• Corpus ID: 235435771

Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset

@article{Henriques2021GeneratingDA,
  title={Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset},
  author={Luis Felipe M.O. Henriques and S{\'e}rgio Colcher and Ruy Luiz Milidi'u and Andr{\'e} Bulc{\~a}o and Pablo Barros},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.08269}
}
Nowadays, subsurface salt body localization and delineation, also called semantic segmentation of salt bodies, are among the most challenging geophysicist tasks. Thus, identifying large salt bodies is notoriously tricky and is crucial for identifying hydrocarbon reservoirs and drill path planning. While several successful attempts to apply Deep Neural Networks (DNNs) have been made in the field, the need for a huge amount of labeled data and the associated costs of manual annotations by experts… 

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References

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TLDR
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