Article(id=1274057483548135720, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1274057338156769818, articleNumber=null, orderNo=null, doi=10.13343/j.cnki.wsxb.20260170, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1772380800000, receivedDateStr=2026-03-02, revisedDate=null, revisedDateStr=null, acceptedDate=1778169600000, acceptedDateStr=2026-05-08, onlineDate=1781688574921, onlineDateStr=2026-06-17, pubDate=1780502400000, pubDateStr=2026-06-04, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1781688574921, onlineIssueDateStr=2026-06-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1781688574921, creator=13701087609, updateTime=1781688574921, updator=13701087609, issue=Issue{id=1274057338156769818, tenantId=1146029695717560320, journalId=1192105938417971205, year='2026', volume='66', issue='6', pageStart='2561', pageEnd='3114', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1781688540257, creator=13701087609, updateTime=1781688602467, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1274057599193486082, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1274057338156769818, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1274057599193486083, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1274057338156769818, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3052, endPage=3068, ext={EN=ArticleExt(id=1274057484126949674, articleId=1274057483548135720, tenantId=1146029695717560320, journalId=1192105938417971205, language=EN, title=Indigenous microbial distribution and microbial enhanced oil recovery potential in high water-cut reservoirs of an oilfield, columnId=1192149543992045670, journalTitle=Acta Microbiologica Sinica, columnName=Research Article, runingTitle=null, highlight=null, articleAbstract=

An oilfield has entered the stage of high water-cut development, and the conventional water flooding effect is declining. It is urgent to develop microbial enhanced oil recovery (MEOR) technology to tap the remaining oil. Objective To analyze the indigenous bacterial community characteristics of different oil reservoirs and identify the indigenous oil-displacing bacteria, thus providing a scientific basis for the activation-type MEOR involving indigenous bacteria. Methods Produced fluid samples were collected from three high water-cut reservoirs (K1h2, J2x, and J2t). The 16S rRNA gene high-throughput sequencing combined with alpha diversity analysis, beta diversity analysis, linear discriminant analysis effect size (LEfSe)-based differential species identification, and canonical correlation analysis (CCA) of environmental factor correlations was employed to systematically reveal the bacterial community structure and analyze its driving mechanism. Additionally, the oil-displacement potential of the indigenous strain was assessed by core flooding test. Results A total of 174 OTUs were shared among the three groups, while the community composition was significantly different. Temperature, salinity, and water content were the main environmental influencing factors. The K1h2 group demonstrated prominent diversity, mainly consisting of bacteria with the potential to produce biosurfactants, such as Pseudomonas and unclassified_f_Rhodobacteraceae. The J2x group enriched salt-tolerant hydrocarbon-degrading Marinobacter and significantly enriched sulfate-reducing groups. The J2t group was dominated by thermophilic hydrocarbon-degrading bacteria such as Tepidiphilus and Burkholderiales. Core flooding test indicated that P. aeruginosa LD8 isolated from the K1h2 reservoir increased the oil recovery by 9.61% in the simulated reservoir environment. Conclusion The differences in physicochemical and microbial environments among different reservoirs emphasize the necessity of developing particular MEOR strategies. This study provides a research basis for the targeted activation of dominant oil-displacing bacteria, the avoidance of corrosion risks, and the optimization of on-site implementation plans.

