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Hung Vo Thanh

Assistant Professor

Waseda University

Japan

Research Interests

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Articles (20)

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2026

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Collaborators (6)

Kenneth Carroll

Assoc. Professor

University of New Mexico

UNITED STATES

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Mohamad R. Soltanian

Full Professor of Hydrogeology

University of Cincinnati

UNITED STATES

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Huichao Yin

University of New Mexico

UNITED STATES

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Zhenxue Dai

Staff Scientist

Los Alamos National Laboratory

UNITED STATES

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Baehyun Min

Associate Professor

Ewha Womans University

SOUTH KOREA

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Suryeom Jo

Senior Researcher

Korea Institute of Geoscience and Mineral Resources

SOUTH KOREA

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Hung Vo Thanh

Research Interests

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Articles (20)

Impacts of operational controls on hydrogen recovery factor in a depleted gas reservoir for underground hydrogen storage

Artificial intelligence-driven monitoring network optimization under reservoir uncertainty for underground hydrogen storage

Assessment of CO2 storage and enhanced oil recovery performance under limited-sample conditions

Molecular Understanding of Hydrogen Behavior in Moist Kerogen Matrix with Residual Methane Presence: Implications for Underground Hydrogen Storage

Toward Real-Time Digital Twins for CO₂ Storage: Graph Neural Network Ensembles for Multi-physics Forecasting and Risk Quantification

Advances in Underground Gas Storage: A Review of Current Practices and Future Prospects

Deep learning schemes for predicting deliverability from different underground gas storage reservoir types

Physics informed machine learning for prediction hydrogen solubility in aqueous solution to implication for underground hydrogen storage formations

Second‐Order Degradation Modeling and Multiscale Feature Fusion for High‐Fidelity Segmentation of Low‐Quality Digital Rock Images

An integrated framework of deep learning and entropy theory for enhanced high-dimensional permeability field identification in heterogeneous aquifers

Hybrid machine-learning and optimization models for precise determination of pore pressure changes in subsurface reservoirs

Interpretable knowledge-guided machine learning for prediction wettability hydrogen-rocks/minerals-brine system in underground hydrogen storage project

Enhanced prediction and uncertainty analysis for hydrogen production rate in depleted oil and gas reservoirs using advanced machine learning techniques

Revolutionizing hydrogen storage: Predictive modeling of hydrogen-brine interfacial tension using advanced machine learning and optimization technique

Fractal and NMR based characterizations of multi-scale pore structure alterations in tight sandstones due to scCO2-water–rock interactions

Low-carbon advancement through cleaner production: A machine learning approach for enhanced hydrogen storage predictions in coal seams

Committee machine learning: A breakthrough in the precise prediction of CO2 storage mass and oil production volumes in unconventional reservoirs

Carbon dioxide storage and cumulative oil production predictions in unconventional reservoirs applying optimized machine-learning models

Modeling the thermal transport properties of hydrogen and its mixtures with greenhouse gas impurities: A data-driven machine learning approach

Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids

Collaborators (6)

Kenneth Carroll

Mohamad R. Soltanian

Huichao Yin

Zhenxue Dai

Baehyun Min

Suryeom Jo

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