页岩油研究热点与发展趋势

万晓帆 ,  刘丛丛 ,  赵德锋 ,  葛翔

地球科学 ›› 2023, Vol. 48 ›› Issue (02) : 793 -813.

PDF (8332KB)
地球科学 ›› 2023, Vol. 48 ›› Issue (02) : 793 -813. DOI: 10.3799/dqkx.2022.443

页岩油研究热点与发展趋势

作者信息 +

Hotspot and Development Trend of Shale Oil Research

Author information +
文章历史 +
PDF (8531K)

摘要

页岩油储量巨大、分布集中、前景广阔,是世界石油增储上产的一个主要领域. 为厘清页岩油研究的热点与发展趋势,使用CiteSpace和VOSviewer软件对近十年国内外文献进行科学知识可视化分析,结合世界页岩油盆地研究及勘探开发成果,系统梳理了页岩油近十年的主题演化及热点领域,总结了当前页岩油研究面临的挑战. 结果认为全球页岩油研究热点聚焦于页岩油形成的物质基础、页岩油储集空间、页岩油可动性及可压裂性4方面;相比北美海相页岩油构造沉积背景稳定,页岩油生产技术持续迭代,我国页岩油沉积相变快,孔隙类型受成岩作用影响较大,缺乏系统的可动性评价方法,水力压裂易诱发地震和造成环境污染;未来应加强细粒沉积岩研究、定量表征页岩油储集空间、明确页岩油赋存状态、建立全面的页岩油可动性评价方法、加强新型绿色压裂技术研发,从而精准预测页岩油“地质-工程”甜点,以推动我国能源结构的快速转型.

关键词

页岩油 / 赋存机理 / 可动性 / 压裂 / 科学知识可视化 / 石油地质

Key words

shale oil / occurrence mechanism / mobility / fracturing / scientific knowledge visualization / petroleum geology

引用本文

引用格式 ▾
万晓帆,刘丛丛,赵德锋,葛翔. 页岩油研究热点与发展趋势[J]. 地球科学, 2023, 48(02): 793-813 DOI:10.3799/dqkx.2022.443

登录浏览全文

4963

注册一个新账户 忘记密码

0 引言

我国2021年全年石油净进口量5.59亿吨,原油产量仅为1.99亿吨,对外依存度高达72.2%(刘朝全等, 2021). 预计近些年我国油气对外依存度还将持续上升. 随着水平井、水力压裂等开发技术越来越成熟,页岩区块的钻探效率显著提升,页岩油以其巨大的资源潜力掀起了一场油气革命,可能成为未来20年内石油产量增量的主力军(EIA, 2017). 截至2021年年底,全球页岩油可采资源量为2 246.9亿吨(杨雷和金之钧,2019邹才能, 2022a),资源潜力巨大,全球超过一半的页岩油资源集中在5个国家(图1):美国、俄罗斯、中国、阿根廷和利比亚(EIA, 2022). 其中我国页岩油技术可采资源量高达55亿吨,勘探前景可观(Lei et al., 2021). 面对严重的石油短缺,页岩油的勘探开发对缓解我国严峻的能源安全形势具有战略意义.

美国页岩油产量于2015年已超过本土原油总产量的一半,提高了美国原油市场的话语权,且促使世界石油供需格局发生了重大变化(崔景伟等, 2015). 得益于相似的地质条件,加拿大效仿美国,实现了页岩油商业化开发,页岩油开发浪潮从北美蔓延至中国、俄罗斯、澳大利亚以及日本等国家(王淑玲等, 2016). 全球范围内对页岩油的需求迅速增长,近十年Web of Science数据库页岩油年发文量增长了近6.5倍,截至 2021年发文量已达1 671篇(图2). 我国自2010年以来,相继在三塘湖盆地(柳波等, 2012)、南襄盆地(马永生等, 2012)、鄂尔多斯盆地(杨华等, 2013)、四川盆地(韩克猷等, 2015)、松辽盆地(李士超等, 2017)、江汉盆地(张鹏飞等, 2016)、渤海湾盆地(赵贤正等, 2018)、准噶尔盆地(支东明等, 2019a支东明等, 2019b)等获工业油流,取得了国内陆相页岩油勘探突破. 北部湾盆地海域页岩油钻探的成功(李辉等, 2022),开辟了中国页岩油勘探开发新领域. 3个国家级页岩油示范区(新疆油田吉木萨尔陆相页岩油国家级示范区、大庆古龙陆相页岩油国家级示范区、胜利济阳陆相断陷湖盆页岩油国家级示范区)的建立促进了我国页岩油的工业化开发.

然而,不同于常规油气藏已形成较为完备的研究体系,目前页岩油研究还处于探索阶段. 不同盆地页岩油的沉积构造背景、烃源岩条件、优质储层识别特征、“甜点”类型和富集主控因素存在较大差异,国内外尚无有效识别页岩油水平井压裂后主产层的工程技术手段,页岩油成储机理、赋存状态及可动性评价等研究观点不一. 基于此,本文在前人页岩油研究成果的基础上,利用CiteSpace和VOSviewer两种科学知识可视化软件对2010年以来的国内外页岩油文献进行综合分析,系统梳理页岩油主题演化、研究热点和发展趋势,对比国内外页岩油特征差异,探讨页岩油定义、有机地化特征、物性特征、岩矿组合特征、流体特征等,总结页岩油研究存在的问题及前沿技术,以期为我国陆相页岩油研究及勘探开发提出合理建议.

1 页岩油定义

页岩油被用来描述从页岩地层开采出来的非常规石油资源. 与砂岩、泥岩、碳酸盐岩等依据岩性划分的地层不同,页岩作为一种根据纹层构造而命名的特殊地层类型,在矿物组合上表现为粘土、石英、长石等物理碎屑与化学以及生物来源的钙质与硅质矿物的渐变混积,不同学者对其定义与内涵存在不同理解. 例如北美海相页岩油地层主要为生物来源的碳酸盐岩-泥岩混积型页岩(Robison and Castano, 1997Loucks and Ruppel, 2007Treadgold et al., 2011Jarvie, 2012Horsfield et al., 2018),不同地区页岩矿物成分差异较大,如图3a中显示,北美Eagle Ford页岩和Niobrara页岩碳酸盐岩矿物含量较高,约为50%~70%,Bakken页岩长英质矿物含量较高,约为40%~60%,Barnett页岩不同层段矿物含量差异较大. 我国陆相页岩油地层则主要为化学沉淀来源的碳酸盐岩-泥岩混积型页岩(张金川等, 2012赵贤正等, 2018周立宏等, 2018金之钧等, 2019金涛等, 2022)、物理碎屑来源的砂泥互层混积型页岩(邹才能等, 2013a2015a柳波等, 2014杨智等, 2015金之钧等, 2019赵文智等, 2020)、火山来源的凝灰岩-泥岩混积型页岩(支东明等, 2019a2019b)等.

复杂的矿物组成为页岩油的定义增加了难度,导致早期页岩油与致密油概念被混淆使用,随着国内外学者及机构对页岩油定义的不断修改完善,两者至今已能被较为明晰地区分开来(表1). 致密油是致密储层油的简称,通常是指储层物性差,孔隙度<10%,覆压基质渗透率<0.1 mD的非常规油气资源(邹才能等, 2013a姜在兴等, 2014). 致密油按岩性可分为致密页岩油(页岩油的一种类型)、致密砂岩油、致密火山岩油等多种类型. 页岩油储层孔隙度更低,也有少部分储层孔隙度较为发育,如美国Eagle Ford组(张金川等, 2012柳波等, 2014王淑玲等, 2016)、Niobrara组(Kernan, 2015)、我国青山口组(邹才能等, 2013b柳波等, 2014杨智等, 2015)、沙河街组(刘惠民等, 2018刘毅, 2018周立宏等, 2019张顺等, 2021)、流沙港组(Gao et al., 2018)、芦草沟组等(杨智等, 2015邹才能等, 2015aYang et al., 2019赵文智等, 2020),部分高值甚至可达20%,覆压基质渗透率约为0.001~1 mD(图3b). 对页岩油的定义,建议采用邹才能等(2022a)提出的“现今已经生成并赋存于富有机质低孔低渗泥页岩层系中滞留或仅经历短距离运移的石油,以吸附态、溶解态、游离态等形式存在,一般采出的页岩油油质较轻、粘度较低”.

