期刊论文（Journal Paper）
[76] Zhiguo Wang, Qiannan Wang, Yang Yang*, Naihao Liu, Yumin Chen, and Jinghuai Gao*, 2023, Seismic Facies Segmentation via A Segformer-based Specific Encoder-Decoder-Hypercolumns Scheme, IEEE Transactions on Geoscience and Remote Sensing, 61, 5903411, 1-11.
[75] Naihao Liu, Jingyu Wang, Yang Yang*, Zhen Li, and Jinghuai Gao, 2023, WVDNet: Time-frequency analysis via semi-supervised learning, IEEE Signal Processing Letters, 30, 22594779, 55-59.
[74] Haoran Zhang, Naihao Liu*, Zhiguo Wang, Yijie Zhang*, Jinghuai Gao, and Jianhua Wang, 2023, Sand Bodies Delineation by Fusing Multi-frequency Attributes via t-SNE, IEEE Geoscience and Remote Sensing Letters, 20, 7501205, 1-5.
[73] Hao Wu, Shizhen Li, and Naihao Liu*, 2023, Seismic interpolation via multi-scale HU-Net, Geoenergy Science and Engineering, 222, 211458, 1-10.
[72] Qian Wang*, Xuehua Yang, Bo Tang, Naihao Liu, Jinghuai Gao, 2023, Application of multi-synchrosqueezed generalized S-transform in seismic time-frequency analysis, Journal of Seismic Exploration, 32, 39-49.
[71] Yihuai Lou, Lukun Wu, Lin Liu, Kai Yu, Naihao Liu*, Zhiguo Wang*, and Wei Wang, 2022, Irregularly sampled seismic data interpolation via wavelet-based convolutional block attention deep learning, Artificial Intelligence in Geosciences, 3, 192-202.
[70] Rongchang Liu, Rui Guo*, Naihao Liu*, Guangya Zhu, Xingfang Liu, Chaozhong Ning, Ganlin Hua, 2022, Multi-frequency analysis via LTSA and its application on carbonate reservoir delineation, IEEE Geoscience and Remote Sensing Letters, 19, 7508205, 1-5.
[69] Naihao Liu, Yuxin Zhang, Youbo Lei, Yang Yang*, Zhiguo Wang*, Jinghuai Gao, and Xiudi Jiang, 2022, Seismic Sparse Time-frequency Network with Transfer Learning, IEEE Transactions on Geoscience and Remote Sensing, 60, 4513913, 1-13.
[68] Naihao Liu, Shengtao Wei, Rongchang Liu, Yang Yang*, Nan Zhang, and Jinghuai Gao*, 2022, Seismic Attenuation Estimation via Unscaled Time-frequency Representation and Divergence, IEEE Transactions on Geoscience and Remote Sensing, 60, 4513610, 1-10.
[67] Naihao Liu, Jiale Wang, Jinghuai Gao, Kai Yu, Yihuai Lou*, and Yitao Pu, Shaojie Chang*, 2022, NS2NS: Self-learning for Seismic Image Denoising, IEEE Transactions on Geoscience and Remote Sensing, 60, 5922311, 1-11. [code]
[66] Mingke Zhang, Jinghuai Gao*, Zhiguo Wang*, Yang Yang, Naihao Liu, and Qiansheng Wei, 2022, Q Estimation via the Discriminant Method based on Error Modeling, IEEE Transactions on Geoscience and Remote Sensing, 60, 5922811, 1-11.
[65] Hui Li, Bo Qiu, Yonghao Zhang, Baohai Wu, Yang Wang, Naihao Liu*, and Jinghuai Gao, 2022, CNN-based Network Application for Petrophysical Parameter Inversion: Sensitivity Analysis of Input-output Parameters and Network Architecture, IEEE Transactions on Geoscience and Remote Sensing, 60, 4513113, 1-13.
[64] Yang Yang, Youbo Lei, Naihao Liu*, Zhiguo Wang*, Jinghuai Gao, and Jicai Ding, 2022, SparseTFNet: A Physically Informed Autoencoder for Sparse Time-Frequency Analysis of Seismic Data, IEEE Transactions on Geoscience and Remote Sensing, 60, 4512812, 1-12.
