Zhilei Han

Zhilei Han

Reservoir Simulation | Formation Evaluation & Petrophysics

King Abdullah University of Science and Technology (KAUST)

Profile

I am a PhD candidate in Petroleum Engineering at King Abdullah University of Science and Technology (KAUST), focusing on computational reservoir simulation and AI modeling.

Before that, I worked for 7 years as a Senior Petrophysicist at China National Offshore Oil Corporation (CNOOC), specializing in formation evaluation, reservoir characterization, and reserves estimation.

Education

Ph.D., Energy Resources and Petroleum Engineering

2022-09-01
2026-12-31

King Abdullah University of Science and Technology (KAUST)

M.S., Petrophysics

2012-09-01
2015-07-01

China University of Petroleum (East China)

B.S., Exploration Technology and Engineering

2008-09-01
2012-07-01

China University of Petroleum (East China)

Expertise

Reservoir Simulation Machine/Deep Learning Formation Evaluation & Petrophysics Underground Gas Storage

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.

Zhilei Han, Bicheng Yan (2026). Deep Learning-Assisted Flash Calculations for Underground Hydrogen Storage. SPE Europe Energy Conference and Exhibition.
DOI
Zhilei Han, Zeeshan Tariq, Bicheng Yan (2025). A novel robust optimization framework based on surrogate modeling for underground hydrogen storage in depleted natural gas reservoirs. InterPore Journal, 2(3), IPJ250825-6.
DOI
Zhilei Han, Bicheng Yan (2025). Numerical Simulation of Coupling Compositional Two-Phase Flow and Micro-Bio Reactive Transport in Underground Hydrogen Storage. SPE Reservoir Simulation Conference, Galveston, Texas, USA.
DOI
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.