Personal Information

Suzhen Shi

Professor

Email：ssz@cumtb.edu.cn

Research Interests

(1) Artificial Intelligence and Geophysics

(2) Distributed Optical Fiber Detection

(3) Digital Rock and Rock Physics Theory

(4) Seismic Sedimentology and Reservoir Sweet Spot Prediction

Education/Work Background

2000.09-2004.07, School of Resources and Environment, Henan Polytechnic University, Bachelor.

2004.09-2007.01, School of  Resources, China University of Mining and Technology-Beijing, Master.

2007.03-2012.01, College of Earth Science and Surveying Engineering, China University of Mining and Technology-Beijing, PhD.

2012.03-2014.05, College of Mechanics and Architectural Engineering, China University of Mining and Technology-Beijing, Postdoc.

2014.06-2018.06, State Key laboratory of Coal Resources and Safe Mining, China University of Mining and Technology-Beijing, Lecturer.

2018.07-2023.06，State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, Associate Professor.

2023.07-Now，State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, Professor.

Teaching Courses

Geophysical Exploration

Seismic Data Interpretation and Inversion

Seismic Data Processing and interpretation

Key Research Funding

[1] Suzhen Shi. Research on full-frequency band dispersion and attenuation mechanisms of coal reservoirs and construction of fluid factors. National Natural Science Foundation of China. 2025-2028, PI.

[2] Suzhen Shi. Seismic response mechanism of fractures in coal reservoirs. National Natural Science Foundation of China, 2018-2021, PI

[3] Geophysical prediction for key parameters of tight reservoir geology-engineering sweet spot, 2021-2024, PI

[3]  Post-stack wave impedance in Xinjing Coal Mine, 2023-2024, PI

Honors

2019.06, I won the Coal Youth Science and Technology Award.

2018.12, I was awarded the Green Mine Youth Science and Technology Award.

Selected Publications

[1] Shi, S., Guo J., Bai J., et al. Eliminate the tuning effect of AVO attribute for coal structure identification, Chinese Journal of Geophysics. 2025,68(4), 1542-1554.

[2] Shi, S., Li, M., Chang, W., et al. Seismic impedance inversion based on semi-supervised learning. Computer & Geosciences, 2024, 182, 105497.

[3] Shi, S., Shi G., Pei J., et al. Porosity prediction in tight sandstone reservoirs based on a one–dimensional convolutional neural network–gated recurrent unit model. Applied Geophysics, 2023, 20(4), 1-13.

[4] Shi, S., Qi, Y., Chang, W., et al. Acoustic impedance inversion in coal strata using the priori constraint-based TCN-BiGRU method. Advances in Geo-Energy Research, 2023, 9(1): 13-24.

[5] Wang, X., Shi, S.*, Yao, X., et al. Automatic Identification of Seismic Faults via the Integration of ResNet-50 Residual Blocks and Convolutional Attention Modules. Applied Geophysics, 2023: 1-16.

[6] Shi, S., Feng, J., Bai, J., et al. In situ stress field prediction based on seismic data in Sijiazhuang mining area. Interpretation, 2023, 11(1): T7-T19.

[7] Shi, S., Li, M., Gao, W., et al. Improved Unet in Lithology Identification of Coal Measure Strata. Lithosphere, 2022(Special 12): 4087265.

[8] Shi, S., Gu, J., Liu, Z., et al. Tunneling route prediction of shield machine based on random forest P-wave generation. Applied Geophysics, 2021, 18(3): 1-11.

[9] Shi, S., Feng, J., Liu, Z., et al. Seismic inversion-based prediction of the elastic parameters of rocks surrounding roadways: a case study from the Shijiazhuang mining area of North China. Acta Geophysica, 2021, 69(6): 2219-2230.

[10] Shi, S., Gu, J., Feng, J., et al. Intelligent identification method for near-surface ground fissures based on seismic data. Applied Geophysics, 2020, 17(5-6): 639-648.

[11] Shi, S., Liu, Z., Feng, J., et al. Using 3D seismic exploration to detect ground fissure. Advances in Geo-Energy Research, 2020, 4(1): 13-19.