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Title: Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Journal Article · · Earth-Science Reviews
 [1];  [2];  [3];  [1];  [1];  [1];  [4]; ORCiD logo [5];  [6];  [6];  [7]
  1. Jilin University, Changchun (China)
  2. Jilin University, Changchun (China); Qingdao University of Science and Technology (China)
  3. Waseda University, Shinjuku (Japan)
  4. King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)
  5. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  6. New Mexico State University, Las Cruces, NM (United States)
  7. University of Cincinnati, OH (United States)

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
3016115
Report Number(s):
LA-UR--25-29869; 10.1016/j.earscirev.2026.105411
Journal Information:
Earth-Science Reviews, Journal Name: Earth-Science Reviews Vol. 275; ISSN 0012-8252
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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