Corpus ID: 204907055

Attenuating Random Noise in Seismic Data by a Deep Learning Approach

@article{Zhao2019AttenuatingRN,
  title={Attenuating Random Noise in Seismic Data by a Deep Learning Approach},
  author={Xing Zhao and Ping Lu and Yanyan Zhang and Jianxiong Chen and Xiaoyang Rebecca Li},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.12800}
}
In the geophysical field, seismic noise attenuation has been considered as a critical and long-standing problem, especially for the pre-stack data processing. Here, we propose a model to leverage the deep-learning model for this task. Rather than directly applying an existing de-noising model from ordinary images to the seismic data, we have designed a particular deep-learning model, based on residual neural networks. It is named as N2N-Seismic, which has a strong ability to recover the seismic… Expand

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