Natural hydrogen exploration within western European and eastern Mediterranean ophiolites and ultramafic complexes

蛇绿岩 超镁铁质岩 山体 地质学 自然(考古学) 地中海气候 地球科学 地球化学 古生物学 地理 构造学 考古
作者
Frédéric‐Victor Donzé,Nicolas Lefeuvre,Laurent Truche,Yao Yan,Ivan Vujevíc,Hugo Dutoit
出处
期刊:Geochemistry-exploration Environment Analysis [Zoological Society of London]
标识
DOI:10.1144/geochem2024-043
摘要

This study investigates the potential for natural hydrogen (H 2 ) production across western continental Europe and eastern Mediterranean, focusing on ophiolitic and ultramafic massifs. Our approach integrates geophysical, geological, and geochemical parameters to identify regions where serpentinization could be a key natural process for H 2 generation. Based on these parameters, we have developed a comprehensive probabilistic model to assess the likelihood of abiotic H 2 production at depth. This model incorporates parameters such as geothermal heat flux, magnetic anomalies, and existence of hyperalkaline springs, each weighted according to their possible influence on serpentinization. This weighting is derived from a case study in Albania, where H 2 degassing has been observed. The model has been applied to several ophiolitic and ultramafic complexes, including the Ordenes (Spain), the Alter-do-Chão (Portugal), the Ronda (Spain), the North-Western Alps, the Apennine (Italy), the Dinarides, the Hellenides (e.g. Vourinos and Pindos ophiolites in Greece), Troodos (Cyprus), Kızıldağ, Bassit, Hatay (Turkey), and Leka (Norway). A ranking has been proposed in terms of the probability of finding H 2 at these locations. Subsequently, the model was applied to the well-documented Samail ophiolite in Oman, where H 2 seepages are observed, in order to underscore the potential need for region-specific adaptations of the model. While the model provides a framework for H 2 -targeted exploration, it also acknowledges its current limitations, emphasizing the necessity for continuous refinement and validation against new observations. The inherent uncertainties in geological processes call for a dynamic modeling strategy to accurately predict and explore geological hydrogen resources.
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