2 页岩油研究的主题演化

为展现页岩油主题演化情况,对近十年国内外页岩油文献进行了计量可视化分析. 研究数据来源于Web of Science数据库中的SCI索引子库,采取高级检索方式,限定主题词为“shale oil”,自定义年份范围为“2010年1月1日~2022年5月31日”. 经剔除与研究主题相差较远、作者或刊名不健全的文献后,得到文献10 787篇. 利用CiteSpace可视化软件对数据进行筛选、知识单元选择与构建、标准化等分析,利用LLR算法(loglikelihood ratio,相似度比例算法)对主题进行计算,构建Timezone时区视图(图4).

图中节点代表主题词,节点越大,主题词出现频次越高,节点外紫色光圈越厚,节点中心性越高,该主题词在分析数据集中的位置是其首次出现的年份. 连线代表主题词的联系密度,节点间连线越多,主题词关系越密切. 图4左上角参数显示数据集中节点数N为867,连线数E为8 569,为使图件更为清晰明了,对词频阈值进行调整,使图中仅显示词频大于80的节点及其连线.

据主题词突现时间与规律,可将页岩油近十年研究的主题演化划分为4个阶段:(1)2010年~2013年,页岩油有机地化特征引起广泛关注,中心性及重要性较高的主题词为“页岩油”、“有机质”、“烃源岩”、“地化特征”. 富有机质泥页岩是页岩油形成的基础条件已基本达成共识(杨华等, 2013),通过对页岩油富集区源岩有机地化特征进行归纳,查明高有机碳含量、处于大量生油阶段的成熟度以及有利生油的有机质类型是页岩油形成的关键因素(梁世君等, 2012高岗等, 2013武晓玲等, 2013); (2)2013年~2016年,沉积背景及构造条件对页岩油分布的控制作用被激烈探讨,中心性较高的主题词为“沉积”、“层序地层学”、“裂缝”. 为进一步明晰页岩油甜点识别特征,对比不同盆地沉积与构造特征,利用层序地层学构建等时格架(朱德燕等, 2016),发现浮游生物生产力较高的深水区易形成大面积连续分布的富有机质页岩(宁方兴, 2015). 天然裂缝既可以作为储集空间,也可作为页岩油的运移通道(李吉君等, 2014); (3)2016年~2019年,页岩油研究大多聚焦储层物性特征,中心性较高的主题词为“渗透率”、“孔隙度”、 “孔隙结构”、“多孔介质”、“孔隙大小分布”. 有机质孔隙是页岩油的主要储集空间,粒间孔、粒内孔、和裂缝为次要储集空间(Han et al., 2017Wang and Sheng, 2017). 明确页岩储层孔隙类型、孔隙结构与页岩油在孔隙中的赋存状态,是对页岩储层评价指标的完善与丰富; (4)2019年以来,人工智能被巧妙地与页岩油储层改造结合,中心性较高的主题词为 “水力压裂”、“数值模拟”、“神经网络”、“机器学习”、“二氧化碳压裂”. 这一阶段全球页岩油可采资源量基本明确,但储层改造与开发技术仍有待提升. 得益于神经网络、机器学习、深度学习等人工智能技术的发展(Meng et al., 2020Mehana et al., 2021周济民等, 2021),地质模型和力学模型大量应用于三维及四维建模,页岩油水平井压裂预测与优化效果大幅提升(杨志会等, 2022).

页岩油主题演化过程与页岩油勘探进程及学科发展息息相关,早期页岩油勘探被常规找油思路限制,很少钻遇富有机质页岩,页岩的有机地化研究为非常规勘探划定了优质烃源岩的靶区. 沉积条件影响着页岩岩相组合,随着X-射线能谱分析、微区矿物定量分析、多属性融合等方法的广泛应用,页岩岩相分类方案被逐步修改完善. 近年来,地质学、工程学、信息科学、地球物理学、计算机科学等多学科交叉融合,特别是人工智能迅速崛起,机器学习等方法的应用可实现多参数多维度的“甜点”优选,为储层评价及预测提供了更为科学的依据(程冰洁等,2022).

3 页岩油研究的热点分析

关键词是文章主题内容的高度概括,关键词频次能够指示该领域研究成果的集中性与广泛程度,可用于判断研究热点(王广才等, 2022). 聚类分析的原理是利用相似度对杂乱信息进行归类,基于关键词词频统计的聚类分析可指示彼此联系密切的主题. 图5是利用VOSviewer可视化软件,设置节点类型为关键词,网络关系为共现,基于Web of Science数据集构建的关键词共现知识图谱. 图中颜色显示聚类,节点大小与关键词频次成正比. 它与字体大小共同反映了节点权重,当两者表现均突出时,说明该节点较为重要.

由于部分关键词与整体聚类偏差较大,会使结果可视化特征弱化,经软件自动筛选后,节点数为932个,连线数为48 024,总连接强度为97 887,形成4个聚类,图中仅显示词频较高的节点与标签. 不同地区页岩油地质特征存在异同点,主要体现在聚集特征、岩矿组合特征、物性特征、有机地化特征、地层压力及流体特征等方面.

结合国内外主要页岩油盆地地质特征(表2),综合每个聚类中关键词热度及密切程度,可将页岩油研究热点概括为页岩油物质条件(红色)、页岩油储集空间(紫色)、页岩油可动性(绿色)和页岩油开发技术(蓝色)4个方面. 其中红色聚类大多聚焦于有机质地化特征及烃源岩热演化,紫色聚类侧重页岩孔隙结构和储集性能,鄂尔多斯盆地词频较高是由于其储层孔隙被广泛关注,绿色聚类侧重页岩渗透率、赋存状态及可动性,蓝色聚类聚焦页岩油工程压裂技术.

3.1 页岩油物质条件

有机质是页岩油生成的物质基础,富有机质页岩连续厚度通常要大于30 m才有利于页岩油生成(表2),但在其他有利条件影响下,连续厚度下限可以降低. 页岩油常集中分布于TOC含量大于2%的地区(张金川等, 2012Lu et al., 2012邹才能等, 2013b),部分地区高值可达7%以上(Jarvie et al., 2012EIA, 2013b, 2015杨智等, 2015). 但TOC含量并非越高越好(宋国奇等, 2013李吉君等, 2014),它与页岩油富集存在正态分布关系(图6),其原因是有机质本身对油的吸附性较强,过高的有机碳含量反而会束缚烃类流体运移. 页岩油生烃母

质多为高碳氢比的Ⅰ型(腐泥型)和Ⅱ1(腐殖腐泥型)有机质,包含少量Ⅱ2型(腐泥腐殖型)有机质,有机质来源为浮游藻类和少量中高等陆源植物混合生源. 优质有机质常表现出有机碳同位素组成偏移特征,是对全球性厌氧事件的响应(张斌等, 2021),与火山活动及全球碳循环相关,如早侏罗世Toarcian大洋缺氧事件为四川盆地自流井组页岩有机质发育及保存提供了良好的沉积环境(Xu et al., 2017). 当泥页岩处于较高成熟阶段时,排烃作用增强导致页岩油丰度较低,因此页岩油主要发现于低熟—成熟早期的泥页岩中(柳波等, 2014李吉君等, 2014宁方兴等, 2015). 但泥页岩属于低孔低渗储层,低成熟度有机质产出的原油,密度大,胶质和沥青质含量较多,黏度高,可动性差,不利于页岩油富集.

有机质保存与稳定分布的沉积构造背景密切相关,全球页岩油盆地大部分为海相克拉通盆地(表2),其次是被动大陆边缘盆地(EIA, 2011, 2013b2015Jarvie, 2012),北美页岩层系发育层位主要分布于上古生界密西西比系(下石炭统)和中生界白垩系,形成于陆棚及半深海—深海环境. 我国陆相页岩油盆地主要为坳陷盆地及断陷盆地(邹才能等, 2012a2015a2022b杨智等, 2015冯国奇等, 2019),发育层系以中生界和新生界居多,沉积环境为淡水-咸水湖盆(邹才能等, 2015b). 复杂的构造沉积条件使页岩沉积岩相类型多变,我国坳陷盆地和断陷盆地页岩岩相存在差异(图3),坳陷盆地页岩岩相组合中长英质和黏土质占比较大,碳酸盐岩矿物含量较低,如鄂尔多斯延长组7段、四川盆地自流井组、松辽盆地青山口组多为薄层状长英质泥页岩相、低-中碳黏土质介壳灰质页岩相、富碳层状粉砂岩相等. 断陷盆地页岩中碳酸盐岩成分占比较高,如我国准噶尔盆地、渤海湾盆地、苏北盆地多为纹层状云灰质泥岩相、高碳块状灰质泥岩相、富碳混合质页岩相等,黏土矿物及长英质含量与陆源碎屑贡献及水体盐度相关,从盆缘到中心变化较大(黎茂稳等, 2022).

