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Chunxiao Li

Master Tutor

Honors and Titles : 中国地质大学青年拔尖人才(A类)
Gender : Female
Date of Birth : 1990-10-10
Alma Mater : University of North Dakota, US
Education Level : Faculty of Higher Institutions
Degree : Doctoral Degree in Engineering
Status : Employed
School/Department : School of Earth Resources
Business Address : Building Wenhua , Room 617
Contact Information : lichunxiao@cug.edu.cn
Email :
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Personal Profile

Dr. Chunxiao Li, appointed researcher and a distinguished young talent (Class A) at China University of Geosciences (Wuhan). She completed her undergraduate and master's degrees in Geological Resources and Geological Engineering at China University of Petroleum (Beijing), and earned her Ph.D. in Geological Engineering from the University of North Dakota, USA.

In 2020-2021, she worked as a reservoir engineer at the  Energy & Environmental Research Center in the United States. Subsequently, she joined the School of Resources at China University of Geosciences (Wuhan).

Her main research areas include rock mechanics of unconventional oil and gas reservoirs, geological mechanics of carbon dioxide sequestration, and the application of artificial intelligence in unconventional oil and gas and new energy fields. During her overseas tenure, she participated in several research projects related to the development of unconventional oil and gas fields and geological storage of carbon dioxide.

In the past five years, she has published 23 papers, including 9 as the first or corresponding author. Among them, 8 are SCI papers published in important journals such as Rock Mechanics & Rock Engineering, Journal of Petroleum Science and Engineering, FUEL, and International Journal of Rock Mechanics and Mining Sciences. She has delivered oral and poster presentations at 8 international top academic conferences, and two of her papers have been recognized as ESI highly cited papers. As of August 2023, her research has been cited 835 times, and her H-index is 17. She serves as a reviewer for several international journals, including Fuel, Rock Mechanics & Rock Engineering, and the Journal of Petroleum Science and Engineering. She is a member of the International Petroleum Engineering Association and the China Rock Mechanics and Engineering Association.

Researchgate: Chunxiao Li (researchgate.net)

‪Google Scholar:  ‪Chunxiao Li‬ - ‪Google Scholar‬

Research Interest:

  • Reservoir Engineering

  • Rock Mechanics

  • Application of AI/Machine Learning on Geosciences and Petroleum Engineering

Potenial students:

Dr. Li's research group is always looking for motivated, talented master and PhD students and researchers. Please send your CV to  email for communication.  Email : lichunxiao@cug.edu.cn

Projects & Fund

  1. 二氧化碳对岩石微观力学性质劣化规律研究,第72批博士后面上基金项目,2022

  2. 阿拉斯加北部斜坡重油油藏聚合物驱的历史拟合和数值模拟 First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil EOR 美国能源部项目(Source: US. Department of Energy),2018-2020

  3. 富气提高采收率 BPOP – East Nesson Rich Gas EOR, 美国北达科他州项目,2020, EERC

  4. Aquistore 二氧化碳储存智能监测 Development of Intelligent Monitoring System (IMS) Modules for the Aquistore CO2 Storage Project, 美国能源部项目 ( Source: US. Department of Energy):11/2017-05/2018, EERC

  5. 美国能源部项目:内布拉斯卡州二氧化碳储存评估 Carbon Storage Assurance Facility Enterprise (CarbonSAFE ) in Nebraska, EERC

  6. 二氧化碳封存泄漏风险评估 Validation of National Risk Assessment Partnership (NRAP) Tools, 05/2017-12/2017, EERC


  1. Li, C., Wang, D., Kong, L., Ostadhassan, M., 2022. Estimation of Mechanical Properties of the Bakken Shales Through Convolutional Neural Networks. Rock Mechanics and Rock Engineering, 55, 1213-1225.

  2. Li, C., Wang, D., Kong, L., 2021a. Mechanical response of the Middle Bakken rocks under triaxial compressive test and nanoindentation. International Journal of Rock Mechanics and Mining Sciences 139, 104660.

  3. Li, C., Wang, D., Kong, L., 2021b. Application of Machine Learning Techniques in Mineral Classification for Scanning Electron Microscopy - Energy Dispersive X-Ray Spectroscopy (SEM-EDS) Images. Journal of Petroleum Science and Engineering 200, 108178.

  4. Li, C., Kong, L., Ostadhassan, M., Gentzis, T., 2019a. Nanoscale Pore Structure Characterization of Tight Oil Formation: A Case Study of the Bakken Formation. Energy & Fuels 33, 6008–6019.

  5. Li, C., Ostadhassan, M., Kong, L., Bubach, B., 2019b. Multi-scale assessment of mechanical properties of organic-rich shales: A coupled nanoindentation, deconvolution analysis, and homogenization method. Journal of Petroleum Science and Engineering 174, 80–91.

  6. Li, C., Ostadhassan, M., Abarghani, A., Fogden, A., Kong, L., 2019c. Multi-scale evaluation of mechanical properties of the Bakken shale. J Mater Sci 54, 2133–2151.

  7. Li, C., Ostadhassan, M., Gentzis, T., Kong, L., Carvajal-Ortiz, H., Bubach, B., 2018a. Nanomechanical characterization of organic matter in the Bakken formation by microscopy-based method. Marine and Petroleum Geology 96, 128–138.

  8. Li, C., Ostadhassan, M., Guo, S., Gentzis, T., Kong, L., 2018b. Application of PeakForce tapping mode of atomic force microscope to characterize nanomechanical properties of organic matter of the Bakken Shale. Fuel 233, 894–910.

Education Background

  • 2009.9 -- 2013.6

    中国石油大学(北京)       Geological resources and geological engineering       Undergraduate (Bachelor’s degree)

  • 2013.9 -- 2016.6

    中国石油大学(北京)       Geological resources and geological engineering       With Certificate of Graduation for Study as Master's Candidates

  • 2016.8 -- 2020.8

    University of North Dakota       Geological resources and geological engineering       Doctoral Degree

Work Experience

  • 2022.5 -- Now

    中国地质大学(武汉)      资源学院      特任研究员

  • 2020.9 -- 2021.10

    Energy & Environmental Research Center (US)      Reservoir Engineer

Other Contact Information

  • email :

Research Focus

  • Development of unconventional oil and gas
  • Rock Mechanics
  • Application of AI/Machine Learning on geosciences and petroleum engineering