姓名：刘哲哿

职称：讲师

方向：机器学习、地球探测与信息技术

系别：通信工程系

团队：智能信息处理

邮箱：liuzhege@cuit.edu.cn

【个人简介】

刘哲哿，博士研究生学历。曾在华为技术有限公司工作，有丰富的科研和工程开发经验。发表期刊及会议论文25篇，其中SCI收录21篇。主要研究地震信号处理与解释。

【主讲课程】

本科生课程：《机器学习》《数据结构与算法设计》《程序设计训练》《创新发明与知识产权实务》

【主持参与项目情况】

1.国家自然科学基金委员会，面上项目，42474145，基于薛定谔方程的深层-超深层碳酸盐岩储层含气性检测理论和方法研究，2025/01-2028/12，参与，第1主研。

2.国家自然科学基金委员会，专项项目，42042046，人工智能在地球物理反演和成像中的应用战略研究，2021/01-2021/12，参与。

3.国家自然科学基金委员会，重点项目，42030812，基于地震数据次微成分x-矢量深度学习的四川盆地深层碳酸盐岩储层含气性检测理论方法研究，2021/01-2025/12，参与。

4.国家自然科学基金委员会，面上项目，41974160，基于深度域地震波频散反演的四川盆地深层碳酸盐岩储层含气量预测理论方法研究，2020/01-2023/12，参与。

5.数学地质四川省重点实验室2023年开放基金课题，scsxdz2023-11，基于深度学习的复杂叠置致密河道储层表征方法研究与应用，2024/1-2025/12，主持。

6.油气资源与勘探技术教育部重点实验室（长江大学） 第十批开放基金资助项目，K2024-20，2025/01-2026/12，主持。

7.海相深层复杂储层的量子力学表征方法，成都信息工程大学科技创新重大团队项目，KYTD202306，2023/01-2024/12，参与，第1主研。

8.四川省自然科学基金面上项目，2023NSFSC0258，四川盆地碳酸盐岩储层的脉冲神经网络识别理论及方法研究，2023/01-2024/12，参与，第1主研。

9.中国石油天然气股份有限公司西南油气田分公司勘探开发研究院委托项目，基于频率衰减属性的储层预测技术攻关，2023/11-2023/12，参与，第1主研。

10.数学地质四川省重点实验室2022年开放基金，scsxdz2022-02，海相深层复杂储层的含气性检测方法研究，2023/01-2024/12，参与，第1主研。

11.先进密码技术与系统安全四川省重点实验室开放课题，SKLACSS-202610，面向SEG-Y格式地震数据体的自适应鲁棒水印与溯源应用研究，2026/1-2027/12，主持。

【科研成果】

（1）发表论文

1. Wang, Z.,Liu, Z.G.*, Xue, Y.J., Chen, S.N. and Yang, J., 2026. EPAC-Net: Enhanced Parallel Attention Convolution Net for Seismic Image Super-Resolution Reconstruction. Applied Geophysics, pp.1-16.

2. Chen, S.,Liu, Z.*, Qin, Z., Liu, X., Xue, Y. and Cao, J., 2025. A Convolutional Neural Network to Spiking Neural Network Conversion Framework for Seismic Denoising. IEEE Access.

3. Liu, J.,Liu, Z.*, Xue, Y., Cao, J., Lu, Y. and Chen, H., 2024. A model integration approach for stratigraphic boundary delineation based on local data augmentation. Journal of Applied Geophysics, p.105514.

4. Chen, S.,Liu, Z.*, Zhou, H., Wen, X. and Xue, Y., 2023. Seismic Facies Visualization Analysis Method of SOM Corrected by Uniform Manifold Approximation and Projection. IEEE Geoscience and Remote Sensing Letters, 20, pp.1-5.

5.Liu, Z., Cao, J., You, J., Chen, S., Lu, Y. and Zhou, P., 2021. A lithological sequence classification method with well log via SVM-assisted bi-directional GRU-CRF neural network. Journal of Petroleum Science and Engineering, 205, p.108913.

6.Liu, Z., Cao, J., Lu, Y., Zhou, P. and Hu, J., 2021. A Hierarchical Clustering Method of SOM Based on DTW Distance for Variable-Length Seismic Waveform. IEEE Geoscience and Remote Sensing Letters, 19, pp.1-5.

7.Liu, Z., Cao, J., Chen, S., Lu, Y. and Tan, F., 2020. Visualization analysis of seismic facies based on deep embedded SOM. IEEE Geoscience and Remote Sensing Letters, 18(8), pp.1491-1495.

8.Liu, Z., Cao, J., Lu, Y., Chen, S. and Liu, J., 2019. A seismic facies classification method based on the convolutional neural network and the probabilistic framework for seismic attributes and spatial classification. Interpretation, 7(3), pp.SE225-SE236.