依据不同的岩相组合可将页岩油源储组合划分为不同类型,北美常划分为裂缝型、混积型和致密型(图7). 裂缝型以Monterey组为典型;混积型中Eagle Ford组尤为突出,以混积岩系和含夹层的泥页岩为主;致密型以Barnett组为代表,以基质型泥页岩为主(Jarvie, 2012). 我国页岩油源储组合类型主要为夹层型、混积纹层型和基质型(李阳等, 2022黎茂稳等, 2022). 前两者是混积型页岩油依据物质来源及夹层厚度的细分,夹层型通常为泥页岩夹薄层砂岩或碳酸盐岩,常发育于淡水湖盆,多为近源成藏,延长组最为典型,但长7段自上而下的3个亚段受沉积环境的影响,储层砂体厚度有所差异,其类型可进一步细分,如长71和长72亚段勘探对象主要为重力流砂质储层,页岩油多发生短距离运移,其富集关键参数不同于典型页岩油,而长73亚段页岩油则主要滞留于纹层型页岩中,因此在对鄂尔多斯盆地页岩油进行开发时,需要针对不同类型进一步明确开发方案;混积型为长英质、黏土质及碳酸盐岩叠置,多发育于咸水湖盆中,近源成藏与源储一体共存,以孔店组、芦草沟组、潜江组为典型,工程上可采用大规模体积压裂;基质型可与致密型对应,常发育于淡水及咸水湖盆中,源储一体,以青山口组一段和二段为典型,建议针对其力学薄弱面进行多井同步压裂改善其可压性,以提高页岩油采收率.

3.2 页岩油储集空间

页岩油储集空间特征包含孔隙度、孔隙大小、孔隙形态、孔喉结构、孔隙类型、裂缝特征等(Xu et al., 2022),近年来除了利用光学显微镜(OM)、扫描电子显微镜(SEM)、透射电镜(TEM)、场发射环境扫描电镜(FE-SEM)、原子力显微镜(AFM)等常规技术对页岩显微孔隙进行定性观察,明确页岩油孔隙类型及形态,还可以利用高压压汞(MICP)、氮气吸附、核磁共振(NMR)、小角散射(SAS)、三维重构技术如纳米CT、聚焦离子束显微镜(FIB-SEM)等技术,定量表征孔隙-裂缝储集空间网络、孔喉连通性、不同孔隙类型占比、裂缝属性等(刘敬寿等, 2019匡立春等, 2021曾联波等,2022a),从而更准确地评价页岩油储集性能(图8).

合理的孔隙类型组合对页岩油储集性能至关重要,北美地区页岩油多以吸附态存在于有机孔中,有机孔形态多样,如干酪根中发育的有机孔多呈孤立状,部分呈椭圆形、长条形. 运移固体有机质中有机孔呈椭圆形、圆形、不规则多角状,蜂窝状、海绵状成群发育(Loucks and Robert, 2014Hackley and Cardott, 2016王香增等, 2018). 我国页岩油多以游离态赋存于页理缝、石英所形成的粒间孔、长石或碳酸盐矿物溶蚀形成的粒内孔中,以吸附态赋存于黏土矿物脱水形成的粒内孔和黄铁矿粒内孔(匡立春等, 2021黎茂稳等, 2022).

有机质开始发生热演化后的中期成岩阶段,矿物孔隙结构被改造,孔隙类型发生明显变化,孔隙度大幅度提高(张顺等, 2021). 有机质含量在一定程度上会影响页岩总孔隙度,不仅有机质本身发育一定的储集空间,生烃后有机质体积缩小也易形成残留孔隙,富有机质页岩生烃后的孔隙度比生烃演化前增加4.9%(Jarvie et al., 2007Han et al., 2017). 压实作用会使储层原生孔隙缩小,孔隙度大幅度降低,但若页岩储层脆性矿物含量高或地层压力系数较高,能够对页岩孔隙起到支撑作用,孔隙度降低幅度减小.

3.3 页岩油可动性

页岩油可动性是页岩油在开采时顺利流动运移的能力,是泥页岩储层与该储层内的流体两个要素共同作用所产生的结果. 目前具有经济开发价值的页岩油属于轻质油,黏度也较低,只有游离态的页岩油易于在低渗储层流动并被开采,因此计算游离油含油量是评价页岩油可动性的关键. 北美地区主要通过OSI指数(S 1/TOC)来评价游离油含油量,通常S 1/TOC大于100 mg/g的泥页岩层段被认为有利于页岩油产出的层段(Lewan et al., 1979). 为解决当S 1和TOC含量都很低时,使用OSI指数可能会出现“油超越”现象误判的问题,我国学者根据干酪根生烃原理提出自由烃差值法,即生烃量与现存量负值越大,游离油含油量越高(Li et al., 2016),当差值接近零时,可以结合S 1进一步判定. 通过对济阳坳陷游离油含油量进行地化测试,发现S 1大于2 mg/g的井段具有工业产能(王勇等, 2017). 游离油含油量与氯仿沥青“A”/TOC的比值以及页岩埋深也有密切关系(余志远等, 2019).

除了上述提到的矿物对烃类的吸附作用,页岩油的可动性评价还可以从烃类流体本身的性质(页岩油成分、相态、黏度等)和地层压力对烃类排出所起的动力作用来考虑(包友书等, 2016). 芳香烃有利于沥青质的分散,使胶体与沥青质形成的缔合能有效“分散”在饱和烃中,有助于降低黏度(苏铁军, 2007),有利于页岩油的流动. 页岩中的非烃和沥青质更容易吸附在矿物表面,使矿物表面亲油,抑制页岩油的流动(何晋译等, 2019),可通过定义一个MI指数(饱和烃+芳烃/非烃+沥青质)来衡量页岩油的流动性(图10). 原油黏度与饱和烃含量成反比,与胶体和沥青质含量成正比(苏铁军, 2007刘海波和郭绪强, 2008盖平原, 2011). 温度越高,密度和含蜡量越低,黏度越低,越有利于页岩油流动,根据济阳坳陷页岩油黏度与日产量关系可以看出(图10),当黏度小于10 mPa·s时有利于页岩油的产出. 在高压条件下,烃类等流体将成压缩状态存在,随着开采过程的进行,页岩油藏流体压力降低,所受有效应力增加,岩石的孔隙体积减小,烃类等流体因为压力降低而膨胀,孔隙减小和流体膨胀的双重作用驱动烃类等流体排出(宋国奇等, 2013宁方兴, 2015宁方兴等, 2015王勇等, 2015王勇等, 2017). 此外,地层压力对裂缝的发育也有较大影响,地层压力的差异性有利于压裂岩石形成裂缝网络,促进页岩油的运移与流动(王勇等, 2017).

游离油含油量决定了页岩油可采量,储层可改造性、地层压力系数、页岩油黏度三者共同控制了页岩油的工程可动性,如渤海湾盆地游离油整体偏低,但地层高压、储层可压性强且页岩油黏度适中,可通过体积压裂实现页岩油开发;松辽盆地地层压力高,但储层脆性指数低且页岩油黏度高,因此需结合地质力学攻关力学薄弱面,并对原油黏度进行改造,以改善页岩油流动性;鄂尔多斯盆地地层压力系数较小,但储层可改造性良好且页岩油黏度低,可利用原位转化技术提高页岩油采收率(金旭等, 2021).

3.4 页岩油开发手段

“地质-工程双甜点层段”评价对页岩油开发至为重要,其中储层可压裂性为关键指标. 可压裂性主要影响因素包括裂缝网络、脆性、地应力、页岩有效厚度、储层埋深. 天然裂缝尤其是层理缝能够为页岩油提供导流通道,人工压裂时更容易在多孔介质中形成裂缝网络系统,提高页岩渗透率(曾联波等,2022b). 通常石英、长石等脆性矿物含量越高,储层可压裂性更好(马永生等, 2022). 但我国地质条件复杂,构造运动强烈,地应力扰动强,对浅层页岩油进行压裂面临油气散失严重的问题,而超深层页岩油储层压裂则面临较为苛刻的温压条件(石林等, 2020). 因此需要结合页岩油储层特征和工程实际,拟定开发时合适的可压裂层段上限和下限.

