Seminar

Fractured rocks provide preferential fluid pathways due to the lower hydraulic resistance in comparison with the surrounding host rock and transport most of the solute and thermal energy. Understanding fracture distribution and heat transport in a fracture network are crucial to predict possible fluid dynamics and heat extraction, optimize the heat extraction, and manage reservoir conditions with respect to dynamic changes. Consequently, fracture network characterization and design optimization hold profound significance for addressing earth, energy, and environmental challenges. Here, we present a mathematical framework to characterize the fracture network and develop efficient machine learning based optimization algorithms for the earth, energy & environmental problems. The research aims to establish a solid basis for fractured systems, e.g., fractured aquifer, enhanced geothermal system and fractured oil reservoir, and sheds light on the model management strategies of data-driven optimization in the areas of fracture inversion and future decision making with numerical simulation involved.

Additional information: Mr. Guodong CHEN, u3008598@connect.hku.hk