StorSeismic: An approach to pre-train a neural network to store seismic data features

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Deep Learningstorseismic
Overview

StorSeismic: An approach to pre-train a neural network to store seismic data features

This repository contains codes and resources to reproduce experiments of StorSeismic in Harsuko and Alkhalifah, 2020.

Instruction

No Notebook name Description
1 nb0_1_data_prep_pretrain.ipynb Create pre-training data
2 nb0_2_data_prep_finetune.ipynb Create fine-tuning data
3 nb1_pretraining.ipynb Pre-training of StorSeismic
4 nb2_1_finetuning_denoising.ipynb Example of fine-tuning task: denoising
5 nb2_2_finetuning_velpred.ipynb Example of fine-tuning task: velocity estimation

References

Harsuko, R., & Alkhalifah, T. (2022). StorSeismic: A new paradigm in deep learning for seismic processing. ArXiv, abs/2205.00222.

Citation

Citations are very welcomed. This work can be cited using:

@article{Harsuko2022StorSeismicAN,
  title={StorSeismic: A new paradigm in deep learning for seismic processing},
  author={Randy Harsuko and Tariq Alkhalifah},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.00222}
}
Owner
Seismic Wave Analysis Group
Seismic Wave Analysis Group
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