Dr. Jinxin Cao, China University of Petroluem, Beijing, China
Jinxin Cao is a Doctor of Engineering and a PhD student at the China University of Petroleum, Beijing. Since joining the institution in August 2018, he has focused on the integration of artificial intelligence with energy and mining, specializing in computer vision in microfluidics, signal processing, and time series analysis. His research covers a broad spectrum, including tight oil development, microfluidics, interfacial mechanisms, and numerical simulation. Cao has led over 15 major projects, including special projects, joint fund integrations, and comprehensive scientific research initiatives. He has achieved significant breakthroughs in microfluidic image processing, elucidating interface evolution laws and mechanical mechanisms, which are pivotal for advancing “Lab on a Chip” technologies. Additionally, he has applied signal processing techniques to petroleum engineering, utilizing empirical mode decomposition and Hilbert-Huang transforms to analyze and predict oil well production. His contributions include 11 published papers (8 indexed by SCI/EI), 5 granted patents, and 6 accepted articles. Cao has also earned 20 awards in science, technology, and competitions, highlighting his impact in his field
Professional Profile:
Summary of Suitability for Best Researcher Award:
Jinxin Cao is currently pursuing a PhD at China University of Petroleum, Beijing (CUPB) and has been a part of the institution since August 2018. His research focuses on artificial intelligence applications in petroleum engineering, including computer vision in microfluidics, signal processing, and time series analysis. With a total experience of 6 years at CUPB, he has made significant contributions to various interdisciplinary fields.
Education:
- Doctor of Engineering
Institution: China University of Petroleum, Beijing
Specialization: Energy and Mining
Research Focus: Computer Vision in Microfluidics
Work Experience:
- Position: Doctor of Engineering
Department: College of Petroleum Engineering
Institution: China University of Petroleum, Beijing
Duration: August 2018 – Present
Experience: Jinxin Cao has been engaged in artificial intelligence with a focus on computer vision in microchips, signal processing, time series processing, tight oil development, microfluidics, and interfacial mechanisms. He has been involved in over 15 major projects, including special projects, joint fund integration projects, and comprehensive scientific research endeavors. His work has led to significant breakthroughs in microfluidic image processing, uncovering interface evolution laws and mechanical mechanisms in microfluidic processes using computer vision methods. Additionally, Cao has applied signal processing techniques to petroleum engineering, utilizing empirical mode decomposition and Hilbert-Huang transform to analyze oil well production and predict future production using artificial intelligence methods.
Academic Achievements:
- Publications: 11 academic papers, 8 indexed by SCI/EI
- Patents: 5 invention patents
- Accepted Articles: 6
- Awards: 20 science and technology or competition awards at various levels
Publication top Notes:
Microscopic experiment on efficient construction of underground gas storages converted from water-invaded gas reservoirs
Identification of Polymer Flooding Flow Channels and Characterization of Oil Recovery Factor Based On U-Net
Experimental investigation on the effect of interfacial properties of chemical flooding for enhanced heavy oil recovery
Study on reservoir damage characteristics of tight oil oxygen reduction air huff and puff development
Adaptability and enhanced oil recovery performance of surfactant-polymer flooding in inverted seven-spot well pattern
Research on the Adaptability of SP Flooding in Sand-Gravel Mixture Reservoir Based on the Inverted Seven-Spot Well Pattern