SCLRAD: Semi-supervised contrastive learning using random replacement of adjacent depths for lithology identification

• Published in: Journal of applied geophysics Vol. 241; p. 105795
• Main Authors: Zhao, Fengda, Zhai, Haobing, Zhou, Zihan, Zhang, Pengwei, Li, Xianshan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2025
• Subjects: Contrastive learning; Lithological identification; Sample pairs; Semi-supervised; Lithological identification; Sample pairs; Contrastive learning; Semi-supervised

Lithological identification is significant in logging interpretation work, as it is the foundation for evaluating reservoirs and describing reservoirs and basins. In lithological identification, due to the difficulty in obtaining lithological data and the high cost of labeling, there is often a situ...