplace transforms, providing more trustworthy porosity and pore-size estimations.
• The SGE technique has broader applicability in fields beyond geology, including material, medical, and food sciences, wherever mixed Gaussian and exponential decays occur.