A Comparative Study of Vision Transformer and Convolutional Neural Network Models in Geological Fault Detection

Geological fault detection is a critical aspect of geological exploitation and oil-gas exploration. The automation of fault detection can significantly reduce the dependence on expert labeling. Current prevailing methods often treat fault detection as a semantic segmentation task using the Convoluti...

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Detalles Bibliográficos

Principais autores:	Jing Wang, Siteng Ma, Yu An, Ruihai Dong
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2024-01-01
Series:	IEEE Access
Assuntos:	Convolutional neural network vision transformer fault detection seismic interpretation
Acceso en liña:	https://ieeexplore.ieee.org/document/10609386/
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