Novel insights into extraction and utilization of subsurface free natural hydrogen present in rocks: Bibliometric analysis, opportunities, challenges and possible solutions

Muhammad Imran Rashid*, Abdur Rehman, Zohaib Atiq Khan*, Muhammad Athar, Mahboob Ahmed Aadil, Talib Elahi Butt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Phasing out fossil fuels is crucial for combating climate change, and hydrogen offers a viable carbon-free alternative. Natural hydrogen from the Earth's crust could significantly aid the transition to renewable energy, yet comprehensive analysis on its extraction remains limited. This study reviews existing research, identifies knowledge gaps, and explores potential reserves and ongoing projects. Former Soviet Union countries have 223 hydrogen discoveries, and rift zones show strong potential for exploration, with the highest hydrogen concentrations (33.7–96.3%), while salt deposits have the lowest (1.1–34.6%). Key challenges include hydrogen identification, well management, leakage risks, and explosion hazards. Areal Location of Hazardous Atmosphere (ALOHA) simulations assess these risks, showing wind speed significantly reduces outdoor hydrogen concentration, while increasing borehole diameter raises it. Simulations for the Bourakebougou (Mali) hydrogen well indicate accidental release concentrations remain below explosive limits. Statistical Experimental Design reveals that larger boreholes increase hydrogen concentration, while higher gas mass, temperature, and wind speed decrease it. These calculations help determine safe distances for preventing explosions. Machine learning has accelerated ALOHA calculations from 40 minutes to seconds, enabling real-time gas concentration estimates. These findings support safer and more efficient natural hydrogen exploration, addressing both opportunities and risks associated with its extraction.
Original languageEnglish
Pages (from-to)958-972
Number of pages15
JournalInternational Journal of Hydrogen Energy
Volume138
Early online date21 May 2025
DOIs
Publication statusPublished - 16 Jun 2025

Keywords

  • ALOHA
  • Bibliometric analysis
  • Challenges and solutions
  • Machine learning
  • Natural hydrogen
  • Natural hydrogen reserves

Cite this