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Related Experiment Video

Updated: May 21, 2026

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Published on: October 21, 2018

Two-dimensional T2 distribution mapping in rock core plugs with optimal k-space sampling.

Dan Xiao¹, Bruce J Balcom

¹MRI Research Center, Department of Physics, University of New Brunswick, 8 Bailey Drive, Fredericton NB, Canada E3B 5A3. d.x@unb.ca

Journal of Magnetic Resonance (San Diego, Calif. : 1997)

|June 12, 2012

Summary

This study introduces efficient 2D T(2) mapping for fluid-saturated rock core plugs using undersampled k-space imaging. New sampling patterns significantly reduce acquisition time while maintaining high image quality for pore property analysis.

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Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Published on: February 25, 2015

Area of Science:

Geophysics
Materials Science
Nuclear Magnetic Resonance (NMR) Imaging

Background:

1D T(2) distribution mapping is established, but 2D extension is time-prohibitive.
2D T(2) mapping is crucial for rock core plugs due to anisotropic pore properties.
Existing methods face challenges in acquiring detailed 2D pore information efficiently.

Purpose of the Study:

To develop and validate efficient 2D T(2) mapping techniques for fluid-saturated rock core plugs.
To reduce the significant acquisition time associated with 2D T(2) mapping.
To enable detailed analysis of pore properties influenced by rock structures.

Main Methods:

Development of novel k-space sampling patterns for reduced data acquisition.
Application of undersampling techniques (acquiring 22.2% and 11.7% of k-space data).
Utilizing companion density images with keyhole imaging and compressed sensing for reconstruction.
Pixel-wise T(2) distribution extraction using inverse Laplace transform.

Main Results:

Novel k-space sampling patterns significantly reduce acquisition time for 2D T(2) mapping.
High-quality T(2) distribution maps were successfully reconstructed from undersampled data.
Compressed sensing reconstruction yielded comparable results to full k-space acquisition with similar acceleration factors.
The method effectively captures T(2) variations related to rock bedding planes.

Conclusions:

Restricted k-space sampling is a viable and efficient strategy for 2D T(2) mapping in rock core analysis.
The developed technique overcomes the time limitations of traditional 2D imaging for this application.
This approach enhances the ability to characterize complex pore structures in geological samples using NMR.