Two students from SmartOilfiel's research group won the Outstanding Dissertation of China University of Petroleum (East China), among which Jiang Yunqi won the honor of "2023 Excellent Doctoral Dissertation of China University of Petroleum", and Wang Xiaoya won the honor of "2023 Excellent Master's Thesis of China University of Petroleum".

 Jiang Yunqi's graduation thesis is entitled "Research on the Analysis of Inter-well Connectivity in Water-flooded Reservoirs Based on Explainable Machine Learning Model", which introduces the physical equation of seepage in the construction process of the machine learning model, and realizes the efficient, fast and interpretable inter-well connectivity analysis of water-flooding reservoirs by considering the interrelationship characteristics of injection-production units and the connectivity analysis experience of the inherited history, which was completed under the joint guidance of Prof. Kai Zhang and Prof. Jian Wang.

 In view of the shortcomings of traditional reservoir numerical simulation production prediction, which involves many grids, large computational amount and long time, a framework for automatic reservoir history fitting based on integrated data-driven model is proposed, which turns the fitting problem into a single-objective optimization problem and uses intelligent optimization algorithm to find the optimal reservoir model parameters, which was completed under the guidance of Professor Kai Zhang.

 It is hoped that the students studying in the school will take this as an example, keep upright, innovate, and go far.