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.

Methane-oxidizing bacteria (MOB) have long been recognized as an important bioindicator for oil and gas exploration. However, due to their physiological and ecological diversity, the distribution of MOB in different habitats varies widely, making it challenging to authentically reflect the abundance of active MOB in the soil above oil and gas reservoirs using conventional methods. Here, we selected the Puguang gas field of the Sichuan Basin in Southwest China as a model system to study the ecological characteristics of methanotrophs using culture-independent molecular techniques. Initially, by comparing the abundance of the pmoA genes determined by quantitative PCR (qPCR), no significant difference was found between gas well and non-gas well soils, indicating that the abundance of total MOB may not necessarily reflect the distribution of the underlying gas reservoirs. 13C-DNA stable isotope probing (DNA-SIP) in combination with high-throughput sequencing (HTS) furthermore revealed that type II methanotrophic Methylocystis was the absolutely predominant active MOB in the non-gas-field soils, whereas the niche vacated by Methylocystis was gradually filled with type I RPC-2 (rice paddy cluster-2) and Methylosarcina in the surface soils of gas reservoirs after geoscale acclimation to trace- and continuous-methane supply. The sum of the relative abundance of RPC-2 and Methylosarcina was then used as specific biotic index (BI) in the Puguang gas field. A microbial anomaly distribution map based on the BI values showed that the anomalous zones were highly consistent with geological and geophysical data, and known drilling results. Therefore, the active but not total methanotrophs successfully reflected the microseepage intensity of the underlying active hydrocarbon system, and can be used as an essential quantitative index to determine the existence and distribution of reservoirs. Our results suggest that molecular microbial techniques are powerful tools for oil and gas prospecting.