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某油田已进入高含水开发阶段,常规水驱效果递减,亟需发展微生物提高采收率(microbial enhanced oil recovery, MEOR)技术以挖潜剩余油。 目的 解析各主力油藏的内源微生物群落特征并识别其中的内源驱油功能菌,为内源微生物激活型MEOR提供科学依据。 方法 采集K1h2、J2x和J2t 3个高含水油藏的采出液样品,采用16S rRNA基因高通量测序,结合α多样性分析、β多样性分析、线性判别分析效应大小(linear discriminant analysis effect size, LEfSe)差异物种识别及典型相关性分析(canonical correspondence analysis, CCA)环境因子关联分析,系统解析微生物群落结构及其驱动机制,并通过岩心驱替实验验证本源驱油菌株的驱油潜力。 结果 三组共享174个操作分类单元,但群落组成显著分化,温度、矿化度、含水率是主要的环境影响因子。K1h2组群落多样性突出,以假单胞菌属(Pseudomonas)、红细菌科未分类属(unclassified_f_Rhodobacteraceae)等潜在的表面活性剂产生菌为主;J2x组富集耐盐烃降解海杆菌属(Marinobacter),并显著富集硫酸盐还原类群;J2t组以嗜微温菌属(Tepidiphilus)、伯克霍尔德氏菌目(Burkholderiales)等嗜高温烃降解菌为主导。岩心驱替实验表明,分离自K1h2油藏的铜绿假单胞菌(P. aeruginosa) LD8在模拟油藏环境下可提高原油采收率9.61%。 结论 不同油藏之间理化环境与微生物环境的差异决定了针对性制定MEOR策略的重要性。本文为某油田定向激活优势驱油菌、规避腐蚀风险及优化现场实施方案提供了研究基础。

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作者贡献声明

马艳清:数据处理及分析,图表制作,论文撰写和修改;魏凤丹:论文选题,研究思路,稿件修改和校对;薛鹏:数据处理,图表制作,稿件修改和校对;刘晓丽:研究思路,数据分析;吴丛文:研究思路;陈玉琨:数据处理;闫泽云:数据处理,图表制作;陈富林:论文选题,研究思路。

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A: CCA analysis of environmental factors and bacterial communities; B: Environmental factor heatmap., figureFileSmall=/xhxvZ1orPKCZidKAe9bCA==, figureFileBig=PhRrR3CwtKKoKG3UqY3WXg==, tableContent=null), ArticleFig(id=1274088208339030433, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=CN, label=图4, caption=环境因子对细菌群落的影响, figureFileSmall=/xhxvZ1orPKCZidKAe9bCA==, figureFileBig=PhRrR3CwtKKoKG3UqY3WXg==, tableContent=null), ArticleFig(id=1274088208401944994, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=EN, label=Figure 5, caption=Network of bacterial genus correlations., figureFileSmall=MaVp3PPYtH3QlpbMFLSUyg==, figureFileBig=DgVh/mQYtAfY6fUbQvFYQw==, tableContent=null), ArticleFig(id=1274088208624243107, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=CN, label=图5, caption=细菌相关性网络, figureFileSmall=MaVp3PPYtH3QlpbMFLSUyg==, figureFileBig=DgVh/mQYtAfY6fUbQvFYQw==, tableContent=null), ArticleFig(id=1274088208771043748, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=EN, label=Figure 6, caption=Characterization of enhanced oil recovery by Pseudomonas aeruginosa LD8. A: The colony morphology; B: Phylogenetic tree stem from the 16S rRNA gene sequence; C: Oil-spreading result; D: Recovery rate during core flooding tests in 0.5 PV of strain LD8., figureFileSmall=NZOIGhAHkn6vOJ93NrfrsA==, figureFileBig=72QDfUlEZ0+KzIkNTK8sOg==, tableContent=null), ArticleFig(id=1274088209077227941, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=CN, label=图6, caption=铜绿假单胞菌LD8的提高采收率评价, figureFileSmall=NZOIGhAHkn6vOJ93NrfrsA==, figureFileBig=72QDfUlEZ0+KzIkNTK8sOg==, tableContent=null), ArticleFig(id=1274088210733978022, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=EN, label=Table 1, caption=

Processing results of sample sequencing data

, figureFileSmall=null, figureFileBig=null, tableContent=
SampleRaw readsEffective readsQ20/%Q30/%G+C/%OTUs
K1127 930127 93099.698.754.4388
K2131 137131 13799.598.454.1643
K3120 280120 28099.698.854.8390
K4128 337128 33799.698.554.7381
K5122 399122 39999.598.454.5382
X1120 446120 44699.598.353.4436
X2129 928129 92899.598.453.4789
X3131 154131 15499.598.553.9398
T1131 846131 84699.598.452.9385
T2131 061131 06199.498.156.3367
T3129 339129 33999.598.556.3322
), ArticleFig(id=1274088211098882471, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1274057483548135720, language=CN, label=表1, caption=

样品测序数据处理结果统计

, figureFileSmall=null, figureFileBig=null, tableContent=
SampleRaw readsEffective readsQ20/%Q30/%G+C/%OTUs
K1127 930127 93099.698.754.4388
K2131 137131 13799.598.454.1643
K3120 280120 28099.698.854.8390
K4128 337128 33799.698.554.7381
K5122 399122 39999.598.454.5382
X1120 446120 44699.598.353.4436
X2129 928129 92899.598.453.4789
X3131 154131 15499.598.553.9398
T1131 846131 84699.598.452.9385
T2131 061131 06199.498.156.3367
T3129 339129 33999.598.556.3322
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某油田高含水油藏内源微生物分布特征及微生物提高采收率应用潜力
