Mr. Lijie Cui | Geosciences | Best Researcher Award
Mr Lijie Cui , China University of Petroleum , China.
Mr. Cui Lijie π is a skilled geoscientist and researcher specializing in seismic fault detection and Geological modeling π°οΈ. Currently serving at the China University of Petroleum-Beijing at Karamay π«, she brings over a decade of field and research experience. With advanced expertise in U-Net modeling and fault architecture visualization π»πͺ¨, her contributions to 3D fault detection and deformation simulations are impactful. Cui has previously led projects at Beijing UltraDo Resources Technology Co. Ltd. and contributed as a technician at Henan Coalbed Methane Development Co. Ltd. She is a recipient of notable funding programs including the prestigious βTianchi Talentsβ award π .
Professional Profile
Scopus
Orcid
Education & ExperienceΒ
π Education
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π PhD in Geosciences β China University of Petroleum, East China (2018β2022)
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π Masterβs Degree β Yangtze University, School of Geosciences (2009β2012)
πΌ Experience
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π« China University of Petroleum-Beijing at Karamay (2022βPresent) β Faculty Member
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π§ͺ Beijing UltraDo Resources Technology Co., Ltd. (2013β2018) β Project Leader, Geological Research
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π§ Henan Coalbed Methane Development Co., Ltd. (2012β2013) β Technician
Summary Suitability
Dr. Cui Lijie is a standout candidate for the Best Researcher Award, bringing over a decade of applied geoscientific research experience, with significant contributions to fault detection, seismic data interpretation, and numerical simulations in complex geological formations. With a demonstrated trajectory of academic and industrial achievements, Dr. Cui has emerged as a leading researcher in the integration of machine learning with geophysical methodologies.
Professional DevelopmentΒ
Cui Lijieβs professional journey is marked by continuous development through applied research and technical leadership ππ§ . She advanced from technician roles to becoming a leading project head in geological comprehensive research π§. Her PhD enhanced her technical toolkit in geoscientific computing and modeling π₯οΈ. Actively involved in academic publishing π and funded by national research initiatives π°, Cui regularly contributes to cutting-edge advancements in seismic fault detection. Her participation in programs like the “Tianchi Talents” signifies her growing influence in China’s geoscience community π. She remains engaged in innovation and training the next generation of petroleum geoscientists.
Research Focus
Cui Lijie focuses her research on computational geosciences, particularly in 3D seismic fault detection, fault zone architecture, and numerical geological modeling π§ π. Leveraging AI and deep learning frameworks like U-Net π€, she designs multi-scale feature fusion models to improve subsurface fault interpretation. Her work addresses challenges in resource exploration and tectonic deformation simulation using advanced numerical techniques ππ°οΈ. Her interests also span fault growth mechanisms, hybrid attribute imaging, and seismic data interpretation. This research contributes greatly to oil and gas exploration efficiency and tectonic safety π’οΈπ, positioning her work at the intersection of geoscience and intelligent modeling.
Awards & Honors
π Tianchi Talents Program
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Awarded by the Xinjiang Uygur Autonomous Region for outstanding academic contributions π
ποΈ Research Grant β China University of Petroleum-Beijing at Karamay
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Received institutional research funding for scientific innovation in petroleum geosciences π¬
Publication Top Notes
1. MS-Unet: A Multi-Scale Feature Fusion U-Net for 3D Seismic Fault Detection
π
Published: 2025-06-23
π Journal: Processes
π DOI: 10.3390/pr13071976
π₯ Contributors: Lijie Cui, Yawen Huang, Yuxi Niu, Hongyan Cui, Ye Tao, Longlong Qian, Jiaqi Zhao
πΉ 2. Numerical Simulation of the Deformation of the Hutubi Anticline in the Southern Margin of the Junggar Basin
π
Published: 2025-03-18
π Type: Preprint
π DOI: 10.5194/egusphere-egu25-4669
π₯ Contributors: Lijie Cui, Yongrui Chen, Yawen Huang, Yuxi Niu, Ye Tao, Ying Liu, Zening Chen
πΉ 3. 3D Fault Identification Based on Improved U-Net with Multi-Scale Feature Fusion
π
Published: 2025-03-15
π Type: Preprint
π DOI: 10.5194/egusphere-egu25-16619
π₯ Contributors: Yawen Huang, Lijie Cui, Yuxi Niu, Ye Tao, Ying Liu, Yongrui Chen
πΉ 4. Insights into Fault Zone Architecture and Growth Based on Enhanced Image of Fault Zone Arrays Using Hybrid Attributes
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Published: 2025-01-20
π Type: Preprint
π DOI: 10.5194/egusphere-egu24-3512
π₯ Contributors: Lijie Cui, Dandan Dong, Yawen Huang
πΉ 5. Enhanced Interpretation of Strike-Slip Faults Using Hybrid Attributes: Advanced Insights into Fault Geometry and Relationship with Hydrocarbon Accumulation in Jurassic Formations of the Junggar Basin
π
Published: 2022-01
π Journal: Journal of Petroleum Science and Engineering
π DOI: 10.1016/j.petrol.2021.109630
π₯ Contributors: Lijie Cui, Kongyou Wu, Qiang Liu, Di Wang, Wenjian Guo, Yulei Liu, Guanhua Xu
πΉ 6. Characterizing Subsurface Damage Zones From 3D Seismic Data Using Artificial Neural Network Approach
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Published: 2021
π Conference: 82nd EAGE Annual Conference & Exhibition
π DOI: 10.3997/2214-4609.202113327
π₯ Contributors: L. Cui, K. Wu
πΉ 7. Distribution of MidβDeeply Buried SandβBodies and Their Hydrocarbon Significance at Basin Margins: Case Study of the Paleogene in the Eastern Liuzan Area of the Nanpu Sag, Bohai Bay Basin, China
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Published: 2021-08
π Journal: Acta Geologica Sinica β English Edition
π DOI: 10.1111/1755-6724.14782
π ISSN: 1000-9515 / 1755-6724
π₯ Contributors: Lijie Cui, Shikai Jian, Boming Zhang, Xiongju Xie, Liang Li
Conclusion
Dr. Cui Lijie exemplifies the spirit of the Best Researcher Award, through a strong blend of academic excellence, practical innovation, and interdisciplinary insight. Their integration of advanced computational techniques into seismic interpretation and structural geology marks a transformative shift in the field. With a growing portfolio of high-impact publications and funded research, Dr. Cui is not only advancing geoscientific research but also setting benchmarks for future scholars and industry practitioners alike.