Underground hydrogen storage: A recovery prediction using pore network modeling and machine learning-Reference-Cited by-同舟云学术

Underground hydrogen storage: A recovery prediction using pore network modeling and machine learning

Published:2024-02 Issue: Volume:357 Page:130051
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Zhao Qingqi,Wang Hongsheng,Chen Cheng^ORCID

Funder

Stevens Institute of Technology

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference32 articles.

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3. Impact of experimentally measured relative permeability hysteresis on reservoir-scale performance of underground hydrogen storage (UHS);Bo;Int J Hydrogen Energy,2023

4. Interfacial tensions of (H2O + H2) and (H2O + CO2 + H2) systems at temperatures of (298–448) K and pressures up to 45 MPa;Chow;Fluid Phase Equilib,2018

5. Department of Earth Science and Engineering, Imperial College. pnflow—Classical pore-network extraction and flow simulation. Imperial College London; 2019. https://github.com/ImperialCollegeLondon/pnflow.

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