[63] Naihao Liu, Jiale Wang, Jinghuai Gao, Shaojie Chang*, and Yihuai Lou*, 2022, Similarity-Informed Self-Learning Model and its Application on Seismic Image Denoising, IEEE Transactions on Geoscience and Remote Sensing, 60, 5921113, 1-13.
[62] Yihuai Lou, Shizhen Li, Naihao Liu*, and Rongchang Liu, 2022, Seismic volumetric dip estimation via a supervised deep learning model by integrating realistic synthetic data sets, Journal of Petroleum Science and Engineering, 218, 111021, 1-19.
[61] Naihao Liu, Zhuo Li, Jiamin Chen, Yuming Liu, Hao Wu*, Jinghuai Gao, and Xinmao Zhou, 2022, The Edge-guided FPN Model for Automatic Stratigraphic Correlation of Well Logs, Journal of Petroleum Science and Engineering, 218, 110985, 1-13.
[60] Yihuai Lou, Shizhen li, Shengjun Li, Naihao Liu*, and Bo Zhang, 2022, Seismic Volumetric Dip Estimation via Multi-channel Deep Learning Model, IEEE Transactions on Geoscience and Remote Sensing, 60, 4511014, 1-14.
[59] Bo Zhang, Yitao Pu, Zhaohui Xu*, Naihao Liu, Shizhen Li, and Fangyu Li, 2022, Exploring factors affecting the performance of deep learning in seismic fault attribute computation, Interpretation, 10(4), T619-T636.
[58] Hao Wu, Bo Zhang, and Naihao Liu*, 2022, Self-adaptive denoise net: Self-supervised learning for seismic migration artifacts and random noise attenuation, Journal of Petroleum Science and Engineering, 214, 110431: 1-11.
[57] Hao Wu, Zhen Li, and Naihao Liu*, 2022, Variable seismic waveforms representation: Weak-supervised learning based seismic horizon picking, Journal of Petroleum Science and Engineering, 214, 110412: 1-14.
[56] Naihao Liu, Lukun Wu, Jiale Wang, Hao Wu*, Jinghuai Gao, and Dehua Wang*, 2022, Seismic Data Reconstruction via Wavelet-based Residual Deep Learning, IEEE Transactions on Geoscience and Remote Sensing, 60, 4508213, 1-13.
[55] Shizhen Li, Naihao Liu*, Fangyu Li*, Jinghuai Gao, and Jicai Ding, 2022, Automatic Fault Delineation in 3D Seismic Images with Deep Learning: Data Augmentation or Ensemble Learning?, IEEE Transactions on Geoscience and Remote Sensing, 60, 5911214, 1-14.
[54] Naihao Liu, Shengtao Wei, Yang Yang*, Shengjun Li, Fengyuan Sun*, and Jinghuai Gao, 2022, Seismic Attenuation Estimation Using an Enhanced Log Spectral Ratio Method, IEEE Geoscience and Remote Sensing Letters, 19, 8025405, 1-5.
[53] 刘乃豪，李时桢，黄腾，高静怀，丁继才，王治国*，2022，改进的整体嵌套边缘检测技术识别地震断层, 石油地球物理勘探，57(3), 499-509.
[52] Yang Yang, Zhiguo Wang*, Jinghuai Gao*, Naihao Liu, and Zhen Li, 2021, Sparse inversion-based seismic random noise attenuation via self-paced learning, Artificial Intelligence in Geosciences, 2, 223-233.
[51] Yang Yang, Jinghuai Gao*, Zhiguo Wang*, and Naihao Liu, 2021, Data-Driven Time-Frequency Method and its Application in Detection of Free Gas Beneath a Gas Hydrate Deposit, IEEE Transactions on Geoscience and Remote Sensing, 60, 5909713, 1-13.