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马艳清 1 , 魏凤丹 2 , 薛鹏 1 , 刘晓丽 1 , 吴丛文 1 , 陈玉琨 1 , 闫泽云 2 , 陈富林 2
微生物学报 | 研究报告 2026,66(6): 3052-3068
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微生物学报 | 研究报告 2026, 66(6): 3052-3068
某油田高含水油藏内源微生物分布特征及微生物提高采收率应用潜力
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马艳清1, 魏凤丹2, 薛鹏1, 刘晓丽1, 吴丛文1, 陈玉琨1, 闫泽云2, 陈富林2
作者信息
  • 1.中国石油新疆油田分公司,新疆 克拉玛依
  • 2.西北大学 生命科学学院,陕西 西安
Indigenous microbial distribution and microbial enhanced oil recovery potential in high water-cut reservoirs of an oilfield
Yanqing MA1, Fengdan WEI2, Peng XUE1, Xiaoli LIU1, Congwen WU1, Yukun CHEN1, Zeyun YAN2, Fulin CHEN2
Affiliations
  • 1.PetroChina Xinjiang Oilfield Company, Karamay, Xinjiang, China
  • 2.College of Life Sciences, Northwest University, Xi’an, Shaanxi, China
出版时间: 2026-06-04 doi: 10.13343/j.cnki.wsxb.20260170
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某油田已进入高含水开发阶段,常规水驱效果递减,亟需发展微生物提高采收率(microbial enhanced oil recovery, MEOR)技术以挖潜剩余油。 目的 解析各主力油藏的内源微生物群落特征并识别其中的内源驱油功能菌,为内源微生物激活型MEOR提供科学依据。 方法 采集K1h2、J2x和J2t 3个高含水油藏的采出液样品,采用16S rRNA基因高通量测序,结合α多样性分析、β多样性分析、线性判别分析效应大小(linear discriminant analysis effect size, LEfSe)差异物种识别及典型相关性分析(canonical correspondence analysis, CCA)环境因子关联分析,系统解析微生物群落结构及其驱动机制,并通过岩心驱替实验验证本源驱油菌株的驱油潜力。 结果 三组共享174个操作分类单元,但群落组成显著分化,温度、矿化度、含水率是主要的环境影响因子。K1h2组群落多样性突出,以假单胞菌属(Pseudomonas)、红细菌科未分类属(unclassified_f_Rhodobacteraceae)等潜在的表面活性剂产生菌为主;J2x组富集耐盐烃降解海杆菌属(Marinobacter),并显著富集硫酸盐还原类群;J2t组以嗜微温菌属(Tepidiphilus)、伯克霍尔德氏菌目(Burkholderiales)等嗜高温烃降解菌为主导。岩心驱替实验表明,分离自K1h2油藏的铜绿假单胞菌(P. aeruginosa) LD8在模拟油藏环境下可提高原油采收率9.61%。 结论 不同油藏之间理化环境与微生物环境的差异决定了针对性制定MEOR策略的重要性。本文为某油田定向激活优势驱油菌、规避腐蚀风险及优化现场实施方案提供了研究基础。

细菌群落分布  /  LEfSe分析  /  细菌多样性  /  高含水油藏  /  微生物提高采收率  /  三次采油

An oilfield has entered the stage of high water-cut development, and the conventional water flooding effect is declining. It is urgent to develop microbial enhanced oil recovery (MEOR) technology to tap the remaining oil. Objective To analyze the indigenous bacterial community characteristics of different oil reservoirs and identify the indigenous oil-displacing bacteria, thus providing a scientific basis for the activation-type MEOR involving indigenous bacteria. Methods Produced fluid samples were collected from three high water-cut reservoirs (K1h2, J2x, and J2t). The 16S rRNA gene high-throughput sequencing combined with alpha diversity analysis, beta diversity analysis, linear discriminant analysis effect size (LEfSe)-based differential species identification, and canonical correlation analysis (CCA) of environmental factor correlations was employed to systematically reveal the bacterial community structure and analyze its driving mechanism. Additionally, the oil-displacement potential of the indigenous strain was assessed by core flooding test. Results A total of 174 OTUs were shared among the three groups, while the community composition was significantly different. Temperature, salinity, and water content were the main environmental influencing factors. The K1h2 group demonstrated prominent diversity, mainly consisting of bacteria with the potential to produce biosurfactants, such as Pseudomonas and unclassified_f_Rhodobacteraceae. The J2x group enriched salt-tolerant hydrocarbon-degrading Marinobacter and significantly enriched sulfate-reducing groups. The J2t group was dominated by thermophilic hydrocarbon-degrading bacteria such as Tepidiphilus and Burkholderiales. Core flooding test indicated that P. aeruginosa LD8 isolated from the K1h2 reservoir increased the oil recovery by 9.61% in the simulated reservoir environment. Conclusion The differences in physicochemical and microbial environments among different reservoirs emphasize the necessity of developing particular MEOR strategies. This study provides a research basis for the targeted activation of dominant oil-displacing bacteria, the avoidance of corrosion risks, and the optimization of on-site implementation plans.

