A novel robust optimization framework based on surrogate modeling for underground hydrogen storage in depleted natural gas reservoirs
This work develops a surrogate-model-based robust optimization framework for underground hydrogen storage in depleted natural gas reservoirs, targeting computationally efficient evaluation of reservoir and operational uncertainty.
I am a PhD candidate in Energy Resources and Petroleum Engineering at King Abdullah University of Science and Technology (KAUST). My doctoral research focuses on numerical modeling of coupled compositional multiphase flow and microbial reactive transport for underground hydrogen storage (UHS), with emphasis on thermodynamics, reservoir simulation, and computational efficiency.
Before my PhD, I worked for seven years at CNOOC Tianjin as a formation evaluation and logging engineer. This combination of field-scale formation evaluation experience and reservoir simulation research shapes my interest in integrated subsurface characterization, modeling, and decision support.