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March 3, 2026
Swin-UNETR: A transformer-based model for 3D pore network segmentation in low-permeability sedimentary rocks
MS
Mengdi Sun
Sinopec (China)
QY
Qamar Yasin
ED
Eshimiakhe Daniel
Northeast Petroleum University
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Puntos clave
The new model achieves superior 3D segmentation accuracy for pore networks, enhancing understanding of sedimentary rock structures.
A key improvement is seen with a segmentation accuracy of 92% compared to traditional methods in low-permeability rocks.
Assessment using a transformer-based model shows its effectiveness in recovering complex pore structures better than older techniques.
The findings highlight the model's relevance for geological studies, suggesting further exploration in real-world sedimentary formations.
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Sun et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75c68c6e9836116a2544f
https://doi.org/https://doi.org/10.1016/j.coal.2026.104951
Swin-UNETR: Un modelo basado en transformadores para la segmentación de redes de poros en 3D en rocas sedimentarias de baja permeabilidad | Synapse