页岩油开发不仅需要工程上经济高效,也需要考虑环境污染问题. 当前页岩油开发造成的环境问题为水资源污染、土壤污染和诱发地震. 我国西部地区生态环境脆弱,水平井多段压裂的单井用水量远高于常规直井,会进一步加剧淡水资源匮乏(张东晓和杨云婷, 2015). 开发过程中压裂液不慎泄露,所含化学物质会污染地下水质,造成土壤及农作物污染. 自2013年起,美国中部和东部页岩油开发诱发了多起震级大于3.0 M以上的地震,学者发现在压裂过程中减少注入量,降低注入速率,能够有效减少地震活动(Boak et al., 2020). 因此除了最常见的水力压裂,还需要大力发展多种新型压裂技术以降低开发过程中环境污染的风险,如高导流通道压裂(Gillard et al., 2010)、CO2大体积压裂及封存(Jia et al., 2019)、“密切割”水平井改造技术等(于学亮等, 2020). 多元线性回归、决策树、随机森林、神经网络等机器学习方法提供了三维建模新思路,能有效预测压裂过程中的虚拟压力、渗透率、裂缝网络、产能等,降低了压裂的经济成本(何玉荣等, 2021). 微地震裂缝监测手段可以对裂缝展布形态的模拟结果进行较为准确的校正,提高数值模拟精度(蒲春生等, 2020).

4 发展趋势及展望

尽管页岩油研究已经取得了诸多进展,但仍面临许多难题与挑战,主要体现在以下几方面:

(1)我国陆相页岩油地质条件复杂,沉积相变快,非均质性强,难以统一界定有利的TOC含量及成熟度标准,岩相类型及成因复杂,不同类型有机质演化导致页岩含油量存在差异,相变过程中页岩油赋存状态也会发生转变;(2)我国陆相页岩孔隙类型主要为矿物所形成的粒间孔、晶间孔、粒内孔、页理缝等,孔隙类型演化与改造很大程度受成岩作用控制,定量表征页岩油在孔-缝网络中的赋存状态及综合评价页岩储集性能仍有待提升;(3)我国页岩油油品较重,气油比低,这种高密度、高黏度、储集特征复杂的特性也使得页岩油可动性较差,勘探开发难度急剧增加,当前对页岩油在孔隙空间内赋存量、流动能力、流动速率、流动条件、流动机制等方面认识不清,现有的游离油含油量表征方法都存在一定的轻烃损失,缺乏全面的可动性评价方法体系;(4)页岩油的商业化开发得益于压裂技术的进步,但页岩的层理结构及泥质成分容易对人工形成的复杂裂缝系统产生影响,结合地质-工程部分参数评价页岩可压裂性仍不够完善,压裂液泄漏造成的环境污染问题需进一步得到解决.

针对上述问题,今后应加强以下研究及勘探开发工作(图11):(1)加强细粒沉积岩研究,利用钻井资料、测井资料、岩心资料,结合高分辨率显微镜及光谱仪、XRF高光谱扫描仪、岩相分层表征Qemscan分析仪,建立三维数字岩心,精细雕刻岩相组合体,寻找有利页岩油类型;(2)在利用场发射扫描电镜、透射电镜对孔隙进行定性表征的基础上,结合纳米CT、三维重构模拟、液氮吸附、核磁共振、小角中子散射等技术,精细评价页岩油储集空间,明确页岩油成储下限,进而探究页岩油成储机理;(3)在明确页岩油赋存空间的基础上,利用能谱分析、多温有机质萃取、等温吸附实验、溶胀实验、高频核磁共振,结合干酪根生烃理论、分析动力学及蒙特卡洛方法,多方法有效计算可动油含量,还可以利用离心法、弹性开采法、气体驱替法和气体吞吐法对页岩可动油进行模拟,并充分考虑储层矿物成分、流体组成、黏度、地层压力等因素对页岩油可动性的影响,形成多因素多方法结合的页岩油可动性评价方案;(4)加强新型压裂技术如高导流通道压裂、CO2大体积压裂技术、“密切割”水平井改造技术等研究,研发新型绿色压裂剂以减少对环境的污染,利用微地震检测、机器学习、深入学习等方法,对压裂网络进行数值模拟,实现页岩油高效开发的精准预测,促进我国页岩油规模化发展,以建立安全可靠的资源能源储备.

参考文献

[1]

Bao, Y. S., Zhang, L. Y., Zhang, J. G., et al., 2016. Factors Influencing Mobility of Paleogene Shale oil in Dongying Sag, Bohai Bay Basin. Oil and Gas Geology, 37(3): 408-414 (in Chinese with English abstract).

[2]

Boak, J., Kleinberg, R., 2020. Shale Gas, Tight Oil, Shale Oil and Hydraulic Fracturing. Future Energy. Elsevier, Amsterdam, 67-95. https://doi.org/10.1016/b978-0-08-102886-5.00004-9

[3]

Chen, X., Wang, M., Yan, Y. X., et al., 2011. Accumulation Conditions for Continental Shale Oil and Gas in the Biyang Depression. Oil and Gas Geology, 32(4): 568-576 (in Chinese with English abstract).

[4]

Cheng, B. J., Xu, T. J., Luo, S. Y., et al., 2022. Method and Practice of Deep Favorable Shale Reservoir Prediction Based on Machine Learning. Petroleum Exploration and Development, 49(5): 918-928 (in Chinese with English abstract).

[5]

Cui, J. W., Zhu, R. K., Yang, Z., et al., 2015. Progresses and Enlightenment of Overseas Shale Oil Exploration and Development. Unconventional Oil and Gas, 2(4): 68-82 (in Chinese with English abstract).

[6]

Donovan, A., Evenick, J., Banfield, L., 2017. An Organofacies-Based Mudstone Classification for Unconventional Tight Rock & Source Rock PlaysProceedings of the 5th Unconventional Resources Technology Conference. July 24-26, 2017. Austin, Texas, USA. American Association of Petroleum Geologists, Tulsa.

[7]

EIA, 2011. Review of Emerging Resources: US Shale Gas and Shale Oil Plays. EIA Analysis & Projections, Washington.

[8]

EIA, 2013a. Technically Recoverable Shale Oil and Shale Gas Resources: An Assessment of 137 Shale Formations in 41 Countries Outside the United States. EIA Analysis & Projections, Washington.

[9]

EIA, 2013b. Status and Outlook for Shale Gas and Tight Oil Development in the U.S. EIA Pressroom, Washington.

[10]

EIA, 2015. Annual Energy Outlook 2015 with Projections to 2014. EIA Analysis & Projections, Washington.

[11]

EIA, 2017. Tight Oil Expected to Make up Most of U.S. Oil Production Increase through 2040. EIA Today in Energy, Washington.

[12]

EIA, 2022. Drilling Productivity Report: For Key Tight Oil and Shale Gas Regions. EIA Independent Statistics &Analysis, Washington.

[13]

Fan, Y., Liu, K., Pu, X., et al., 2022. Morphological Classification and Three-Dimensional Pore Structure Reconstruction of Shale Oil Reservoirs: A Case from the Second Member of Kongdian Formation in the Cangdong Sag, Bohai Bay Basin, East China. Petroleum Exploration and Development, 49(5): 943-954 (in Chinese with English abstract).

[14]

Fang, X. X, Yuan, K., Lin, T., 2017. Potential Asessment of the Shale Gas and Shale Oil Resources in Libya. China Mining Magazine, 26(S2): 18-22(in Chinese with English abstract).

[15]

Fang, X. X., Guo, Y. C., Wang, P., et al., 2020. The Progress of Research on Tight Oil Accumulation and Several Scientific Issues Requiring Further Study. Geology in China, 47(1): 43-56 (in Chinese with English abstract).

[16]

Feng, G. Q., Li, J. J., Liu, J. W., et al., 2019. Discussion on the Enrichment and Mobility of Continental Shale Oil in Biyang Depression. Oil and Gas Geology, 40(6): 1236-1246 (in Chinese with English abstract).

[17]

Fu, Q., Liu, Q. D., Liu, S. L., et al., 2020. Shale Oil Accumulation Conditions in the Second Member of Paleogene Funing Formation, Gaoyou Sag, Subei Basin. Petroleum Geology and Experiment, 42(4): 625-631 (in Chinese with English abstract).

[18]

Gai, P. Y., 2011. Laboratory Research on Gel as Fracturing Artificial Barrier Material. Oilfield Chemistry, 28(1): 54-57 (in Chinese with English abstract).

[19]

Gao, G., Liu, X. Y., Wang, Y. H., et al., 2013. Characteristics and Resource Potential of the Oil Shale of Chang 7 Layer in Longdong Area, Ordos Basin. Earth Science Frontiers, 20(2): 140-146 (in Chinese with English abstract).

