About
Hongsheng Wang is a Research Fellow at the Bureau of Economic Geology within the Jackson School of Geosciences at The University of Texas at Austin. His research focuses on advancing subsurface energy technologies through interdisciplinary approaches combining geoscience, engineering, and machine learning. Key areas include geological carbon storage, underground hydrogen storage, reservoir simulation, and fracture mechanics.
His work emphasizes innovative applications of machine learning for challenges such as CO2 plume migration forecasting, parameterization of 3D saturation data, and fracture conductivity analysis. He also investigates leakage mitigation strategies in hydrogen storage systems and the role of permeability heterogeneity in subsurface processes.
Publications highlight contributions to microfluidic experiments, porous media dynamics, and AI-driven reservoir modeling. Current projects involve surrogate models for large-scale simulations and dimension reduction techniques to enhance computational efficiency in carbon storage assessments.
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