Ground Ice Estimation in Permafrost Samples using Industrial Computed Tomography and Multi-Sensor Core Logging

Strategic Insights -

Recent research has made significant strides in understanding the properties of ground ice in permafrost landscapes. A study led by University of Alberta researchers has utilized industrial computed tomography (CT) and multi-sensor core logging to non-destructively characterize five permafrost samples. The results demonstrate strong agreement between traditional destructive analyses and recent developments using a multi-sensor core logger, offering promising solutions for improving permafrost characterization and prediction of thaw subsidence.

Key Takeaways:

  • Researchers from the University of Alberta have developed a non-destructive method using industrial CT and multi-sensor core logging to characterize permafrost samples.
  • The method allows for the visualization of cryostructures, measurement of frozen bulk density, and estimation of volumetric and excess ice contents without damaging the samples.
  • The results show strong agreement between traditional destructive analyses and the new non-destructive approaches, with RMSEs for density, volumetric ice, and excess ice contents ranging from 0.08 g cm³ to 0.12 g cm³.
  • The study highlights the potential of developing standardized and interoperable methods for permafrost characterization, which can lead to more robust permafrost datasets and improved understanding of future thaw trajectories.
  • The research is supported by the Canadian Network For Research And Innovation in Machining Technology and the Natural Sciences And Engineering Research Council of Canada.
  • Additional authors for the study include J. Pumple, J. Harvey, and D. Froese.

Statistics:

  • RMSE for density, volumetric ice, and excess ice contents range from 0.08 g cm³ to 0.12 g cm³ for the new non-destructive approaches.
  • The study utilized five permafrost samples for characterization.
  • The research suggests that non-destructive methods can provide consistent results and improve digital permafrost datasets.
  • The study's findings highlight the importance of robust permafrost datasets for predicting future thaw trajectories.

Sources:

  • Ground ice estimation in permafrost samples using industrial computed tomography and multi-sensor core logging and comparison to destructive measurements. The Cryosphere, 2025,19():4259-4275. (The Cryosphere - http://www.the-cryosphere.net/).
  • NewsRx. University of Alberta Researchers Add New Findings in the Area of Imaging Technology (Ground ice estimation in permafrost samples using industrial computed tomography and multi-sensor core logging and comparison to destructive measurements). Journal of Engineering. October 20, 2025; p 4587.