Molecular diagnosis of indicator microorganisms in typical gas fields: a case study of Hangjinqi Gas Field

Abstract:

[Objective] Microbial prospecting for oil and gas, characterized by high resolution, high signal-to-noise ratio, minimal environmental interference, low costs, and short time consumption, garners increasing attention from exploration experts. However, in most cases, microbial prospecting is based on laboratory culture and analysis, which cannot accurately and comprehensively reflect the in-situ dynamic changes of microbiota in oil and gas resources in the geological history. In this study, we compared the microbial community structure and developmental characteristics between the gas-producing zone and the background zone in Hangjinqi Gas Field, aiming to identify the surface microbial anomalies related to oil and gas. [Methods] We conducted the bacterial 16S rRNA gene sequencing for the soil samples collected from Xinzao and Shiguhao areas of Hangjinqi. Furthermore, we compared the microbial diversity, analyzed the impacts of physicochemical parameters on microbial distribution, and identified microbial anomalies. The co-occurrence network analysis was employed to explore the assembly process and functional composition of microbial community in the surface soil above the reservoir.[Results] In the Hangjinqi area, Actinobacteria and Proteobacteria were dominant, accounting for 72.47% of the total microbial abundance. The correlation analysis of environmental factors with microbial abundance showed that the distribution of microorganisms in this area was not significantly correlated with environmental factors. The microbial community structure presented significant differences between the gas-producing area and the background area. The co-occurrence network analysis of the gas-producing area revealed non-randomness and connectivity in the microbial community, indicating deterministic factors play a dominant role in the construction of microbial communities. Modular co-occurrence network analysis revealed the formation of specific functional modules within the microbial community, and different modules possibly served different functions. [Conclusion] By comparing the microbial diversity between the gas-producing and background area of Hangjinqi area, we identified the indicator genera in the gas-producing fields of Xinzao and Shiguhao. Furthermore, the co-occurrence network analysis identified Gemmatimonas, Solirubrobacter, Pseudonocardia, Brevibacillus, Aeromicrobium, and Nocardioides as the key taxa in the gas-producing area, which were associated with the main functional modules of carbon and nitrogen cycling and organic matter degradation, contributing to the degradation of hydrocarbons in the surface soil of the gas-producing area.