[50] Yihuai Lou, Haoran Zhang, Naihao Liu*, Rongchang Liu, and Fengyuan Sun*, 2021, Multi-scale coherence attribute and its application on seismic discontinuity description, IEEE Geoscience and Remote Sensing Letters, 19, 3004705, 1-5.
[49] Yijie Zhang, Haoran Zhang, Yang Yang, Naihao Liu*, and Jinghuai Gao, 2021, Seismic Random Noise Separation and Attenuation Based on MVMD and MSSA, IEEE Transactions on Geoscience and Remote Sensing, 60, 5908916, 1-14.
[48] Zhen Li, Fengyuan Sun, Jinghuai Gao, Naihao Liu, and Zhiguo Wang*, 2021, Multi-synchrosqueezing wavelet transform for time-frequency localization of reservoir characterization in seismic data, IEEE Geoscience and Remote Sensing Letters, 19, 7505305, 1-5.
[47] Dehua Wang, Jinghuai Gao, Fengyuan Sun, Naihao Liu*, and Lili Zhang, 2021, An improved TV-type variational regularization method for seismic impedance inversion, IEEE Geoscience and Remote Sensing Letters, 19, 7505205, 1-5.
[46] Naihao Liu, Jiamin Chen, Hao Wu*, Fangyu Li*, and Jinghuai Gao, 2021, Microseismic first arrival picking using fine-tuning Feature Pyramid Networks, IEEE Geoscience and Remote Sensing Letters, 19, 7505105, 1-5.
[45] Hao Wu, Zhen Li, Naihao Liu, and Bo Zhang*, 2021, Improved seismic well tie by integrating variable-size window resampling with well-tie net, Journal of Petroleum Science and Engineering, 208, 109368, 1-9.
[44] Naihao Liu, Teng Huang, Jinghuai Gao, Zongben Xu, Daxing Wang, and Fangyu Li*, 2021, Quantum-enhanced deep learning based lithology interpretation from well logs, IEEE Transactions on Geoscience and Remote Sensing, 60, 4503213, 1-13.
[43] Hui Li, Jing Lin, Baohai Wu*, Jinghuai Gao, and Naihao Liu, 2021, Elastic properties estimation from prestack seismic data using GGCNNs and application on tight sandstone reservoir characterization, IEEE Transactions on Geoscience and Remote Sensing, 60, 4503521, 1-21.
[42] Naihao Liu, Fangyu Li*, Dehua Wang*, Jinghuai Gao, and Zongben Xu, 2021, Ground-roll Separation and Attenuation Using Curvelet-based Multichannel Variational Mode Decomposition, IEEE Transactions on Geoscience and Remote Sensing, 60, 5901214, 1-14.
[41] Chenyu Qiu, Bangyu Wu*, Naihao Liu, Xu Zhu, and Haoran Ren, 2021, Deep learning prior model for unsupervised seismic data random noise attenuation, IEEE Geoscience and Remote Sensing Letters, 19, 7502005, 1-5.
[40] Fangyu Li, Fengyuan Sun, Naihao Liu*, and Rui Xie, 2021, Denoising seismic signal via resampling local applicability functions, IEEE Geoscience and Remote Sensing Letters, 19, 7501605, 1-5.
[39] Naihao Liu, Teng Huang, Jinghuai Gao, Xiudi Jiang, and Fangyu Li*, 2021, Seismic local instantaneous frequency extraction for describing superposed sands, IEEE Geoscience and Remote Sensing Letters, 19, 3001105, 1-5.
[38] Zirui Wang, Bo Li, Naihao Liu*, Bangyu Wu*, and Xu Zhu, 2021, Distilling knowledge from an ensemble of convolutional neural networks for seismic fault detection, IEEE Geoscience and Remote Sensing Letters, 19, 7500805, 1-5.
[37] Jing Lin, Hui Li*, Naihao Liu*, Jinghuai Gao, and Zhen Li, 2021, Automatic lithology identification by applying LSTM to logging data: A case study in X tight rock reservoirs, IEEE Geoscience and Remote Sensing Letters, 18(8), 1361-1365.
