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Dr Jimmy Li

Postdoctoral Research Fellow

School of Mechanical and Mining Engineering
Faculty of Engineering, Architecture and Information Technology
jimmy.li@uq.edu.au

Overview

Dr Jimmy Xuekai Li is a postdoctoral research fellow at the School of Mechanical and Mining Engineering. He attended China University of Petroleum, where he received a bachelor's degree in petroleum engineering in 2007. He then joined Halliburton Energy Service Company and worked in various technical and management roles in the formation evaluation and directional drilling department. After ten years working in the oil and gas industry (2007-2017), he came to Curtin University (Western Australia) to pursue a higher degree by research and completed his PhD degree in formation evaluation and geophysics in 2021. His PhD thesis resulted in the new theory of wettability-affected wave propagation in fluid-saturated porous media, from which the experimental method was developed to explore rock wettability by using elastic wave measurement. This research has laid a solid theoretical and experimental foundation for the development of multiple-frequency sonic logging tools for measuring formation wettability.

After joining UQ in 2021, Dr Li's research focused on the field of theoretical and experimental study in rock mechanics and geotechnical for underground mining and drilling engineering. In 2022, he assisted to establish the quality management system (QMS) for the Mechanical Testing Laboratory which was granted NATA accreditation on the rock mechanics measurement.

He has a broad interest in geotechnical engineering with special expertise in machine learning, computer vision applications and numerical modelling of geomechanics and underground excavation stability analysis. He also has strong laboratory experience in rock physics, rock strength, wettability and weathering studies.

Research Interests

  • Machine Learning in Geoscience
    Non-linear correlation, Image analysis, Geology, Lithology, Geotechnical properties, UCS, Young's modulus, RQD, CMRR.
  • Rock Physics
    Applied geophysics, Seismic, Microseismic, Ultrasonic wave propagation, Nuclear Magnetic Resonance, Micro-CT of porous media.
  • Weathering in Sedimentary Rock
    Weathering experiment, Fluid-rock interactions, Temperature and humidity effect, Slake durability, Dispersion test, Non-destructive test, Time-lapse monitoring, Rehabilitation.
  • Petrophysics and Formation Evaluation
    Geophysical log interpretation, Reservoir characterization, Core analysis, Laboratory measurements (porosity, permeability, density, pore size distribution, multiphase fluids flow and displacement, wettability, sonic, resistivity, PVT properties).
  • Drilling Engineering
    Directional drilling, Drilling optimisation, Drilling in hostile environments (HPHT), Geosteering, Borehole stability, Formation test, Measurement-While-Drilling, and Logging-While-Drilling in conventional, unconventional, and offshore fields.

Qualifications

  • Doctor of Philosophy of Geophysics
  • Bachelor of Petroleum Engineering, China University of Petroleum

Publications

  • Journal Article: Automatic coal mine roof rating calculation using machine learning

    Li, Jimmy Xuekai, Tsang, Matt, Zhong, Ruizhi, Esterle, Joan, Pirona, Claire, Rajabi, Mojtaba and Chen, Zhongwei (2023). Automatic coal mine roof rating calculation using machine learning. International Journal of Coal Geology, 274 104292, 1-14. doi: 10.1016/j.coal.2023.104292

  • Journal Article: Wettability-dependent wave velocities and attenuation in granular porous media

    Li, Jimmy Xuekai, Rezaee, Reza, Müller, Tobias M., Madadi, Mahyar, Ma, Rupeng and Sarmadivaleh, Mohammad (2022). Wettability-dependent wave velocities and attenuation in granular porous media. Geophysics, 87 (4), MR177-MR187. doi: 10.1190/geo2021-0279.1

  • Conference Publication: UCS prediction by group-based machine learning method

    Li, Jimmy Xuekai, Tsang, Matt, Giese, Stephen, Zhong, Ruizhi, Esterle, Joan, Pirona, Claire, Rajabi, Mojtaba and Chen, Zhongwei (2022). UCS prediction by group-based machine learning method. Resource Operators Conference, Virtual, 10-11 February 2022. Wollongong, NSW, Australia: University of Wollongong and University of Southern Queensland.

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Grants

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Publications

Journal Article

Conference Publication

  • UCS prediction by group-based machine learning method

    Li, Jimmy Xuekai, Tsang, Matt, Giese, Stephen, Zhong, Ruizhi, Esterle, Joan, Pirona, Claire, Rajabi, Mojtaba and Chen, Zhongwei (2022). UCS prediction by group-based machine learning method. Resource Operators Conference, Virtual, 10-11 February 2022. Wollongong, NSW, Australia: University of Wollongong and University of Southern Queensland.

  • Path dispersion of elastic waves in granular matter

    Li, Jimmy X., Rezaee, Reza, Müller, Tobias M., Madadi, Mahyar, Ma, Rupeng and Sarmadivaleh, Mohammad (2021). Path dispersion of elastic waves in granular matter. SEG/SPWLA 2020 Workshop: 7th Workshop on Porous Media: Structure, Flow and Dynamics, Online, 2–3 December 2020. Tulsa, OK United States: Society of Exploration Geophysicists. doi: 10.1190/prmd2020-05.1

  • Wettability dependent P-wave scattering and velocity saturation relation in granular medium

    Li, Jimmy X., Rezaee, Reza, Müller, Tobias M., Madadi, Mahyar and Sarmadivaleh, Mohammad (2020). Wettability dependent P-wave scattering and velocity saturation relation in granular medium. Society of Exploration Geophysicists Annual Meeting (SEG20), Houston, TX, United States, 11-16 October 2020. Tulsa, OK United States: Society of Exploration Geophysicists. doi: 10.1190/segam2020-3427195.1

  • Advanced geosteering technology promotes the accuracy of well placement in the thin reservoirs of China mature oilfield

    Li, Hongsheng, Xia, Guofeng, Xu, Daicai, Li, Xuekai, Calleja-Djefel, Bronwyn and Liu, Youquan (2016). Advanced geosteering technology promotes the accuracy of well placement in the thin reservoirs of China mature oilfield. SPE/IADC Middle East Drilling Technology Conference and Exhibition, Abu Dhabi, United Arab Emirates, 26–28 January 2016. Bellingham, WA United States: Society of Petroleum Engineers. doi: 10.2118/178167-MS

Grants (Administered at UQ)

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ORCID: 0000-0002-5825-0673

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