Abstract：
Methane-oxidizing bacteria (MOB) have long been considered as a microbial indicator for oil and gas prospecting. However, due to the phylogenetically narrow breath of ecophysiologically distinct MOB, classic culture-dependent approaches could not discriminate MOB population at fine resolution, and accurately reflect the abundance of active MOB in the soil above oil and gas reservoirs. Here, we presented a novel microbial anomaly detection (MAD) strategy to quantitatively identify specific indicator methylotrophs in the surface soils for bioprospecting oil and gas reservoirs by using a combination of 13C-DNA stable isotope probing (SIP), high-throughput sequencing (HTS), quantitative PCR (qPCR) and geostatistical analysis. The Chunguang oilfield of the Junggar Basin was selected as a model system in western China, and type I methanotrophic Methylobacter was most active in the topsoil above the productive oil wells, while type II methanotrophic Methylosinus predominated in the dry well soils, exhibiting clear differences between non- and oil reservoir soils. Similar results were observed by quantification of Methylobacter pmoA genes as a specific bioindicator for the prediction of unknown reservoirs by grid sampling. A microbial anomaly distribution map based on geostatistical analysis further showed that the anomalous zones were highly consistent with petroleum, geological and seismic data, and validated by subsequent drilling. Over seven years, a total of 24 wells have been designed and drilled into the targeted anomaly, and the success rate via the MAD prospecting strategy was 83 %. Our results suggested that molecular techniques are powerful tools for oil and gas prospecting. This study indicates that the exploration efficiency could be significantly improved by integrating multi-disciplinary information in geophysics and geomicrobiology while reducing the drilling risk to a greater extent.
摘要：
甲烷氧化细菌（MOB）长期以来一直被认为是油气勘探的微生物指标。然而,由于生态生理上不同的MOB的系统狭窄呼吸，经典的文化依赖方法不能以良好的分辨率歧视暴民人口，准确反映了油气藏上方土壤中活性MOB的丰度。这里,我们提出了一种新的微生物异常检测（MAD）策略，通过使用13C-DNA稳定同位素探测（SIP）的组合来定量识别表层土壤中用于生物勘探油气藏的特定指标甲基营养物质，高通量测序（HTS），定量PCR(qPCR)和地统计学分析。准噶尔盆地春光油田被选为中国西部地区的示范系统,I型甲烷营养型甲基杆菌在生产油井上方的表层土壤中最活跃，而在干井土壤中，II型甲烷营养型甲氧菌占主导地位，非油藏土壤和油藏土壤之间表现出明显的差异。通过定量甲基杆菌pmoA基因作为通过网格采样预测未知储层的特定生物指示剂，观察到类似的结果。基于地统计分析的微生物异常分布图进一步表明，异常带与石油高度一致，地质和地震数据，并通过后续钻井进行验证。七年来,总共设计了24口井，并钻探了目标异常，MAD勘探策略的成功率为83%。我们的结果表明，分子技术是油气勘探的有力工具。该研究表明，通过整合地球物理和地质微生物学的多学科信息，可以显着提高勘探效率，同时在更大程度上降低钻井风险。