[36] Fangyu Li, Rongchang Liu, Yihuai Lou, and Naihao Liu*, 2021, Revisit seismic attenuation attributes: Influences of the spectral balancing operation on seismic attenuation analysis, Interpretation, 9(3), T767-T779.
[35] Bangyu Wu, Weirong Qiu, Junxiong Jia*, and Naihao Liu*, 2021, Landslide susceptibility modeling using bagging based Positive-Unlabeled Learning, IEEE Geoscience and Remote Sensing Letters, 18(5), 766-770.
[34] Yajun Tian, Jinghuai Gao*, Naihao Liu, and Daoyu Chen, 2021, Construction of optimal basic wavelet via AIDNN and its application in seismic data analysis, IEEE Geoscience and Remote Sensing Letters, 18(7), 1144-1148.
[33] Dehua Wang, Jinghuai Gao, Naihao Liu*, and Xiudi Jiang, 2021, Structure-oriented DTGV regularization for random noise attenuation in seismic data, IEEE Transactions on Geoscience and Remote Sensing, 59(2), 1757-1771.
[32] Zhaoqi Gao*, Chuang Li, Naihao Liu, Zhibin Pan, Jinghua Gao, and Zongben Xu, 2021, Large-dimensional seismic inversion using global optimization with Autoencoder based model dimensionality reduction, IEEE Transactions on Geoscience and Remote Sensing, 59(2), 1718-1732.
[31] Naihao Liu, Tao He, Yajun Tian, Bangyu Wu*, Jinghuai Gao, and Zongben Xu, 2020, Common azimuth seismic data fault analysis using residual U-Net, Interpretation, 8(3), SM25-SM37.
[30] Naihao Liu, Zhen Li, Fengyuan Sun, Fangyu Li*, and Jinghuai Gao, 2020, Seismic geological structure characterization using a high-order spectrum-coherence attribute, Interpretation, 8(2), T391-T401.
[29] Naihao Liu, Yang Yang, Zhen Li*, Jinghuai Gao, Xiudi Jiang, and Shulin Pan, 2020, Seismic signal de-noising using Time-Frequency Peak Filtering based on Empirical Wavelet Transform, Acta Geophysica, 68, 425-434.
[28] Fangyu Li, Bangyu Wu, Naihao Liu*, Ying Hu, and Hao Wu, 2020, Seismic time-frequency analysis via adaptive mode separation based wavelet transform, IEEE Geoscience and Remote Sensing Letters, 17(4), 696-700.
[27] Bangyu Wu, Jiaxu Yu, Haoran Ren, Yihuai Lou, and Naihao Liu*, 2020, Seismic traffic noise attenuation using lp-norm Robust PCA, IEEE Geoscience and Remote Sensing Letters, 17(11), 1998-2001.
[26] Hui Li, Jing Lin, Naihao Liu, Fangyu Li*, and Jinghuai Gao, 2020, Seismic reservoir delineation via Hankel transform based enhanced empirical wavelet transform, IEEE Geoscience and Remote Sensing Letters, 17(8), 1411-1414.
[25] Qian Wang, Jinghuai Gao*, and Naihao Liu, 2020, Second-order synchrosqueezed wave packet transform and its application for characterizing seismic geological structures, IEEE Geoscience and Remote Sensing Letters, 17(5), 760-764.
[24] Zhi Hu, Jinghuai Gao*, and Naihao Liu, 2020, Separation of Blended Seismic Data Using the Synchrosqueezed Curvelet Transform, IEEE Geoscience and Remote Sensing Letters, 17(4), 711-715.
[23] Zhen Li, Jinghuai Gao*, Zhiguo Wang*, Naihao Liu, and Yang Yang, 2020, Time-synchrosqueezing general chirplet transform for seismic time-frequency analysis, IEEE Transactions on Geoscience and Remote Sensing, 58(12), 8626-8636.
[22] Bangyu Wu, Delin Meng, Lingling Wang*, Naihao Liu, and Ying Wang, 2020, Seismic Impedance Inversion Using Fully Convolutional Residual Network and Transfer Learning, IEEE Geoscience and Remote Sensing Letters, 17(12), 2140-2144.
