Zhege Liu-College of Communication Engineering

Name: Zhege Liu

Title: Lecturer

Focus: Machine Learning, Geodetection and Information Technology

Department: Department of Communication Engineering

Team: Intelligent Information Processing

[Introduction]

Zhege Liu, male, lecturer, holds a doctoral degree. I have worked at Huawei Technologies Co., Ltd. and have extensive experience in scientific research and engineering development. In recent years, I have published over 20 papers in international journals and important academic conferences, with 13 papers indexed in SCI. Served as a reviewer for the journals IEEE GRSL, IEEE TGRS, Interpretation and Frontiers in Earth Science.

[Undergraduate Courses]

Machine Learning, Data Structure and Algorithm Design, Programming Training

[Research Projects]

1. Open Fund of the Key Laboratory of Mathematical Geology in Sichuan Province, scsxdz2023-11, Research and Application of Characterization Method for Complex Overlapping Tight Channel Reservoirs Based on Deep Learning, 2024-1-1 to 2024-12-31. (Principal Investigator)

2. National Natural Science Foundation of China, Special Project, 42042046, Strategic Research on the Application of Artificial Intelligence in Geophysical Inversion and Imaging, from 2021-01-01 to 2021-12-31. (Participant)

3. National Natural Science Foundation of China, Key Project, 42030812, Research on Theoretical Methods for Gas Detection in Deep Carbonate Reservoirs in Sichuan Basin Based on X-Vector Deep Learning of Seismic Data Minor Components, from 2021-01-01 to 2025-12-31. (Participant)

4. National Natural Science Foundation of China, General Project, 41974160, Research on Theoretical Methods for Predicting Gas Content in Deep Carbonate Reservoirs in Sichuan Basin Based on Dispersion Inversion of Deep Seismic Wavefield, from 2020-01-01 to 2023-12-31. (Participant)

5. Sichuan Provincial Natural Science Foundation General Project, 2023NSFSC0258, Research on the Theory and Method of Pulse Neural Network Recognition for Carbonate Reservoirs in the Sichuan Basin, from 2023-01-01 to -2024-12-31. (Participant)

6. Science and Technology Innovation Major Team Project of Chengdu University of Information Technology, KYTD202306, Science and Technology Innovation Major Team Project of Chengdu University of Information Technology, from 2023-01-01 to 2024-12-31. (Participant)

7. Exploration and Development Research Institute of Southwest Oil and Gas Field Branch, China Petroleum & Natural Gas Corporation (CNPC) commissioned project, Research on Reservoir Prediction Technology Based on Frequency Attenuation Attributes, from 2023-11-01 to 2023-12-31. (Participant)

8. Open Fund of the Key Laboratory of Mathematical Geology in Sichuan Province, Research on Gas Detection Methods for Deep and Complex Marine Reservoirs, from 2023-1-1 to 2024-12-31. (Participant)

[Published Papers]

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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, p.105347.

7. Wang, J., Cao, J. and Liu, 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.

8. 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.

9. 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.

10. 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.

11. 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.

12. Liao, X., Cao, J., Hu, J., You, J., Jiang, X. and Liu, 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.

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