典型气田的指示微生物异常分子诊断:以杭锦旗气田为例

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

摘要:

【目的】油气微生物勘探技术因其多解性小、信噪比高、受环境影响小和经济快速的特点，日益受到勘探者的重视。然而，多数微生物勘探应用是基于非原位的实验室培养分析，不能准确而全面反映漫长地质历史过程中油气资源微生物的原位动态变化规律。本研究以杭锦旗气田为例，分析气区上方和背景区的微生物群落结构和发育特征差异，识别地表油气微生物异常。【方法】对采集自杭锦旗的新召和什股壕大营圈闭土壤样本中细菌16S rRNA基因进行测序，结合理化参数，比较微生物多样性差异，分析理化参数对微生物分布的影响，识别微生物异常。通过共生网络分析，探索气藏上方地表土壤中微生物群落构建过程和功能组成。【结果】群落组成分析发现在杭锦旗地区，放线菌门和变形菌门是主要的微生物类群，占菌落总体丰度的72.47%，理化参数相关性分析表明该地区的微生物分布与理化参数无明显相关关系。群落多样性分析显示，气区和背景区的群落结构存在显著差异。共生网络分析发现气区微生物群落呈现出非随机性和连通性，表明确定性因素在微生物群落构建中占主导作用。模块化的共发生网络揭示微生物群落形成了特定的功能模块，不同模块的节点可能具有不同的功能。【结论】通过对杭锦旗气区和背景区的微生物多样性分析发现了新召和什股壕气区的指示菌属。根据对杭锦旗气区的共生网络分析，发现关键指示类群为出芽单胞菌属、土壤红色杆形菌属、假诺卡氏菌属、短芽孢杆菌属、气微菌属和类诺卡氏菌属，主要的功能模块包括碳氮循环和有机物质降解模块，共同参与气田上方土壤中烃类物质的降解。

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.