Name: Guoyin Zhang
Academic title: Associate Professor
Research Area:Geological resources and geological engineering
Email: zhanggy@upc.edu.cn
Research Interests:
Reservoir characterization and prediction, Machine leaning,Geological modeling
Courses Offered:
Oil & natural gas development geology, Big data and artificial intelligence in geosciences, Reservoir characterization and modeling
Scholarly Activities
-Publications:
[1]Zhang, G., Lin, C., Ren, L., et al., 2022. Seismic characterization of deeply buried paleocaves based on Bayesian deep learning. Journal of Natural Gas Science and Engineering, 97, 104340.
[2] Zhang, G., Wang, Z., Mohaghegh, S., Lin, C., et al., 2021. Pattern visualization and understanding of machine learning models for permeability prediction in tight sandstone reservoirs.Journal of Petroleum Science and Engineering, 200, 108142.
[3] Zhang, G., Lin, C., and Chen, Y., 2020. Convolutional neural networks for microseismicwaveform classification and arrival picking. Geophysics, 85(4), WA227-WA240.
[4] Zhang, G., Wang, Z., Guo, X., et al., 2019. Characteristics of lacustrine dolomitic rock reservoir and accumulation of tight oil in the Permian Fengcheng Formation, the western slope of the Mahu Sag, Junggar Basin, NW China. Journal of Asian Earth Science, 178, pp.64-80.
[3]Zhang, G., Wang, Z., and Chen, Y.,2018. Deep learning for seismic lithology prediction. Geophysical Journal International, 215(2), pp.1368-1387.
-Research Project:
[1] 2023-2025, Fundamental Research Funds for the Central Universities (No. 22CX06002A). Intelligent characterization of oil and gas reservoirs driven by domain knowledge and big data.
[2] 2020-2023, National Natural Science Foundation of China (No. 2002144). Characterization and connectivity pattern of carbonate karst fracture-cave structure based on deep learning.
[2] 2019-2023, Major scientific and technological projects of CNPC (No. ZD2019-183-006). Reservoir characterization of deep complex oil and gas reservoirs in the Tarim Basin.
-Other websites:
https://orcid.org/0000-0003-4833-1741