bacterial community distribution  /  linear discriminant analysis effect size (LEfSe)  /  bacterial diversity  /  high water-cut reservoir  /  microbial enhanced oil recovery  /  tertiary oil recovery
马艳清, 魏凤丹, 薛鹏, 刘晓丽, 吴丛文, 陈玉琨, 闫泽云, 陈富林. 某油田高含水油藏内源微生物分布特征及微生物提高采收率应用潜力. 微生物学报, 2026 , 66 (6) : 3052 -3068 . DOI: 10.13343/j.cnki.wsxb.20260170
Yanqing MA, Fengdan WEI, Peng XUE, Xiaoli LIU, Congwen WU, Yukun CHEN, Zeyun YAN, Fulin CHEN. Indigenous microbial distribution and microbial enhanced oil recovery potential in high water-cut reservoirs of an oilfield[J]. Acta Microbiologica Sinica, 2026 , 66 (6) : 3052 -3068 . DOI: 10.13343/j.cnki.wsxb.20260170
随着注水开发的持续推进,某油田大部分油藏已进入高含水开发阶段,油井综合含水率已达80.3%以上,部分区块甚至超过95%,剩余油高度分散,常规水驱开发效果明显下降,稳产与增产难度不断加大[1]。在高含水条件下,储层中可动用原油比例显著降低,仅依赖一二次采油技术难以满足油田高效开发的需求,微生物提高采收率技术(microbial enhanced oil recovery, MEOR)作为剩余油挖潜的储备三次采油手段,对延长油田开发寿命具有重要意义[2-3]
根据菌种来源不同,MEOR可分为内源微生物驱油技术和外源微生物驱油技术,该技术主要依赖于驱油微生物对原油组分的降解作用,以及微生物产生的次级代谢产物对油水的两相增溶作用,从而降低原油黏度、改善流体渗流,最终提高原油采收率[4-5]。研究表明,假单胞菌属(Pseudomonas)、芽孢杆菌属(Bacillus)、黄单胞菌属(Xanthomonas)、海杆菌属(Marinobacter)、红球菌属(Rhodococcus)等菌属普遍具备芳烃、烷烃组分降解能力[6-7]。Xu等[8]报道,嗜麦芽寡养单胞菌(Stenotrophomonas maltophilia) WGB211可有效降解C16-C36之间的多种烷烃组分,7 d内对C32的降解率超过75%,能有效降低原油中长链烷烃的占比。地芽孢杆菌属(Geobacillus)、施氏假单胞菌(Pseudomonas stutzeri)可以高效降解原油中的胶质、沥青质等重质组分,有效降低原油黏度,提高原油流动性[9-10]。微生物产生的驱油次级代谢产物可分为小分子生物表面活性剂和大分子生物乳化剂,其中小分子生物表面活性剂具有显著的界面活性,主要通过降低界面张力增强油相洗脱能力;大分子生物乳化剂具有突出的乳液稳定性,增强油水乳化[11-13]。据Shaimerdenova等[14]报道,枯草芽孢杆菌(Bacillus subtilis) A9分泌的表面活性素可将表面张力降低至(32.76±0.30) mN/m,有效促进原油的乳化剥离,辅助提高石油采收率。近年来,国内各大油田围绕MEOR技术开展了大量针对性研究与现场实践。胜利油田沾3区块通过定制化富营养激活剂,定向唤醒油藏内源驱油菌,使区块采收率提升23.59%;大庆油田室内岩心驱替试验证实,聚驱后微生物调驱技术可稳定提高采收率3.9%-8.7%[15-16]
尽管MEOR在理论研究和室内实验中均展现出广阔的应用前景,但微生物在油田现场的实施效果受多种因素影响,包括地层流体适应性、储层匹配度以及微生物群落间的竞争与协同关系等[17-20]。因此,MEOR技术在现场的应用需建立在充分掌握油藏原生生物信息的基础上,以适应目标油藏环境的内源驱油微生物为重点开发菌种,从而构建高度适应现场环境的微生物驱油体系,有效提高现场应用效果[21]。然而,目前鲜有研究聚焦于探究新疆某油田K1h2、J2x、J2t油藏的微生物群落结构与MEOR潜力。本研究以上述3个高含水油藏为研究对象,利用16S rRNA基因高通量测序技术解析内源细菌分布特征,使用线性判别分析效应大小(linear discriminant analysis effect size, LEfSe)分析明确不同油藏的差异菌属,并探讨环境因子对微生物分布的影响规律,以期为以内源微生物激活为核心的MEOR技术实施提供前导研究依据。
本研究于准噶尔盆地某油田的K1h2、J2x、J2t油藏高含水油井中分散采集11个来自不同油井的产出液样品。样品根据来源油藏不同分别记作K组、X组、T组。样本采集后,于4 ℃条件下运输至实验室,随后转入-80 ℃储存,用于样品总DNA提取。
