Hydrogen storage in subsurface reservoirs has received a lot of interest as a solution to seasonal demand and supply imbalances. Hydrogen is an excellent energy carrier since its combustion process produces only energy and water as output and can be employed as an energy storage medium. During the hydrogen combustion process, the gravimetric energy content approaches 140 MJ/kg, which is significantly higher than natural gas’s 54 MJ/kg. As a result, the high energy density can be particularly beneficial because hydrogen is used as a reactant in a wide range of chemical processes. Underground hydrogen storage has various problems, including microbial communities that impact hydrogen storage quality. The study presents a complete qualitative analysis combined with an unsupervised learning approach for microbial effect assessments, which was shown on a benchmark reservoir case from the Ahuroa storage site. The findings show that Methanobacteria and Methanosarcinia have a significant impact on the hydrogen storage reservoir at the class level. The unsupervised k-means clustering approach highlighted the relationships between the various class-level microbiological components, demonstrating that while there is a clear distinction between lower and higher read count domains throughout the wells, this may not be reflected for individual wells. Thus, considering heterogeneity as well as differences in hydrogen quality deterioration is critical for efficient hydrogen storage.