Geobody {Extraction} from {Seismic} {Horizons} {Using} {SAM}: a {Novel} {Image} {Segmentation} {Technique}

@inproceedings{razza_geobody_RM2024,
 abstract = {This paper introduces a novel approach aimed at extracting geobodies from seismic horizons using advanced image segmentation techniques. The Segment Anything Model (SAM) of Meta, a deep learning model trained on diverse non-seismic images, is used to identify geological features like channels within horizons. A comparative analysis is conducted against waveform classification, another widely used facies classification tool.},
 author = {Razza, Julien and Abdallah, Hussein},
 booktitle = {Proc. 2024 RING Meeting},
 language = {en},
 pages = {5},
 publisher = {ASGA},
 title = {Geobody {Extraction} from {Seismic} {Horizons} {Using} {SAM}: a {Novel} {Image} {Segmentation} {Technique}},
 year = {2024}
}