VAMNE Magnetic Stool/Soil DNA Extraction Kit,南京诺唯赞生物科技股份有限公司;E.Z.N.A Gel Extraction Kit,Omega Bio-tek公司;ALFA-SEQ DNA建库试剂盒,方舟生物安全科技(广州)有限公司。
NanoDrop One微量紫外-可见分光光度计、Qubit 4.0核酸定量仪,ThermoFisher Scientific公司;Qsep400高通量核酸蛋白分析仪,杭州厚泽生物科技有限公司;Illumina HiSeq X Ten测序仪,Illumina公司。
LB培养基(g/L):胰蛋白胨10.0,酵母粉5.0,NaCl 5.0。相应的LB固体培养基中另需添加16.0 g/L琼脂粉。121 ℃灭菌30 min,室温冷却后保存。
最小无机盐培养基(mineral salt medium, MSM) (g/L):MgSO4 0.1,K2HPO4 7.0,NaCl 0.5,(NH4)2SO4 2.0,KH2PO4 3.0。121 ℃灭菌30 min,室温冷却后保存。
血琼脂固体培养基(g/L):酪蛋白胰酶消化物10.0,心胰酶消化物3.0,玉米淀粉1.0,肉胃酶消化物5.0,酵母粉5.0,氯化钠5.0,琼脂15.0,无菌脱纤维羊血50-100 mL。无菌脱纤维羊血需在其他培养基成分溶解,121 ℃灭菌15 min并水浴冷却至45-50 ℃时加入,随后混匀培养基成分并倾注平板。
采用VAMNE Magnetic Stool/Soil DNA Extraction Kit提取产出液样本中的微生物总DNA,并使用NanoDrop One微量紫外-可见分光光度计检测DNA的浓度和纯度,所有DNA样品检验合格后储存于-80 ℃备用[22]
使用515F (5′-GTGCCAGCMGCCGCGGTA A-3′)和806R (5′-GGACTACHVGGGTWTCTAA T-3′)引物扩增细菌16S rRNA基因V4区,PCR反应由广东美格基因科技有限公司完成。PCR反应体系(50 µL):2×PremixTaq 25 µL,DNA模板2 µL,上、下游引物(10 µmol/L)各1 μL,去离子水21 μL。PCR反应条件:94 ℃预变性5 min;94 ℃变性30 s,52 ℃退火30 s,72 ℃延伸30 s,共30个循环;72 ℃终延伸10 min;4 ℃保温10 min终止反应。获得的目标产物通过琼脂糖凝胶电泳检验片段长度和浓度。使用E.Z.N.A Gel Extraction Kit回收PCR混合产物,利用TE缓冲液回收目标片段[23-24]
使用ALFA-SEQ DNA建库试剂盒制备DNA文库,经Qsep400、Qubit 4.0检验文库片段大小和浓度后,使用Illumina平台进行PE250测序。经引物去除、片段拼接、数据过滤后获得有效拼接片段。获得的有效片段使用UPARSE 10.0.240进行操作分类单元(operational taxonomic unit, OTU)聚类,使用usearch-SINTAX结合BLAST将每个OTU代表序列与SILVA数据库进行对比注释,以获取物种注释信息,置信度阈值设置为0.8[25]。使用R软件进行物种统计、群落组成分析及物种丰度聚类分析。组间主坐标分析(principal co-ordinates analysis, PCoA)聚类与样本距离热图聚类均采用Bray-Curtis算法,采用one against one比较进行LEfSe分析,线性判别分析(linear discriminant analysis, LDA)分数阈值设置为2[26]。采用SPSS Statistics 25.0进行Spearman相关性分析,并设置渗透率、孔隙度、含油饱和度、含水、矿化度等环境因子,基于CANOCO 5.0进行典型相关性分析(canonical correspondence analysis, CCA)[27]。采用R软件计算Spearman相关系数以获取物种相关性信息,物种丰度设置为50,相关系数阈值设置为0.8[28]
以目标区块原油样品作为碳源和菌剂来源,取5 g原油样品加入95 mL MSM培养基中,在目标区块油藏温度下150 r/min培养7 d。梯度稀释获得菌株单克隆后,基于3次平板划线进行菌株纯化,将纯化后的菌株使用牛奶管保存在-80 ℃备用。使用血琼脂固体培养基溶血圈验证各菌株的表面活性剂产生性能。
使用细菌通用引物27F (5′-AGAGTTTGAT CCTGGCTCAG-3′)和1492R (5′-TACGACTTAA CCCCAATCGC-3′)扩增细菌的16S rRNA基因。PCR扩增体系(10 μL):2×RapidTaq Master Mix 5 μL,DMSO 0.5 μL,DNA模板0.4 μL,上、下游引物(5 µmol/L)各0.3 μL,去离子水3.5 μL。PCR反应条件:94 ℃预变性5 min;94 ℃变性45 s,52 ℃退火30 s,72 ℃延伸90 s,共30个循环;72 ℃终延伸8 min;12 ℃保温10 min终止反应。将PCR产物的测序结果通过BLAST与GenBank中已知序列进行同源性比较,并在MEGA软件中使用邻接法构建系统发育树。
使用LB液体培养基在油藏温度下制备细菌发酵液,接种量为1%,培养时间为2 d。向玻璃培养皿中加入5 mL蒸馏水,随后在水面上加入40 mL液体石蜡。将10 μL发酵液缓慢滴加在液体石蜡表面,观察排油情况。
