Comparison of methods to segment variable-contrast xct images of methane-bearing sand using u-nets trained on single dataset sub-volumes

HIGHLIGHTS

• who: Fernando J. Alvarez-Borges and collaborators from the Faculty of Engineering and Physical Sciences, University of Southampton, Southampton , BJ, UK have published the research: Comparison of Methods to Segment Variable-Contrast XCT Images of Methane-Bearing Sand Using U-Nets Trained on Single Dataset Sub-Volumes, in the Journal: Methane 2023, 1, FOR PEER REVIEW of /2023/
• what: In this paper an investigation is carried out a class of Convolutional Neural Network to synchrotron images of CH4 -bearing sand during hydrate formation and extract porosity and CH4 gas saturation. The aim of this investigation . . .
  

   

  

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