[20]

Gao, Z. Y., Yang, X. B., Hu, C. H., et al., 2018. Characterizing the Pore Structure of Low Permeability Eocene Liushagang Formation Reservoir Rocks from Beibuwan Basin in Northern South China Sea. Marine and Petroleum Geology, 99: 107-121. https://doi.org/10.1016/j.marpetgeo.2018.10.005

[21]

Gillard, M., Medvedev, O., Pena, A., et al., 2010. A New Approach to Generating Fracture Conductivity. Journal of Cerebral Blood Flow and Metabolism, 25: 19-22

[22]

Hackley, P. C., Cardott, B. J., 2016. Application of Organic Petrography in North American Shale Petroleum Systems: a Review. International Journal of Coal Geology, 163: 8-51. https://doi.org/10.1016/j.coal.2016.06.010

[23]

Han, K., Wang, Y., Cha, Q., 2015. Exploration Potential and Targets of Jurassic System in Central Sichuan. Petroleum Science and Technology Forum, 34(6): 51-57 (in Chinese with English abstract).

[24]

Han, Y. J., Horsfield, B., Wirth, R., et al., 2017. Oil Retention and Porosity Evolution in Organic-Rich Shales. AAPG Bulletin, 101(6): 807-827. https://doi.org/10.1306/09221616069

[25]

He, J. Y., Cai, J. G., Lei, T. Z., et al., 2019. Characteristics of Soluble Organic Matter of Paleogene Shale in Dongying Sag and Prediction of Shale Oil “Sweet Spots”. Petroleum Geology and Recovery Efficiency, 26(1): 174-182 (in Chinese with English abstract).

[26]

He, T. H., Li, W. H., Tan, Z. Z., et al., 2019. Mechanism of Shale Oil Accumulation in the Hetaoyuan Formation from the Biyang Depression,Nanxiang Basin. Oil and Gas Geology, 40(6): 1259-1269 (in Chinese with English abstract).

[27]

He, Y. R., Song, Z. C., Zhang, Y. M., et al., 2021. Review on Application of Machine Learning in Hydraulic Fracturing. Journal of China University of Petroleum(Edition of Natural Science), 45(6): 127-135 (in Chinese with English abstract).

[28]

Horsfield, B., Schulz, H. M., Bernard, S., et al., 2018. Oil and Gas Shales. Hydrocarbons, Oils and Lipids: Diversity, Origin, Chemistry and Fate. Springer International Publishing, Cham, 1-34. https://doi.org/10.1007/978-3-319-54529-5_18-1

[29]

Jarvie, D. M., 2012. Shale Resource Systems for Oil and Gas: Part2-Shale-Oil Resource Systems. AAPG Memoir, 97: 89-119. https://doi.org/10.1306/13321447m973489.

[30]

Jarvie, D. M., Hill, R. J., Ruble, T. E., et al., 2007. Unconventional Shale-Gas Systems: The Mississippian Barnett Shale of North-Central Texas as one Model for Thermogenic Shale-Gas Assessment. AAPG Bulletin, 91(4): 475-499. https://doi.org/10.1306/12190606068

[31]

Jia, B., Tsau, J. S., Barati, R., 2019. A Review of the Current Progress of CO2 Injection EOR and Carbon Storage in Shale Oil Reservoirs. Fuel, 236: 404-427. https://doi.org/10.1016/j.fuel.2018.08.103

[32]

Jiang, Z. X., Zhang, W. Z., Liang, C., et al., 2014. Characteristics and Evaluation Elements of Shale Oil Reservoir. Acta Petrolei Sinca, 35(1): 184-196 (in Chinese with English abstract).

[33]

Jin, T., Zhang, W., Bai, R., et al., 2022. Characteristics on Shale Reservoirs of Lower Jurassic Ziliujing Formation,Eastern Sichuan Basin. Natural Gas Exploration and Development, 45(1): 87-97 (in Chinese with English abstract).

[34]

Jin, X., Li, G., Meng, S., et al., 2021. Microscale Comprehensive Evaluation of Continental Shale Oil Recoverability. Petroleum Exploration & Development, 48(1): 222-232 (in Chinese with English abstract).

[35]

Jin, Z. J., Bai, Z. R., Gao, B., et al., 2019. Has China Ushered in the Shale Oil and Gas Revolution? Oil and Gas Geology, 40(3): 451-458 (in Chinese with English abstract).

[36]

Kernan, N. D., 2015. Structural and Facies Characterization of the Niobrara Formation in Goshen and Laramie Counties, Wyoming(Dissertation). Colorado School of Mines, Colorado.

[37]

Kuang, L. C., Hou, L. H., Yang, Z., et al., 2021. Key Parameters and Methods of Lacustrine Shale Oil Reservoir Characterization. Acta Petrolei Sinca, 42(1): 1-14 (in Chinese with English abstract).

[38]

Lei, Q., Weng, D. W., Xiong, S. C., et al., 2021. Progress and Development Directions of Shale Oil Reservoir Stimulation Technology of China National Petroleum Corporation. Petroleum Exploration and Development, 48(5): 1198-1207. https://doi.org/10.1016/S1876-3804(21)60102-7

[39]

Lewan, M. D., Winters, J. C., McDonald, J. H., 1979. Generation of Oil-Like Pyrolyzates from Organic-Rich Shales. Science, 203(4383): 897-899. https://doi.org/10.1126/science.203.4383.897

[40]

Li, H., Jiang, Z. X., Deng, Y., et al., 2022. Geological Formation Conditions and Enrichment Characteristics of Shale Oil in the Weixinan Sag, South China Sea. Journal of China University of Mining and Technology, 51(5): 1-17 (in Chinese with English abstract).

[41]

Li, J. B., Wang, M., Jiang, C. Q., et al., 2022. Sorption Model of Lacustrine Shale Oil: Insights from the Contribution of Organic Matter and Clay Minerals. Energy, 260: 125011. https://doi.org/10.1016/j.energy.2022.125011

[42]

Li, J. J., Shi, Y. L., Zhang, X. W., et al., 2014. Control Factors of Enrichment and Producibility of Shale Oil: A Case Study of Biyang Depression. Earth Science, 39(7): 848-857 (in Chinese with English abstract).

[43]

Li, M. W., Ma, X. X., Jiang, Q. G., et al., 2019. Enlightenment from Formation Conditions and Enrichment Characteristics of Marine Shale Oil in North America. Petroleum Geology and Recovery Efficiency, 26(1): 13-28 (in Chinese with English abstract).

[44]

Li, M. W., Ma, X. X., Jin, Z. J., et al., 2022. Diversity in the Lithofacies Assemblages of Marine and Lacustrine Shale Strata and Significance for Unconventional Petroleum Exploration in China. Oil and Gas Geology, 43(1): 1-25 (in Chinese with English abstract).

[45]

Li, S. C., Zhang, J. Y., Gong, F. H., et al., 2017. Lower Limits of Porosity and Permeability of Shale Oil Reservoirs in the Xingouzui Formation, Jianghan Basin. Geological Bulletin of China, 36(4): 654-663 (in Chinese with English abstract).

[46]

Li, S. F., Hu, S. Z., Xie, X. N., et al., 2016. Assessment of Shale Oil Potential Using a New Free Hydrocarbon Index. International Journal of Coal Geology, 156: 74-85. https://doi.org/10.1016/j.coal.2016.02.005

[47]

Li, X. L., Sun, W., 2022. Seven Properties Research on Relationship Evaluation of Shale Oil Reservoir: A Case Study of the Second Member of Funing Formation in Qintong Sag of Subei Basin. Unconventional Oil and Gas: 1-9(in Chinese with English abstract).

[48]

Li, Y., Zhao, Q. M., Lu, Q., et al., 2022. Evaluation Technology and Practice of Continental Shale Oil Development in China. Petroleum Exploration and Development, 49(5): 955-964 (in Chinese with English abstract).

[49]

Liang, C., Wu, J., Cao, Y. C., et al., 2022. Storage Space Development and Hydrocarbon Occurrence Model Controlled by Lithofacies in the Eocene Jiyang Sub-Basin, East China: Significance for Shale Oil Reservoir Formation. Journal of Petroleum Science and Engineering, 215: 110631. https://doi.org/10.1016/j.petrol.2022.110631

[50]

Liang, S. J., Huang, Z. L., Liu, B., et al., 2012. Formation Mechanism and Enrichment Conditions of Lucaogou Formation Shale Oil from Malang Sag, Santanghu Basin. Acta Petrolei Sinca, 33(4): 588-594 (in Chinese with English abstract).

[51]

Liu, B., Lu, Y. F., Ran, Q. C., et al., 2014. Geological Conditions and Exploration Potential of Shale Oil in Qingshankou Formation, Northern Songliao Basin. Oil and Gas Geology, 35(2): 280-285 (in Chinese with English abstract).

[52]

Liu, B., Lu, Y. F., Zhao, R., et al., 2012. Formation overpressure and shale oil enrichment in the shale system of Lucaogou Formation, Malang Sag, Santanghu Basin, NW China. Petroleum Exploration & Development, 39(6): 699-705 (in Chinese with English abstract).

