My research focuses on knowledge-driven reservoir modeling and intelligent production optimization. I integrate domain knowledge, data, and physical constraints to build hybrid models for reservoir analysis and decision support. Current work explores RAG- and Agent-based frameworks to enhance reservoir management and improve recovery efficiency.

• Identification of water flooding advantage seepage channels based on meta-learning. C. Dong, B. Zhang, et al. Energies, 16(2), (2023)
• Study on stratified water injection in ultra-high water cut reservoir based on seepage resistance coefficient. C. Dong, B. Zhang, T. Wu, E. Yang Contemporary Chemical Industry, 50(10), 2513–2516, (2021)

• Visiting Student, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, Sep. 2025 – Present
• Ph.D. Candidate, Petroleum and Natural Gas Engineering, China University of Petroleum (East China), Qingdao, China, 2023–Present
• M.S., Petroleum and Natural Gas Engineering, Northeast Petroleum University, Daqing, China, 2023
• B.S., Computer Science and Technology, Xuhai College, China University of Mining and Technology, Xuzhou, China, 2020

• Society of Petroleum Engineers (SPE), Member since 2021

• Excellent Graduate, Northeast Petroleum University, Jul. 2023
• Second Prize, 19th China Graduate Mathematical Contest in Modeling, Jan. 2023
• Third Prize, 18th China Graduate Mathematical Contest in Modeling, Dec. 2021
• Second Prize, 2nd China Ocean Engineering Design Competition, Nov. 2020

• Physical Science and Engineering Division (PSE)

• China University of Petroleum (East China)