[21] Fengyuan Sun, Jinghuai Gao*, Bing Zhang, and Naihao Liu, 2020, Coherence algorithm with a high-resolution time-time transform and feature matrix for seismic data, Geophysical Prospecting, 68(4), 1113-1125.
[20] Zhen Li, Jinghuai Gao*, Hui Li, Zhuosheng Zhang, Naihao Liu, and Xiangxiang Zhu, 2020, Synchroextracting transform: the theory analysis and comparisons with the synchrosqueezing transform, Signal Processing, 166, 107243.
[18] Naihao Liu, Zhen Li, Fengyuan Sun, Qian Wang*, and Jinghuai Gao*, 2019, The improved empirical wavelet transform and applications to seismic reflection data, IEEE Geoscience and Remote Sensing Letters, 16(12), 1939-1943.
[17] Naihao Liu, Bo Zhang*, Jinghuai Gao, Hao Wu, and Shengjun Li, 2019, Seismic anelastic attenuation estimation using prestack seismic gather, Geophysics, 84(6), A47-W45.
[16] Naihao Liu, Jinghuai Gao*, Bo Zhang, Qian Wang, and Xiudi Jiang, 2019, Self-adaptive generalized S-transform and its application in seismic time-frequency analysis, IEEE Transactions on Geoscience and Remote Sensing, 57(10), 7849-7859.
[15] Zhen Li, Jinghuai Gao*, Naihao Liu, Fengyuan Sun, and Xiudi Jiang, 2019, Random Noise Suppression of Seismic Data by Time-Frequency Peak Filtering with Variational Mode Decomposition, Exploration Geophysics, 50(6), 634-644.
[14] Yihuai Lou, Bo Zhang*, Tengfei Lin, Naihao Liu, Hao Wu, Rongchang Liu, and Danping Cao, 2019, Accurate seismic dip and azimuth estimation using semblance dip guided structure-tensor analysis, Geophysics, 84(5), O103-O112.
[13] Hao Wu, Bo Zhang*, Tengfei Lin, Fangyu Li, and Naihao Liu, 2019, White noise attenuation of seismic data by integrating variational mode decomposition and convolutional neural network, Geophysics, 84(5), V307-V317.
[12] Hongling Chen, Jinghuai Gao*, Naihao Liu, and Yang Yang, 2019, Multitrace Semi-blind nonstationary deconvolution, IEEE Geoscience and Remote Sensing Letters, 16(8), 1195-1199.
[11] Liuyang Yang, Jinghuai Gao*, Naihao Liu, Tao Yang, and Xiudi Jiang, 2019, A coherence algorithm for 3D seismic data analysis based on the mutual information, IEEE Geoscience and Remote Sensing Letters, 16(6), 967-971.
[10] Hao Wu, Fangyu Li, Bo Zhang*, and Naihao Liu, 2019, Semi-automatic first arrival picking of micro-seismic events by using pixel-wise convolutional image segmentation method, Geophysics, 84(3), V143-V155.
[9] Fengyuan Sun, Jinghuai Gao*, and Naihao Liu, 2019, An Efficient Method to Model Seismic Propagation in Diffusive-viscous Media with Dipping Interfaces, Journal of Seismic Exploration, 28, 21-40.
[8] Fengyuan Sun, Jinghuai Gao*, and Naihao Liu, 2019, The approximate constant and linearized reflection coefficients based on the generalized fractional wave equation, Journal of the Acoustical Society of America, 145(1), 243-253.
[2] Naihao Liu, Jinghuai Gao*, Zhuosheng Zhang, Xiudi Jiang, and Qi Lv, 2017, High resolution characterization of geological structures using synchrosqueezing transform, Interpretation, 5(1), T75-T85.
会议论文（Conference Paper）
[37] Yuxin Zhang, Naihao Liu, Yang Yang, Zhiguo Wang, Jinghuai Gao, Xiudi Jiang, 2022, Sparse time-frequency representation based on Unet with domain adaptation, SEG|AAPG Second International Meeting for Applied Geoscience & Energy, 1302-1306.