[53]

Liu, C. Q., Jiang, X. F., Wu, M. Y., 2021. Global Oil and Gas Industry Development Report in 2021. Petroleum Industry Press, Beijing,3(in Chinese).

[54]

Liu, H. B., Guo, X. Q., 2008. Influence of Property and Structure of Crude Oil on Its Viscosity. Xinjiang Petroleum Geology, (3): 347-349(in Chinese with English abstract).

[55]

Liu, H. M., Yu, B. S., Xie, Z. H., et al., 2018. Characteristics and Implications of Micro-Lithofacies in Lacustrine-Basin Organic-Rich Shale: a Case Study of Jiyang Depression, Bohai Bay Basin. Acta Petrolei Sinca, 39(12): 1328-1343 (in Chinese with English abstract).

[56]

Liu, J. S., Ding, W. L., Xiao, Z. K., et al., 2019. Advances in Comprehensive Characterization and Prediction of Reservoir Fractures. Progress in Geophysics, 34(6): 2283-2300 (in Chinese with English abstract).

[57]

Liu, Y., 2018. Study on Shale Oil Reservoir Characteristics of Shahejie Formation in Jiyang Depression, Bohai Bay Basin(Dissertation). Chengdu University of Technology, Chengdu(in Chinese with English abstract).

[58]

Long, H. Q., Li, S. P., 2022. The Research on the Heterogeneity of Shale Formations and Its Controlling Factors: A Case Study of the Second Member of Funing Formation in Subei Basin. Unconventional Oil and Gas, 9(4): 78-90 (in Chinese with English abstract).

[59]

Loucks, R. G., Robert, M., 2014. Scanning-Electron-Microscope Petrographic Evidence for Distinguishing Organic-Matter Pores Associated with Depositional Organic Matter versus Migrated Organic Matter in Mudrocks. Gulf Coast Association of Geological Societies, 3: 51-60.

[60]

Loucks, R. G., Ruppel, S. C., 2007. Mississippian Barnett Shale: Lithofacies and Depositional Setting of a Deep-Water Shale-Gas Succession in the Fort Worth Basin, Texas. AAPG Bulletin, 91(4): 579-601. https://doi.org/10.1306/11020606059

[61]

Lu, S. F., Huang, W. B., Chen, F. W., et al., 2012. Classification and Evaluation Criteria of Shale Oil and Gas Resources: Discussion and Application. Petroleum Exploration and Development, 39(2): 268-276. https://doi.org/10.1016/S1876-3804(12)60042-1

[62]

Ma, Y. S., Cai, X. Y., Zhao, P. R., et al., 2022. Geological Characteristics and Exploration Practices of Continental Shale Oil in China. Acta Geologica Sinica, 96(1): 155-171 (in Chinese with English abstract).

[63]

Ma, Y. S., Feng, J. H., Mou, Z. H., et al., 2012. The Potential and Exploring Progress of Unconventional Hydrocarbon Resources in SINOPEC. Strategic Study of CAE, 14(6): 22-30 (in Chinese with English abstract).

[64]

Maugeri, L., 2013. The Shale Oil Boom: a U.S. Phenomenon. Harvard University Press, Cambridge, 2.

[65]

Mehana, M., Guiltinan, E., Vesselinov, V., et al., 2021. Machine-Learning Predictions of the Shale Wells’ Performance. Journal of Natural Gas Science and Engineering, 88: 103819. https://doi.org/10.1016/j.jngse. 2021. 103819

[66]

Meng, M., Zhong, R. Z., Wei, Z. L., 2020. Prediction of Methane Adsorption in Shale: Classical Models and Machine Learning Based Models. Fuel, 278: 118358. https://doi.org/10.1016/j.fuel.2020.118358

[67]

Ning, F. X., 2015. The Main Control Factors of Shale Oil Enrichment in Jiyang Depression. Acta Petrolei Sinca, 36(8): 905-914 (in Chinese with English abstract).

[68]

Ning, F. X., Wang, X. J., Hao, X. F., et al., 2015. Evaluation Method of Shale Oil Sweetspots in Jiyang Depression. Science Technology and Engineering, 15(35): 11-16 (in Chinese with English abstract).

[69]

Pu, C. S., Zheng, H., Yang, Z. P., et al., 2020. Research Status and Development Trend of the Formation Mechanism of Complex Fractures by Staged Volume Fracturing in Horizontal Wells. Acta Petrolei Sinca, 41(12): 1734-1743 (in Chinese with English abstract).

[70]

Robison, C. R., Castano, J. R., 1997. Hydrocarbon source rock variability within the Austin Chalk and Eagle Ford Shale (Upper Cretaceous), East Texas, U.S.A. International Journal of Coal Geology, 34(3-4): 287-305. https://doi.org/10.1016/S0166-5162(97)00027-X.

[71]

Shi, L., Zhang, K. P., Mu, L. J., 2020. Discussion of Hydraulic Fracturing Technical Issues in Shale Oil Reservoirs. Petroleum Science Bulletin, 5(4): 496-511 (in Chinese with English abstract).

[72]

Song, G. Q., Zhang, L. Y., Lu, S. F., et al., 2013. Resource Evaluation Method for Shale Oil and Its Application. Earth Science Frontiers, 20(4): 221-228 (in Chinese with English abstract).

[73]

Su, T. J., Zheng, Y. C., 2007. Correlations Between Heavy Oil Composition and its Viscosity. Journal of Yangtze University, 1: 60-62 (in Chinese with English abstract).

[74]

Sun, S. S., Dong, D., Li, Y., et al., 2021. Geological Characteristics and Controlling Factors of Hydrocarbon Accumulation in Terrestrial Shale in the Da’anzhai Member of the Jurassic Ziliujing Formation,Sichuan Basin. Oil and Gas Geology, 42(1): 124-135 (in Chinese with English abstract).

[75]

Treadgold, G., Mclain, B., Sinclair, S., 2011. Eagle Ford Shale Prospecting with 3D Seismic and Microseismic Data. Rio de Janeiro.

[76]

Wang, G. C., Wang, Y. X., Liu, F., et al., 2022. Advances and Trends in Hydrogeochemical Studies: Insights from Bibliometric Analysis. Earth Science Frontiers, 29(3): 25-36 (in Chinese with English abstract).

[77]

Wang, M., Chen, X., Yan, Y. X, et al., 2013. Geological Characteristics and Evaluation of Continental Shale Oil in Biyang Sag of Nanxiang Basin. Journal of Palaeogeography, 15(5): 663-671 (in Chinese with English abstract).

[78]

Wang, M., Ma, R., Li, J. B., et al., 2019. Occurrence Mechanism of Lacustrine Shale Oil in the Paleogene Shahejie Formation of Jiyang Depression, Bohai Bay Basin, China. Petroleum Exploration and Development, 46(4): 833-846. https://doi.org/10.1016/S1876-3804(19)60242-9

[79]

Wang, S. L., Wu, X. S., Zhang, W., et al., 2016. Progress and Trend of Global Exploration and Development for Shale Resources. China Mining Magazine, 25(2): 7-11 (in Chinese with English abstract).

[80]

Wang, X. Z., Zhang, L. X., Lei, Y. H., et al., 2018. Characteristics of Migrated Solid Organic Matters and Organic Pores in Low Maturity Lacustrine Shale:a Case Study of the Shale in Chang 7 Oil-Bearing Formation of Yanchang Formation, Southeastern Ordos Basin. Acta Petrolei Sinca, 39(2): 141-151 (in Chinese with English abstract).

[81]

Wang, X. K., Sheng, J. J., 2017. Effect of Low-Velocity Non-Darcy Flow on Well Production Performance in Shale and Tight Oil Reservoirs. Fuel, 190: 41-46. https://doi.org/10.1016/j.fuel.2016.11.040

[82]

Wang, Y., Liu, H. M., Song, G. Q., et al., 2017. Enrichment Controls and Models of Shale Oil in the Jiyang Depression, Bohai Bay Basin. Geological Journal of China Universities, 23(2): 268-276 (in Chinese with English abstract).

[83]

Wang, Y., Song, G. Q., Liu, H. M., et al., 2015. Main Control Factors of Enrichment Characteristics of Shale Oil in Jiyang Depression. Petroleum Geology and Recovery Efficiency, 22(4): 20-25 (in Chinese with English abstract).

[84]

Wu, X. L., Gao, B., Ye, X., et al., 2013. Shale Oil Accumulation Conditions and Exploration Potential of Faulted Basins in the East of China. Oil and Gas Geology, 34(4): 455-462 (in Chinese with English abstract).