基于油藏渗透率参数构建人造岩心,岩心样本在实验前烘干至恒重,而后使用地层水进行饱和水处理,确定孔隙体积。将已经饱和地层水的岩心安装在岩心夹持器中,以饱和脱水脱气原油,实验温度设置为目标油藏温度,回压设置为油藏压力,用于模拟目标油藏的储层环境。为建立剩余油饱和度,进行一次水驱至出口处无油采出。向岩心中注入1%驱油菌株发酵液0.5 PV,注入模式为0.05 mL/min恒速驱替,而后进行二次水驱,至出口处无油采出。实验过程中持续监测采收率。
研究区位于新疆准噶尔盆地北部,主要开发油藏为K1h2、J2x、J2t油藏。K1h2油藏温度为37 ℃,样品平均渗透率为1 801.9×10-3 μm2,有效孔隙度为29.9%,平均剩余含油饱和度为46.9%,地层水矿化度9 382 mg/L,目前油藏综合含水率为95.2%,平均采出程度为35.3%。J2x油藏温度为63.3 ℃,样品渗透率在(12.1-225.0)×10-3 μm2之间,平均渗透率为100.3×10-3 μm2,有效孔隙度为18.9%,平均剩余含油饱和度为54.9%,地层水矿化度为19 709 mg/L,目前综合含水率为95.4%。J2t油藏温度为58 ℃,样品渗透率在(73.3-318.0)×10-3 μm2之间,平均渗透率为167.2×10-3 μm2,有效孔隙度为18.0%,平均剩余含油饱和度为58.5%,地层水矿化度为17 287 mg/L,目前综合含水率为95.0%。
分别在K1h2、J2x、J2t油藏的11个不同油井产出液样本中共识别出1 403 857个有效序列片段,平均每个样本注释到127 623个序列片段。UPARSE聚类显示,所有样本中共注释到3 365个不同的OTUs (表1)。随着测序量的不断增加,样本丰富度逐渐趋于平稳,表明测序量充足,可以有效反映研究区样本中的细菌群落分布情况(图1A)。α多样性指数中,K1h2组产出液样本的Shannon指数最高(3.27)、Simpson指数最低(0.10),表明K1h2组的菌群物种丰富度、群落多样性和分布均匀度显著高于J2x和J2t组(图1B)。韦恩图展示了K1h2、J2x、J2t组产出液样本中的物种数目分别为366、366、247,群落共有OTUs (174个)分别占K1h2、J2x、J2t组产出液OTU总数的47.54%、47.54%、70.45% (图1C)。丰度排名前15的菌属均为3组共有菌,K1h2组的优势菌属为红细菌科未分类属(unclassified_f_Rhodobacteraceae,3.88%-44.35%,平均19.17%)、生丝单胞菌属(Hyphomonas,0.45%-18.10%,平均9.02%)、假单胞菌属(0.48%-21.76%,平均7.18%),而索氏菌属(Thauera)、未分类红环菌科(unclassified_f_Rhodocyclaceae)在部分样本中的占比也超过了10.00% (图1D)。J2x组内不同样本之间有显著的优势菌差异,X1样本中的优势菌属为假单胞菌属(30.64%)、索氏菌属(11.72%)、硫化螺旋菌属(Sulfurospirillum, 21.47%),X2样本中未分类糖小螺菌科(unclassified_f_Saccharospirillaceae, 26.77%)占比突出,X3样本中海杆菌属(34.83%)、交替单胞菌属(Alteromonas, 32.66%)丰度最高。J2t组中,嗜微温菌属(Tepidiphilus,0.89%-45.65%,平均21.63%)、红细菌科未分类属(0.48%-31.79%,平均18.05%)、假单胞菌属(1.22%-17.64%)占比最为突出,在部分样本中丰度较大的还有未分类弓形菌科(unclassified_f_Arcobacteraceae, 0.04%-30.05%)、玫瑰变色菌属(Roseovarius, 0.23-14.70%)、未分类红环菌科(0.55%-16.12%)。
为进一步探究某油田不同油藏的菌群组成差异,基于Bray-Curtis距离进行了主坐标分析,PCoA1和PCoA2轴分别解释了23.3%和18.8%的方差,分析结果将K1h2、J2x、J2t聚类为3个独立的簇(图2A)。热图聚类分析表明K1h2组内部样本多呈现较低的距离值(0.51-0.67),表明其组内群落组成相似度较高;而J2x组内部样本之间离散性强,样本距离在0.89-0.94之间;J2t组中T2与T3距离较近(0.69),而T1与K1h2组中的K1和K5距离小(分别为0.48和0.61),表明T1样本群落结构与K1h2组具有相似性。此外,J2x与J2t组间所有样本的距离均大于0.74,且J2x与K1h2组间距离也普遍高于0.70,表明J2x与其他2组的群落结构差异较大(图2B)。细菌属水平聚类也得到了相似结果,K1h2组样本整体聚类为一支,以红细菌科未分类属和假单胞菌属为主要优势菌,表现出较高的群落一致性,反映出该油藏环境稳定且微生物生态趋于平衡;J2x组内部群落结构差异显著,各样本优势菌种各异,表明其受局部扰动影响较大,群落组成不稳定;J2t组中T1、T3与K1h2聚成一类,而T2与X1聚成一类(图2C)。
