An open-source Matlab code package for improved rank-reduction 3D seismic data denoising and reconstruction Y Chen, W Huang, D Zhang, W Chen Computers & Geosciences 95, 59-66, 2016 | 138 | 2016 |
Empirical low-rank approximation for seismic noise attenuation Y Chen, Y Zhou, W Chen, S Zu, W Huang, D Zhang IEEE Transactions on Geoscience and Remote Sensing 55 (8), 4696-4711, 2017 | 134 | 2017 |
Deep learning reservoir porosity prediction based on multilayer long short-term memory network W Chen, L Yang, B Zha, M Zhang, Y Chen Geophysics 85 (4), WA213-WA225, 2020 | 125 | 2020 |
Data-driven multitask sparse dictionary learning for noise attenuation of 3D seismic data MA Nazari Siahsar, S Gholtashi, AR Kahoo, W Chen, Y Chen Geophysics 82 (6), V385-V396, 2017 | 125 | 2017 |
Improving the signal‐to‐noise ratio of seismological datasets by unsupervised machine learning Y Chen, M Zhang, M Bai, W Chen Seismological Research Letters 90 (4), 1552-1564, 2019 | 108 | 2019 |
Multiple-reflection noise attenuation using adaptive randomized-order empirical mode decomposition W Chen, J Xie, S Zu, S Gan, Y Chen IEEE Geoscience and Remote Sensing Letters 14 (1), 18-22, 2016 | 100 | 2016 |
Simultaneous denoising and interpolation of 3-D seismic data via damped data-driven optimal singular value shrinkage MAN Siahsar, S Gholtashi, EO Torshizi, W Chen, Y Chen IEEE Geoscience and Remote Sensing Letters 14 (7), 1086-1090, 2017 | 92 | 2017 |
Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data D Zhang, Y Zhou, H Chen, W Chen, S Zu, Y Chen Geophysics 82 (5), V351-V367, 2017 | 89 | 2017 |
Recent advancements in empirical wavelet transform and its applications W Liu, W Chen IEEE Access 7, 103770-103780, 2019 | 79 | 2019 |
Unsupervised 3-D random noise attenuation using deep skip autoencoder L Yang, S Wang, X Chen, OM Saad, W Chen, YASI Oboue, Y Chen IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2021 | 73 | 2021 |
Deep learning seismic random noise attenuation via improved residual convolutional neural network L Yang, W Chen, H Wang, Y Chen IEEE Transactions on Geoscience and Remote Sensing 59 (9), 7968-7981, 2021 | 64 | 2021 |
Random noise attenuation based on residual convolutional neural network in seismic datasets L Yang, W Chen, W Liu, B Zha, L Zhu Ieee Access 8, 30271-30286, 2020 | 64 | 2020 |
Automatic noise attenuation based on clustering and empirical wavelet transform W Chen, H Song Journal of Applied Geophysics 159, 649-665, 2018 | 62 | 2018 |
Ground roll attenuation using improved complete ensemble empirical mode decomposition W Chen, Y Chen, W Liu Journal of Seismic Exploration 25 (5), 485-495, 2016 | 60 | 2016 |
Application of principal component analysis in weighted stacking of seismic data J Xie, W Chen, D Zhang, S Zu, Y Chen IEEE Geoscience and Remote Sensing Letters 14 (8), 1213-1217, 2017 | 58 | 2017 |
Deep learning for regularly missing data reconstruction X Chai, G Tang, S Wang, R Peng, W Chen, J Li IEEE Transactions on Geoscience and Remote Sensing 58 (6), 4406-4423, 2020 | 57 | 2020 |
Fast dictionary learning for high-dimensional seismic reconstruction H Wang, W Chen, Q Zhang, X Liu, S Zu, Y Chen IEEE Transactions on Geoscience and Remote Sensing 59 (8), 7098-7108, 2020 | 47 | 2020 |
Permeability prediction of isolated channel sands using machine learning G Zhang, Z Wang, H Li, Y Sun, Q Zhang, W Chen Journal of Applied Geophysics 159, 605-615, 2018 | 47 | 2018 |
Random noise reduction using a hybrid method based on ensemble empirical mode decomposition W Chen, D Zhang, Y Chen J. Seismic Explor 26 (3), 227-249, 2017 | 47 | 2017 |
A structural rank reduction operator for removing artifacts in least-squares reverse time migration M Bai, J Wu, S Zu, W Chen Computers & Geosciences 117, 9-20, 2018 | 40 | 2018 |