9. Chen, S.N.,Liu, Z.G., Ma, S.Y., Zhai, J.B. and Xue, Y.J., 2026. Similarity evaluation of seismic datasets by an adversarial validation framework based on deep learning. Applied Geophysics, pp.1-18.

10.Wang, J., Cao, J. andLiu, Z., 2024. Unsupervised machine learning-based multi-attributes fusion dim spot subtle sandstone reservoirs identification utilizing isolation forest. Geoenergy Science and Engineering, 234, p.212626.

11.Xue, Y.J., Zhang, H., Zhang, J.Q., Wang, X.J., Cao, J.X.,Liu, Z.G., Wen, W. and Zhong, J.D., 2025. Application of a weighted VMD–derived Hilbert marginal differential cepstrum–based hydrocarbon detection method to a Deep Carbonate Thin Reservoir in China. Journal of Applied Geophysics, p.105837.

12.Xue, Y.J., Wang, X.J.,Liu, Z.G., Wen, W., Yang, J., Li, D.F. and Zhang, X.X., 2024. Application of variational mode decomposition–based Hilbert marginal differential cepstrum for hydrocarbon detection. Geophysical Prospecting, 72(2), pp.390-402.

13.Xue, Y.J., Zhang, H., Zhang, J.Q., Wang, X.J., Cao, J.X.,Liu, Z.G., Wen, W., Yang, J. and Li, D.F., 2025. Hydrocarbon detection via quantum mechanics–based highlight volumes extraction. Geophysical Prospecting, 73(1), pp.19-37.

14.Xue, Y.J., Wang, X.J., Cao, J.X.,Liu, Z.G.and Yang, J., 2023. Quantum mechanics-based seismic energy absorption analysis for hydrocarbon detection. Geophysical Journal International, 233(3), pp.1950-1959.

15.Xue, Y.J., Zhang, H., Zhang, J.Q., Wang, X.J., Cao, J.X. andLiu, Z.G., 2025. Local quantum filtering and denoising of seismic data. Geophysics, 90(5), pp.V455-V472.

16.Wang, J., Cao, J.,Liu, Z.and Zhao, S., 2025. Deep carbonate reservoir hydrocarbon detection using multiseismic features constrained unsupervised machine learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

17.Ma, S., Cao, J.,Liu, Z., Jiang, X., Su, Z. and Xue, Y.J., 2023. Gas-bearing prediction of deep reservoir based on DNN embeddings. Frontiers in Earth Science, 11, p.1117797.

18.Lu, Y., Cao, J.,Liu, Z., You, J. and Hu, J., 2024. Adaptive fault enhancement in OVT domain based on anisotropy theory. Journal of Applied Geophysics, 223, p.105347.

19.You, J.,Liu, Z., Liu, J. and Li, C., 2019. One-way propagators based on matrix multiplication in arbitrarily lateral varying media with GPU implementation. Computers & Geosciences, 130, pp.32-42.

20.Liao, X., Cao, J., Hu, J., You, J., Jiang, X. andLiu, Z., 2019. First arrival time identification using transfer learning with continuous wavelet transform feature images. IEEE Geoscience and Remote Sensing Letters, 17(11), pp.2002-2006.

21.Chen, S., Wen, X., Morozov, I.B., Deng, W. andLiu, Z., 2021. Macroscopic non‐Biot's material properties of sandstone with pore‐coupled wave‐induced fluid flows. Geophysical Prospecting, 69(3), pp.514-529.

22.Chen, S., Wen, X. andLiu, Z., 2019, December. The influence of consolidation coefficients on wave attenuation and dispersion based on general linear solid framework. In AIP Conference Proceedings (Vol. 2186, No. 1, p. 170010). AIP Publishing LLC.

23.Wang, Z., Xue, Y.,Liu, Z.and Chen, S., 2025, July. OPMNet: Overlapped Patch Merging Convolution Net for Seismic Image Super-Resolution Reconstruction. In 2025 4th International Conference on Electronics, Integrated Circuits and Communication Technology (EICCT) (pp. 641-645). IEEE.

24.逯宇佳,曹俊兴,刘哲哿,等.波形分类技术在缝洞型储层流体识别中的应用[J].石油学报, 2019.

25.王俊,曹俊兴,刘哲哿,等.基于长短期记忆网络的钻前测井曲线预测方法[J].成都理工大学学报:自然科学版, 2020, 47(2):10.

（2）专著

1.薛雅娟，王兴建，杜正聪，刘哲哿，杜浩坤，陈伟。储层烃类信息的局域波分解提取理论及方法，西安电子科技大学出版社，2024，7。