Zhilei Han

PhD Candidate | Reservoir Simulation | Formation Evaluation & Petrophysics

King Abdullah University of Science and Technology (KAUST)

Profile

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.

Education

PhD, Energy Resources and Petroleum Engineering

2022-01-01
2026-12-31

King Abdullah University of Science and Technology (KAUST)

Expertise

Reservoir Simulation Underground Hydrogen Storage Compositional Multiphase Flow Microbial Reactive Transport Formation Evaluation & Petrophysics Scientific Machine Learning

Research & Technical Focus

Integrated subsurface modeling

My work combines reservoir simulation, thermodynamics, reactive transport, scientific machine learning, and formation evaluation.

Underground Hydrogen Storage

Reservoir-scale modeling of injection, storage, production, phase behavior, and microbial conversion of hydrogen.

Reservoir simulation H2 storage Cyclic operation

Reactive-Compositional Simulation

Coupling multicomponent multiphase flow with microbial reactive transport and comparing numerical coupling strategies.

Compositional flow Reactive transport FIM vs SNI

Phase Equilibrium & Scientific ML

Physics-based and deep-learning-assisted methods for accelerating phase stability analysis and flash calculations.

Flash calculation Thermodynamics Deep learning

Formation Evaluation & Petrophysics

Seven years of field experience in well logging and formation evaluation, connecting reservoir characterization with modeling decisions.

Well logging Formation evaluation Petrophysics
Selected Publications

Selected work on underground hydrogen storage, coupled simulation, and data-driven reservoir modeling.

Recent Highlights
2026 · Presented Deep Learning-Assisted Flash Calculations for Underground Hydrogen Storage at the SPE Europe Energy Conference and Exhibition.
2025 · Published surrogate-model-based robust optimization research for underground hydrogen storage in depleted natural gas reservoirs.
2025 · Presented coupled compositional flow and microbial reactive-transport simulation work at the SPE Reservoir Simulation Conference.
2024 · Received an InterPore Invited Student Paper Award for UHS optimization research.