采用LEfSe分析(LDA阈值>2.5,P<0.05)在3个油藏采出液中鉴定出高贡献的差异细菌类群(图3)。Hyphomicrobiales目(LDA=4.84)、根瘤菌科(Rhizobiaceae, LDA=4.57)、根瘤菌科未分类属(unclassified_f_Rhizobiaceae, LDA=4.38)、斯塔普氏菌科未分类属(unclassified_f_Stappiaceae, LDA=4.33)、异根瘤菌属(Allorhizobium, LDA=3.92)、Lutibaculaceae科(LDA=3.22)、潘隆尼亚碱湖杆菌属(Pannonibacter, LDA=3.25)和泥棒菌属(Lutibaculum, LDA=3.24)显著富集于K1h2组;J2x组以碱土菌属(Geoalkalibacter, LDA=4.07)、脱硫单胞菌科(Desulfuromonadaceae, LDA=4.09)、脱铁杆菌属(Deferribacter, LDA=3.35)、Desulfotomaculales目(LDA=3.15)、Desulfotomaculia纲(LDA=3.19)、未分类的Acetothermiia纲(LDA=2.76)以及Acetothermiia纲中未分类的目、科、属(LDA在2.75-2.76之间)为特征;J2t组则特异性富集斯塔普氏菌属(Stappia, LDA=4.53)、脱铁杆菌科(Deferribacteraceae, LDA=5.06)、嗜微温菌属(LDA=5.07)、伯克霍尔德氏菌目(Burkholderiales, LDA=5.14)、四球状菌属(Quadrisphaera, LDA=3.65)、Lutibaculaceae科(LDA=3.68)及异根瘤菌属(LDA=3.53)。斯塔普氏菌属在K1h2中也有富集(LDA=3.21),但其在J2t中的LDA值更高(LDA=4.53),表明其在J2t中更具判别性。树状图进一步显示,这些标志类群在进化分支上高度聚集,3组之间几乎不重叠。
通过CCA分析探讨了影响菌群组成变化的主要环境因子,CCA1和CCA2分别解释了26.9%、22.7%的变异(图4A)。储层物性和流体因素不同程度地影响了菌群的分布,其中矿化度、温度和含水率是起主导作用的环境因子。K1h2组样本位于左上区域,主要受孔隙度和渗透率影响;J2x组样本主要分布右侧区域,与温度和矿化度正相关;J2t组相对集中于左下区,与含油饱和度和含水率密切相关。热图进一步揭示了各环境因子与优势菌属的关联性(图4B)。Hyphomicrobiales目、玫瑰变色菌属、海滨小杆菌属(Actibacterium)等在高孔隙度、低含油饱和度条件下富集,而硫膨大杆菌属(Thioclava)、硫化螺旋菌属、假单胞菌属等在高含水率、高温环境中相对丰度较高;海杆菌属、交替单胞菌属与矿化度呈强正相关,生丝单胞菌属、索氏菌属则在中等矿化度条件下占据优势。
以丰度前50的菌属作为分析对象计算Spearman相关性,选取相关系数阈值大于0.8且P值小于0.05的物种构建相关性网络图(图5)。结果表明31个相互作用的菌属共形成了7个相关性网络,组成28个边,其中23个正相关,5个负相关,涉及11个门。物种相关性分析中的主要核心菌门是假单胞菌门(Pseudomonadota),涉及4个网络、10个节点、6条边。
由于J2x和J2t油藏样本间群落分布差异较大,而K1h2油藏样本间物种分布相似性较高,选择K1h2油藏样本分离潜在的内源驱油微生物更具应用潜力。在K1h2样本中分离出一株原油乳化效果最好的菌株,其单菌落呈现黄绿色圆形凸起,边缘光滑,命名为LD8 (图6A)。经16S rRNA基因序列BLAST比对,菌株LD8与铜绿假单胞菌(Pseudomonas aeruginosa) DSM 50071、NBRC 12689、ATCC 10145具有高度同源性,被鉴定为铜绿假单胞菌(图6B)。排油圈实验表明菌株LD8发酵液具有突出的表面活性(图6C)。为评估内源铜绿假单胞菌在K1h2油藏中的驱油潜力,基于油藏平均渗透率(1 100×10-3 μm2)制备了人造岩心,并在37 ℃、10 MPa的模拟油藏环境中进行了岩心驱替实验。驱替结果表明,菌株LD8在0.5 PV注入量下可提高采收率9.61% (图6D)。
受储层物性、流体物化条件、开发措施等多重因素影响,不同油藏通常呈现出鲜明的菌群分布差异,因此基于目标油藏现有微生物基础确定适宜的MEOR开发策略具有必要性。据Wang等[3]报道,鄂尔多斯盆地侏罗系高含水油藏中假单胞菌属(15.74%)、硫化螺旋菌属(9.94%)、脱硫棒状菌属(Desulfotignum, 8.66%)、盐单胞菌属(Halomonas, 6.80%)占据优势,而三叠系高含水油藏中的优势菌属为假单胞菌属(33.54%)、不动杆菌属(Acinetobacter, 11.41%)、海小杆菌属(Marinobacterium, 7.58%)、海杆菌属(7.51%)。虽然群落结构有所不同,但侏罗系和三叠系高含水油藏中占比最高的优势菌属均为假单胞菌属。相比之下,尽管K1h2、J2x、J2t 3组样本之间存在174个共有OTUs,但在群落组成与优势功能菌群方面存在显著差异。本研究通过高通量测序技术系统解析新疆某油田3个主力油藏(K1h2、J2x、J2t)采出液中微生物群落的多样性、组成结构及其环境驱动机制,并基于室内实验评估微生物驱油潜力,为内源微生物驱油技术的推进提供依据。