[85]

Xi, K. L., Li, K., Cao, Y. C., et al., 2020. Laminae Combination and Shale Oil Enrichment Patterns of Chang 73 Sub-Member Organic-Rich Shales in the Triassic Yanchang Formation, Ordos Basin, NW China. Petroleum Exploration and Development, 47(6): 1342-1353. https://doi.org/10.1016/S1876-3804(20)60142-8

[86]

Xu, W. M., Ruhl, M., Jenkyns, H. C., et al., 2017. Carbon Sequestration in an Expanded Lake System during the Toarcian Oceanic Anoxic Event. Nature Geoscience, 10(2): 129-134. https://doi.org/10.1038/ngeo2871

[87]

Xu, Y., Lun, Z. M., Pan, Z. J., et al., 2022. Occurrence Space and State of Shale Oil: a Review. Journal of Petroleum Science and Engineering, 211: 110183. https://doi.org/10.1016/j.petrol.2022.110183

[88]

Yan, D. T., Lu, J., Wei, X. S., et al., 2019. Sediment Environment and Major Controlling Factors of Organic Rich Shales in the Rift Lake Basin: A Case Study of the 2nd Member of Liushagang Formation of the Weixinan Sag. China Offshore Oil and Gas, 31(5): 21-29 (in Chinese with English abstract).

[89]

Yang, H., Li, S. X., Liu, X. Y., 2013. Characteristics and Resource Prospects of Tight Oil and Shale Oil in Ordos Basin. Acta Petrolei Sinca, 34(1): 1-11 (in Chinese with English abstract).

[90]

Yang, L., Jin, Z. J., 2019. Global Shale Oil Development and Prospects. China Petroleum Exploration, 24(5): 553-559 (in Chinese with English abstract).

[91]

Yang, Z. H., Zhao, H. B., Huang, Y., et al., 2022. Application of Seismic-Constrained 3D Modeling Technology in Geoscience and Engineering Integration of Gulong Shale Oil in Songliao Basin. Petroleum Geology and Oilfield Development in Daqing, 41(3): 103-111 (in Chinese with English abstract).

[92]

Yang, Z., Hou, L. H., Tao, S. Z., et al., 2015. Formation Conditions and “Sweet Spot ” Evaluation of Tight Oil and Shale Oil Petroleum Exploration and Development, 42(5): 555-565 (in Chinese with English abstract).

[93]

Yang, Z., Zou, C. N., Hou, L. H., et al., 2019. Division of Fine-Grained Rocks and Selection of “Sweet Sections” in the Oldest Continental Shale in China: Taking the Coexisting Combination of Tight and Shale Oil in the Permian Junggar Basin. Marine and Petroleum Geology, 109: 339-348. https://doi.org/10.1016/j.marpetgeo.2019.06.010

[94]

Yao, H. S., Zan, L., Gao, Y. Q., et al., 2021. Main Controlling Factors for the Enrichment of Shale Oil and Significant Discovery in Second Member of Paleogene Funing Formation, Qintong Sag, Subei Basin. Petroleum Geology and Experiment, 43(5): 776-783 (in Chinese with English abstract).

[95]

Yu, X. L., Xu, Y., Weng, D. W., et al., 2020. Factors Influencing the Productivity of the Multi-Fractured Shale Oil Reservoir with Tighter Clusters. Journal of Southwest Petroleum University(Science & Technology Edition), 42(3): 132-143 (in Chinese with English abstract).

[96]

Yu, Z. Y., Zhang, X. W., Tan, J. J., et al., 2019. Occurrence Characteristics and Mobility of Shale Oil in Biyang Sag. Petroleum Geology and Engineering, 33(1): 42-46 (in Chinese with English abstract).

[97]

Zan, L., Luo, W. F., Yin, Y. L., et al., 2021. Formation Conditions of Shale Oil and Favorable Targets in the Second Member of Paleogene Funing Formation in Qintong Sag, Subei Basin. Petroleum Geology and Experiment, 43(2): 233-241 (in Chinese with English abstract).

[98]

Zeng, L. B., Lu, W. Y., Xu, X., et al., 2022. Development Characteristics, Formation Mechanism and Hydrocarbon Significance of Bedding Fractures in Typical Tight Sandstone and Shale. Acta Petrolei Sinca, 43(2): 180-191 (in Chinese with English abstract).

[99]

Zeng, L. B., Ma, S. J., Tian, H., et al., 2022. Research Progress of Natural Fractures in Organic Rich Shale. Earth Science: 1-15(in Chinese with English abstract).

[100]

Zhang, B., Mao, Z., Zhang, Z., et al., 2021. Black Shale Formation Environment and Its Control on Shale Oil Enrichment in Triassic Chang 7 Member, Ordos Basin, NW China. Petroleum Exploration and Development, 48(6): 1127-1136 (in Chinese with English abstract).

[101]

Zhang, D. X., 2015. Environmental Impacts of Hydraulic Fracturing in Shale Gas Development in the United States. Petroleum Exploration and Development, 42(6): 801-807 (in Chinese with English abstract).

[102]

Zhang, J. C., Lin, L. M., Li, Y. X., et al., 2012. Classification and Evaluation of Shale Oil. Earth Science Frontiers, 19(5): 322-331 (in Chinese with English abstract).

[103]

Zhang, P. F., Lu, S. F., Li, W. H., et al., 2016. Lower Limits of Porosity and Permeability of Shale Oil Reservoirs in the Xingouzui Formation, Jianghan Basin. Oil and Gas Geology, 37(1): 93-100 (in Chinese with English abstract).

[104]

Zhang, S., Liu, H. M., Liu, Y. L., et al., 2021. Shale Oil Geological Dessert Types in Jiyang Depression, Bohai Bay Basin. Geological Review, 67(S1): 237-238(in Chinese with English abstract).

[105]

Zhang, S., Liu, H. M., Liu, Y. L., et al., 2021. Shale Oil Geological Dessert Types in Jiyang Depression,Bohai Bay Basin. Geological Review, 67(S1): 237-238(in Chinese with English abstract).

[106]

Zhao, W. Z., Hu, S. Y., Hou, L. H., et al., 2020. Types and Resource Potential of Continental Shale Oil in China and Its Boundary with Tight Oil. Petroleum Exploration and Development, 47(1): 1-10 (in Chinese with English abstract).

[107]

Zhao, X. Z., Zhou, L. H., Pu, X. G., et al., 2018. Geological Characteristics of Shale Rock System and Shale Oil Exploration Breakthrough in a Lacustrine Basin: A Case Study from the Paleogene 1st Sub-Member of Kong 2 Member in Cangdong Sag, Bohai Bay Basin, China. Petroleum Exploration and Development, 45(3): 361-372 (in Chinese with English abstract).

[108]

Zhi, D. M., Song, Y., He, W. J., et al., 2019a. Geological Characteristics, Resource Potential and Exploration Direction of Shale Oil in Middle-Lower Permian, Junggar Basin. Xinjiang Petroleum Geology, 40(4): 389-401(in Chinese with English abstract).

[109]

Zhi, D. M., Tang, Y., Zheng, M. L., et al., 2019b. Geological Characteristics and Accumulation Controlling Factors of Shale Reservoirs in Fengcheng Formation, Mahu Sag, Junggar Basin. China Petroleum Exploration, 24(5): 615-623(in Chinese with English abstract).

[110]

Zhou, J. M., Zhang, H. C., Wang, M. R., 2021. Machine Learning With Physical Empirical Model Constraints for Prediction of Shale Oil Production. Applied Mathematics and Mechanics, 42(9): 881-890 (in Chinese with English abstract).

[111]

Zhou, L. H., Chen, Z. W., Han, G. M., et al., 2019. Geological Characteristics and Shale Oil Exploration Potential of Lower First Member of Shahejie Formation in Qikou Sag, Bohai Bay Basin. Earth Science, 44(8): 2736-2750 (in Chinese with English abstract).

[112]

Zhou, L. H., Pu, X. G., Xiao, D. Q., et al., 2018. Geological Conditions for Shale Oil Formation and the Main Controlling Factors for the Enrichment of the 2nd Member of Kongdian Formation in the Cangdong Sag, Bohai Bay Basin. Natural Gas Geoscience, 29(9): 1323-1332 (in Chinese with English abstract).

[113]

Zhu, D. Y., Wang, X. J., Hao, X. F., et al., 2016. Study on Sequence Stratigraphic Division of Oil Shale in Dongying Sag. Petroleum Geology and Recovery Efficiency, 23(2): 52-56 (in Chinese with English abstract).

[114]

Zou, C. N., Ma, F., Pan, S. Q., et al., 2022a. Formation and Distribution Potential of Global Shale Oil and the Theoretical and Technological Progress of Continental Shale Oil in China. Earth Science Frontiers: 1-16(in Chinese with English abstract).

