The Application of the Depth Residual Network Denoising Method in the Complex Mountainous Seismic Exploration

Author:

Qin Nan,Zeng Qingcai,Shou Hao,Hou Sian,Li Meng,Cui Dong

Publisher

Springer Nature Singapore

Reference11 articles.

1. Chen, W., Song, H.: Automatic noise attenuation based on clustering and empirical wavelet transform. J. Appl. Geophys. 159, 649–665 (2018)

2. Zhang, G., Wang, Z., Chen, Y.: Deep learning for seismic lithology prediction. Geophys. J. Int. 215(2), 1368–1387 (2018)

3. Liu, L.H., Lu, R., Yang, W.K.: Seismic lithofacies inversion based on deep learning. Geophys. Prospect. Petrol. 58(1), 123–129 (2019)

4. Xie, W., Li, Y., Jia, X.: Deep convolutional networks with residual learning for accurate spectral-spatial denoising. Neurocomputing 312, 372–381 (2018)

5. Zhou, H., Wu, R.S., Jiang, M., et al.: Dictionary learning based on dip patch selection training for random noise attenuation. Geophysics 1–105 (2019)

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