Machine learning for locating organic matter and pores in scanning electron microscopy images of organic-rich shales
Abstract
null null For purposes of locating kerogen/organic matter and pores in SEM images of shale samples, we tested an automated SEM-image segmentation workflow involving feature extraction followed by machine learning. The proposed segmentation workflow is an alternative to threshold-based and object-based segmentation. For each pixel in the SEM image, sixteen features are generated and then fed to a random forest classifier to determine the presence...
Paper Details
Title
Machine learning for locating organic matter and pores in scanning electron microscopy images of organic-rich shales
Published Date
Oct 1, 2019
Journal
Volume
253
Pages
662 - 676
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