陈国雄

基本信息Personal Information

副教授 博士生导师 硕士生导师

性别 : 男

毕业院校 : 中国地质大学(武汉)

学历 : 博士研究生毕业

学位 : 博士学位

在职信息 : 在职

所在单位 : 地质过程与矿产资源国家重点实验室

入职时间 : 2016年07月10日

学科 : 地球探测与信息技术

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个人简介Personal Profile

陈国雄,副研究员,博士生导师,1988年生,湖南怀化人。主要从事地质-地球物理-数学地球科学交叉研究,注重利用大数据、计算机模拟以及人工智能技术解决地学定量化问题;近年来聚焦极端地质事件(如超大陆聚散、大火成岩省、大氧化事件及其大规模成矿效应等)的定量表征、模拟及预测研究这一前沿领域,结合大数据与人工智能,取得创新成果如下:(1)建立了极端地质事件时空大数据挖掘的小波-分形-神经网络模型与方法体系;(2)为深部成矿弱缓信息表征和深部矿产资源定量预测提供了新的智能方法技术,被应于多个矿集区的找矿预测并取得成效;(3)为深时多种极端地质事件模拟预测提供了数据驱动模型与方法,揭示了超大陆聚散、沉积物俯冲以及大氧化事件协同演化新机制。全部成果在Nature Communications、Earth and Planetary Science Letters、Geophysical Research Letters、Journal of Geophysical Research: Solid Earth、Mathematical Geosciences、Geophysics、Computers & Geosciences等刊物上发表第一/通讯作者SCI论文18篇(近五年12篇)。应邀撰写英文《数学地球科学百科全书》长篇章节1篇。受邀担任Ore Geology Reviews副主编、Mathematical Geosciences期刊编委和专辑客座主编、地球科学和Journal of Earth Science青年编委等。获得国家发明专利1项和软件著作权2项。

》招生方向

大数据矿产资源预测,深时地学大数据分析与地球早期演化,背景噪声地震学,智能地震数据解译及三维地质建模等方向,欢迎具有地质、地球物理、矿普或类似专业背景,兼具一定编程能力/兴趣(Matlab/Python/C++)的本科生/研究生加入课题组。

》科研项目

国家自然科学基金面上基金,基于多尺度小波-分形-神经网络的深部找矿信息挖掘研究,2020/1-2023/12,主持;

国家自然科学基金青年基金,小波域多重分形建模与深部矿致异常识别研究—以南岭矿集区为例,2018/1-2020/12,主持;

自然资源部中国地质调查局矿产地质调查项目,集宁覆盖区二维反射地震测量,2019/7-2020/5,主持;

自然资源部中国地质调查局矿产地质调查项目,集宁覆盖区背景噪声地震成像,2019/5-2020/4,主持;

鄂东南矿集区战略性矿产深部找矿理论与技术方法应用创新子课题铜绿山矿田密集台阵面波层析成像技术研究, 2022/6-2022/6,主持;

国家重点研发计划“深部矿产资源预测理论与方法”项目子课题,“深部矿产三维预测模型与虚拟现实”,2016/7-2020/6,参与。

》第一作者/通讯作者论文

2022年

23. Wang D., Chen G.*. Intelligent Seismic Stratigraphic Modeling Using Temporal Convolutional Network, Computers & Geosciences, 2022, moderate revision.

22. Chen G., Cheng Q.*, Timothy Lyons, Shen J., Frits Agterberg, Huang N., Zhao M.. Reconstructing Atmospheric Oxygenation History Using Machine Learning. 2022, Nature Communications, 13, 5862 (2022). https://doi.org/10.1038/s41467-022-33388-5.

21. Chen G.*, Huang N., Wu G., et al.. Mineral Prospectivity Mapping Based on Wavelet Neural Network and Monte Carlo Simulations: A Case Study from Nanling W-Sn Metallogenic Province. Ore Geology Reviews, 2022(143): 104765, https://doi.org/10.1016/j.oregeorev.2022.104765.

20. Luo L., Chen G.*, Xia Q. Tectonic-diffusion Estimates of Global Porphyry Molybdenum Resources. Nature Resource Research, 2022, 31, 751–766,https://doi.org/10.1007/s11053-022-10024-z.

19. Chen G. , Cheng Q.*, Shanan E. Peter, Christopher Spencer, Zhao M..Feedback between Surface and Deep Processes: Insight from Time Series Analysis of Sedimentary Record. Earth and Planetary Science Letters. 2022, 579: 117352. DOI: 10.1016/j.epsl.2021.117352.

18. 王德涛,陈国雄*. 基于时间卷积网络的地震波阻抗反演.地球科学,2022,47(04):1492-1506. 

2021年及之前

17. Chen G.*, Zhang H., Wavelets in Geosciences. Earth Science Series. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_37-1.

16. Chen G.*, Cheng Q., Luo Y., Yang Y. Deng X. Seismic imaging of Caosiyao giant porphyry molybdenum deposit using ambient noise tomography. 2021,Geophysics, 86(6), B401-B412.

15. Wang D., Chen G.*, Seismic stratum segmentation using an encoder-decoder convolutional neural network. Mathematical Geosciences, 2021, 53: 1355-1374. 

14. Wu G., Chen G.*, Cheng Q., et al., Unsupervised Machine Learning for Lithological Mapping in Covered Areas, Jining, China, Using Geochemical Data. Nature Resource Research,  2020. 30 (2), 1053-1068. 

13. Yu H., Chen G.*, Gu H., A new multivariate pore-pressure prediction method based on machine learning, Computers & Geosciences. 2020(143): 104548. 