K1h2组37 ℃的温和温度、95.2%的超高含水率及1 801.9×10-3 μm2的高渗透率适合大量微生物生长繁殖,因此K1h2组的Shannon指数和Chao1指数最高[29]。长期注水形成的稳定水相环境为微生物提供了充足的生存空间与营养交换条件,有利于维持群落多样性[24]。该组中丰度较高的菌属,如假单胞菌属、红细菌科未分类属和索氏菌属具有MEOR潜力,例如假单胞菌属和副球菌属(Paracoccus)中的某些成员可以分解芳香烃、烷烃并生成鼠李糖脂,索氏菌属中的某些成员可以降解芳香烃并产生具有乳化活性的胞外多糖[30-34]。LEfSe分析表明,异根瘤菌属、潘隆尼亚碱湖杆菌属、泥棒菌属、斯塔普氏菌属等在K1h2组中具有判别性。这些物种的最适温度普遍在28-37 ℃,具备降解复杂有机物的能力,多见于营养较丰富、环境相对稳定的生境,表明该油藏或可通过营养激活策略定向富集内源驱油菌[35-36]
J2x组中,样本之间Bray-Curtis距离普遍较高(>0.89),表明其群落结构离散性强,可能与油藏非均质性或差异化历史开采有关。海杆菌属作为J2x组的优势菌,具有突出的耐温、耐盐和广谱石油烃降解能力,其最适生长盐浓度普遍在20-30 g/L之间,可耐受50 ℃高温,在高温高盐环境下具有突出的烃降解能力,可作为储备的石油指示剂[37-39]。此外,LEfSe结果显示碱性嗜热铁还原的碱土菌属(LDA=4.07)及Desulfotomaculales目等硫酸盐还原菌在该组特异性富集,表明该油藏可能处于强还原状态,存在硫代谢活跃、H2S腐蚀风险,该油藏中微生物驱油的实施需特别关注硫酸盐还原菌的抑制[40-43]
J2t组中,红细菌科未分类属、嗜微温菌属相对丰度较高,其中红细菌科未分类属是兼具有机污染物降解和氮、磷去除能力的耐高温菌,最高耐受温度可达65 ℃,嗜微温菌属作为嗜热烃氧化细菌,最适生长温度为50-55 ℃,最高可耐受61 ℃高温[44-46]。此外,嗜微温菌属(LDA=5.07)和伯克霍尔德氏菌目(LDA=5.14)作为生物标志物被LEfSe识别,上述菌属均被报道具有降解芳香烃及长链烷烃的能力,适用于高温油藏生物开发[47-48]。此外,T1样本在β多样性上与K1h2组相似度高,且同样富含假单胞菌属,表明该井位可能处于注水交叉区域,具备与K1h2类似的MEOR应用条件。
K1h2油藏优势菌属的驱油潜力较为突出且样本间群落分布差异较小,因此该油藏有可能通过提高内源驱油微生物占比而有效促进剩余油的开采。作为内源驱油细菌,假单胞菌属不仅具有产生鼠李糖脂生物表面活性剂的潜力,其在K1h2油藏样本中的平均占比达到了7.18%,表明该菌属在内源微生物中具有较强的竞争力,在储层环境中具有较好的适应性。在37 ℃、10 MPa的模拟油藏环境中,分离自K1h2产出液的铜绿假单胞菌LD8在一次水驱的基础上提高驱替效率9.61%,使整体采出程度达到70.76%,表明针对性激活或强化注入内源驱油菌在K1h2油藏的持续开发中具有巨大应用潜力。
某油田K1h2、J2x和J2t高含水油藏采出液的群落组成与优势功能菌群存在显著差异。油藏温度、矿化度、含水率及物性参数等环境因子共同影响了微生物群落的分化特征。K1h2组由于温和的温度、高含水和高渗透率形成了多样且稳定的细菌群落,其中假单胞菌属、红细菌科未分类属整体占比较高。基于一株内源铜绿假单胞菌LD8的岩心驱替实验表明,内源驱油微生物在该油藏的后续开发中具有突出的应用潜力。J2x组因突出的矿化度特点有效富集了耐盐烃降解菌Marinobacter,但Desulfotomaculales目等硫酸盐菌的代谢活动可能加剧腐蚀风险。J2t组以嗜微温菌属和伯克霍尔德氏菌目为主导,可用于中高温油藏生物采油。K1h2、J2x、J2t油藏具备不同的微生物基础,结合环境因子与菌群特征,针对性激活驱油菌群有望长期改善井下菌群,持续提高原油采收率,推动油田的绿色高效开发。
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2026年第66卷第6期
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doi: 10.13343/j.cnki.wsxb.20260170
  • 接收时间:2026-03-02
  • 首发时间:2026-06-17
  • 出版时间:2026-06-04
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  • 收稿日期:2026-03-02
  • 录用日期:2026-05-08
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    1.中国石油新疆油田分公司,新疆 克拉玛依
    2.西北大学 生命科学学院,陕西 西安
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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