[36] Youbo Lei, Yang Yang, Naihao Liu, Shengtao Wei, Jinghuai Gao, Xiudi Jiang, 2022, Seismic sparse time-frequency representation via GAN-based unsupervised learning, SEG|AAPG Second International Meeting for Applied Geoscience & Energy, 1432-1436.
[35] Jiale Wang, Naihao Liu, Yihuai Lou, Jinghuai Gao, 2022, Seismic random noise attenuation via enhanced similarity self-supervised learning, SEG|AAPG Second International Meeting for Applied Geoscience & Energy, 1447-1451.
[34] Bo Zhang, Yitao Pu, Zhaohui Xu, Naihao Liu, Shizhen Li, Fangyu Li, 2022, Training data versus deep learning architectures in the seismic fault attribute computation, SEG|AAPG Second International Meeting for Applied Geoscience & Energy, 1725-1729.
[33] Youbo Lei, Naihao Liu, Yang Yang, Shengtao Wei, Zhiguo Wang, Jinghuai Gao, 2022, Sparse Time-Frequency Representation Based on Self-Supervised Learning, EAGE Annual Meeting Expanded Abstracts, 1-5.
[32] Yuxin Zhang, Naihao Liu, Yang Yang, Zhiguo Wang, Jinghuai Gao, Xiudi Jiang, 2022, Sparse Time-Frequency Transform Via Deep Learning and Transfer Learning: Part II-Transfer Learning and Field Data Application, EAGE Annual Meeting Expanded Abstracts, 1-5.
[31] Yihuai Lou, Fengyuan Sun, and Naihao Liu, 2021, Seismic fault interpretation by using a multi-scale coherence attribute, EAGE Annual Meeting Expanded Abstracts, 1-5.
[30] Haoran Zhang, Yijie Zhang, Yang Yang, Naihao Liu, Zhiguo Wang, and Jinghuai Gao, 2021, Seismic random noise attenuation using MVMD and MSSA, SEG|AAPG First International Meeting for Applied Geoscience & Energy. Society of Exploration Geophysicists, 1111-1115.
[29] Delin Meng, Bangyu Wu, Naihao Liu, and Wenchao Chen, 2020, Semi-supervised deep learning seismic impedance inversion using generative adversarial network, IEEE International Geoscience and Remote Sensing Symposium, 1393-1396.
[28] Lingling Wang, Delin Meng, Bangyu Wu, and Naihao Liu, 2020, Seismic Inversion via Closed-Loop Fully Convolutional Residual Network and Transfer Learning, SEG Technical Program Expanded Abstracts, 1521-1525.
[27] 王紫蕊, 吴帮玉, 刘乃豪, 朱旭, 李博, 2019, 卷积神经网络在地震断层自动识别中的应用, 中国石油学会2019年物探技术研讨会.
[26] 俞嘉旭, 吴帮玉, 刘乃豪, 孟德林, 任浩然, 2019, 基于p范数鲁棒主成分分析的地震数据公路噪声压制, 中国石油学会2019年物探技术研讨会.
[25] 何涛, 刘乃豪, 吴帮玉, 朱旭, 郑浩, 2019, 合成数据样本卷积神经网络断层自动识别应用, 中国石油学会2019年物探技术研讨会.
[24] 俞嘉旭, 吴帮玉, 刘乃豪, 任浩然, 朱小三, 2019, 基于局部成像矩阵的监督学习散射点识别, 中国石油学会2019年物探技术研讨会.
[23] 孟德林, 邱维蓉, 汪玲玲, 吴帮玉, 刘乃豪, 2019, 基于残差网络的波阻抗反演, 中国石油学会2019年物探技术研讨会.
[12] Naihao Liu, Jinghuai Gao, and Qian Wang, 2017, Weighted average instantaneous frequency extraction via time-frequency analysis, EAGE Technical Program Expanded Abstracts.