12. Wu G., Chen G.*, Wang D., et al. Identifying mineral prospectivity using seismic and potential field data in the Hongniangyu district, Inner Mongolia, China. Ore Geology Reviews. 2020(119):103317. 

11. Chen G., Cheng Q*. Cyclicity and Persistence of Earth’s Evolution Over Time Wavelet and Fractal Analysis. Geophysical Research Letters.  2018. 45: 8223-8230.

10. Chen G.*, Cheng Q. Fractal-Based Wavelet Filter for Separating Geophysical or Geochemical Anomalies from Background. Mathematical Geosciences, 2018, 50:249–272.

9. Chen G., Cheng Q.*, Fractal density modeling of crustal heterogeneity from the KTB deep hole, Journal of Geophysical Research: Solid Earth, 2017, 122:1919-1933.

8. Chen G., Cheng, Q.*, Zhang, H., Matched filtering method for separating magnetic anomaly using fractal model, Computers & Geosciences, 2016, 90: 179-188.

7. Chen G., Cheng, Q.*, Singularity analysis based on wavelet transform of fractal measures for identifying geochemical anomaly in mineral exploration, Computers & Geosciences, 2016, 87: 56–66.

6. Chen G., Cheng, Q.*, Zuo, R., Fractal analysis of geochemical landscapes using scaling noise model, Journal of Geochemical Exploration, 2016, 161: 62-71.

5. Chen G., Liu,T., Sun, J., Cheng, Q.*, Sahoo, B., Zhang,Z., Zhang, H., Gravity method for investigating the geological structures associated with W–Sn polymetallic deposits in the Nanling Range, China, Journal of Applied Geophysics, 2015, 120: 14-25.

4. Chen G.*, Cheng, Q., Zuo, R., Liu, T., Xi, Y., Identifying gravity anomalies caused by granitic intrusions in Nanling mineral district, China: a multifractal perspective, Geophysical Prospecting, 2015, 63:256-270.

3. Chen G.*, Cheng, Q., Liu,T., Yang, Y., Mapping local singularities using magnetic data to investigate the volcanic rocks of the Qikou depression, Dagang oilfield, eastern China, Nonlinear Processes in Geophysics, 2013, 20: 501-511.

2. 陈国雄, 刘天佑*, 孙劲松, 欧洋, 刘双. 2014. 南岭花岗岩成矿带多尺度重力场及深部构造特征. 地球科学−中国地质大学学报, 39(2):240-250.

1. 陈国雄*, 孙劲松, 刘天佑. 2012.GRACE卫星时变重力场的小波多尺度分解:以2008年汶川Ms 8.0大震为例,武汉大学学报−信息科学版. 37(6):679-682.

》合作论文(部分)

Zhao Y., Chen G., Liu X., et al. New method for estimating strike and dip based on structural expansion orientation for 3D geological modeling. Computers & Geosciences. In revision, 2020. 

Xu H, Luo Y, Yang Y, Shen W., Yin X., Chen G., et al. Three‐Dimensional Crustal Structures of the Shanxi Rift Constructed by Rayleigh Wave Dispersion Curves and Ellipticity: Implication for Sedimentation, Intraplate Volcanism, and Seismicity. Journal of Geophysical Research: Solid Earth, 2020, 125(11): e2020JB020146.

Zhang H, Ravat D, Marangoni Y R, Chen G., Hu X#. Improved total magnetization direction determination by correlation of the normalized source strength derivative and the RTP fields. Geophysics, 2018, 83(6): 1-45.

Zuo R., Wang J., Chen G., Yang M., 2015. Identification of weak anomalies: A multifractal perspective. Journal of Geochemical Exploration 154, 200-212.

Liu P., Liu T., Zhu P., Yang Y., Zhou Q., Zhang H., Chen G.. Depth Estimation for Magnetic and Gravity Anomaly Using Model Correction[J]. Pure and Applied Geophysics, 2017, 174(4): 1729-1742.

》会议摘要/报告

陈国雄,报告题目:基于小波-分形-神经网络的找矿信息挖掘与矿产资源预测,全国首届金属矿产资源勘查大会,2021.10, 合肥

陈国雄,报告题目:金属矿床背景噪声成像技术—以曹四夭超大型斑岩Mo矿床为例,固体地球科学重点实验室联盟2021年实验技术与应用年会,2021.7, 北京

陈国雄,报告题目:地学大数据与智能找矿预测,鄂东南矿集区深部成矿规律与找矿预测研讨会,2021.6,大冶,湖北。

Chen G.. Multifractal Modeling in Wavelet Domain for Identifying Anomalies Caused by Deep Mineral Resources (Oral presentation). IAMG Annual Meeting, 2018, Olomonc & Prague, Czech.

Chen G.. Mineral Potential Mapping in Covered Area Using Scaling Analysis of Geophysical and Geochemical Data (Oral presentation). 2018 Sino-Italian International Cooperation and Exchange & Advancements in Gravity and Magnetic Technology Seminar Programme. 2018. Wuhan, China. 

Chen G., Cheng Q.. Singularity theories for mapping geochemical anomalies based on wavelet analysis (Oral presentation). IAMG Annual Meeting, 2015, Freiberg, German.

Chen G., Cheng Q., Liu T.. Singularity analysis of potential fields to enhance weak anomalies  (Poster presentation). AGU Fall Meeting, 2013, San Francisco, American.


  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 大数据矿产资源预测
  • 深时地学大数据与重大地质事件
  • 智能地球物理解译与三维地质建模
  • 背景噪声地震、重磁勘探方法