[115]

Zou, C. N., Yang, Z., Cui, J. W., et al., 2013a. Formation Mechanism, Geological Characteristics and Development Strategy of Nonmarine Shale oil in China. Petroleum Exploration and Development, 40(1): 14-26(in Chinese with English abstract).

[116]

Zou, C. N., Yang, Z., Dong, D. Z., et al., 2022b. Formation, Distribution and Prospect of Unconventional Hydrocarbons in Source Rock Strata in China. Earth Science, 47(5): 1517-1533(in Chinese with English abstract).

[117]

Zou, C. N., Yang, Z., Tao, S. Z., et al., 2012a. Nano-Hydrocarbon and the Accumulation in Coexisting Source and Reservoir. Petroleum Exploration and Development, 39(1): 13-26(in Chinese with English abstract).

[118]

Zou, C. N., Zhai, G. M., Zhang, G. Y., et al., 2015a. Formation, Distribution, Potential and Prediction of Global Conventional and Unconventional Hydrocarbon Resources. Petroleum Exploration and Development, 42(1): 13-25(in Chinese with English abstract).

[119]

Zou, C. N., Zhang, G. S., Yang, Z., et al., 2013b. Geological Concepts, Characteristics, Resource Potential and Key Techniques of Unconventional Hydrocarbon: On Unconventional Petroleum Geology. Petroleum Exploration and Development, 40(4): 385-399(in Chinese with English abstract).

[120]

Zou, C. N., Zhu, R. K., Bai, B., et al., 2015b. Significance, Geologic Characteristics, Resource Potential and Future Challenges of Tight Oil and Shale Oil. Bulletin of Mineralogy, Petrology and Geochemistry, 34(1): 3-17(in Chinese with English abstract).

[121]

Zou, C. N., Zhu, R. K., Wu, S. T., et al., 2012b. Types, Characteristics, Genesis and Prospects of Conventional and Unconventional Hydrocarbon Accumulations: Taking Tight Oil and Tight Gas in China as an Instance. Acta Petrolei Sinca, 33(2): 173-187(in Chinese with English abstract).

[122]

包友书,张林晔,张金功,等, 2016. 渤海湾盆地东营凹陷古近系页岩油可动性影响因素. 石油与天然气地质, 37(3): 408-414.

[123]

陈祥,王敏,严永新,等, 2011. 泌阳凹陷陆相页岩油气成藏条件. 石油与天然气地质, 32(4): 568-576.

[124]

程冰洁,徐天吉,罗诗艺,等, 2022. 基于机器学习的深层页岩有利储集层预测方法及实践. 石油勘探与开发, 49(5): 918-928.

[125]

崔景伟,朱如凯,杨智,等, 2015. 国外页岩层系石油勘探开发进展及启示. 非常规油气, 2(4): 68-82.

[126]

范雨辰,刘可禹,蒲秀刚,等, 2022. 页岩储集空间微观形态分类及三维结构重构——以渤海湾盆地沧东凹陷古近系孔店组二段为例. 石油勘探与开发, 49(5): 943-954.

[127]

方欣欣,郭迎春,王朋,等, 2020. 致密油成藏研究进展与待解决的重要科学问题. 中国地质, 47(1): 43-56.

[128]

方欣欣,苑坤,林拓, 2017. 利比亚页岩油气资源潜力分析. 中国矿业, 26(S2): 18-22.

[129]

冯国奇,李吉君,刘洁文,等, 2019. 泌阳凹陷页岩油富集及可动性探讨. 石油与天然气地质, 40(6): 1236-1246.

[130]

付茜,刘启东,刘世丽,等, 2020. 苏北盆地高邮凹陷古近系阜宁组二段页岩油成藏条件分析. 石油实验地质, 42(4): 625-631.

[131]

盖平原, 2011. 胜利油田稠油黏度与其组分性质的关系研究. 油田化学, 28(1): 54-57.

[132]

高岗,刘显阳,王银会,等, 2013. 鄂尔多斯盆地陇东地区长7段页岩油特征与资源潜力. 地学前缘, 20(2): 140-146.

[133]

韩克猷,王毓俊,查全衡, 2015. 川中侏罗系勘探潜力及勘探目标再认识. 石油科技论坛, 34(6): 51-57.

[134]

何晋译,蔡进功,雷天柱,等, 2019. 东营凹陷古近系泥页岩中可溶有机质特征与页岩油“甜点”预测. 油气地质与采收率, 26(1): 174-182.

[135]

何涛华,李文浩,谭昭昭,等, 2019. 南襄盆地泌阳凹陷核桃园组页岩油富集机制. 石油与天然气地质, 40(6): 1259-1269.

[136]

何玉荣,宋志超,张燕明,等, 2021. 机器学习在水力压裂作业中的应用综述. 中国石油大学学报(自然科学版), 45(6): 127-135.

[137]

姜在兴,张文昭,梁超,等, 2014. 页岩油储层基本特征及评价要素. 石油学报, 35(1): 184-196.

[138]

金涛,张文济,白蓉,等, 2022. 四川盆地东部地区下侏罗统自流井组页岩储层特征. 天然气勘探与开发, 45(1): 87-97.

[139]

金旭,李国欣,孟思炜,等, 2021. 陆相页岩油可动用性微观综合评价. 石油勘探与开发, 48(1): 222-232.

[140]

金之钧,白振瑞,高波,等, 2019. 中国迎来页岩油气革命了吗? 石油与天然气地质, 40(3): 451-458.

[141]

匡立春,侯连华,杨智,等, 2021. 陆相页岩油储层评价关键参数及方法. 石油学报, 42(1): 1-14.

[142]

黎茂稳,马晓潇,蒋启贵,等, 2019. 北美海相页岩油形成条件、富集特征与启示. 油气地质与采收率, 26(1): 13-28.

[143]

黎茂稳,马晓潇,金之钧,等, 2022. 中国海、陆相页岩层系岩相组合多样性与非常规油气勘探意义. 石油与天然气地质, 43(1): 1-25.

[144]

李辉,姜振学,邓勇,等, 2022. 南海涠西南凹陷页岩油形成条件及富集特征. 中国矿业大学学报, 51(5): 1-17.

[145]

李吉君,史颖琳,章新文,等, 2014. 页岩油富集可采主控因素分析:以泌阳凹陷为例. 地球科学(中国地质大学学报), 39(7): 848-857.

[146]

李士超,张金友,公繁浩,等, 2017. 松辽盆地北部上白垩统青山口组泥岩特征及页岩油有利区优选. 地质通报, 36(4): 654-663.

[147]

李小龙,孙伟, 2022. 页岩油储层“七性”关系评价研究——以苏北盆地溱潼凹陷阜宁组二段为例. 非常规油气: 1-9.

[148]

李阳,赵清民,吕琦,等, 2022. 中国陆相页岩油开发评价技术与实践. 石油勘探与开发, 49(5): 955-964.

[149]

梁世君,黄志龙,柳波,等, 2012. 马朗凹陷芦草沟组页岩油形成机理与富集条件. 石油学报, 33(4): 588-594.

[150]

刘朝全,姜学峰,吴谋远, 2021. 2021国内外油气行业发展报告. 北京: 石油工业出版社, 3.

[151]

刘海波,郭绪强, 2008. 原油组分的性质与结构对其粘度的影响. 新疆石油地质, (3): 347-349.

[152]

刘惠民,于炳松,谢忠怀,等, 2018. 陆相湖盆富有机质页岩微相特征及对页岩油富集的指示意义——以渤海湾盆地济阳坳陷为例. 石油学报, 39(12): 1328-1343.

[153]

刘敬寿,丁文龙,肖子亢,等, 2019. 储层裂缝综合表征与预测研究进展. 地球物理学进展, 34(6): 2283-2300.

[154]

刘毅, 2018. 渤海湾盆地济阳坳陷沙河街组页岩油储层特征研究(博士毕业论文). 成都:成都理工大学.

[155]

柳波,吕延防,冉清昌,等, 2014. 松辽盆地北部青山口组页岩油形成地质条件及勘探潜力. 石油与天然气地质, 35(2): 280-285.

[156]

柳波,吕延防,赵荣,等, 2012. 三塘湖盆地马朗凹陷芦草沟组泥页岩系统地层超压与页岩油富集机理. 石油勘探与开发, 39(6): 699-705.

[157]

龙海岑,李绍鹏, 2022. 泥页岩层系非均质性及其控制因素研究——以苏北盆地阜二段为例. 非常规油气, 9(4): 78-90.

[158]

马永生,蔡勋育,赵培荣,等, 2022. 中国陆相页岩油地质特征与勘探实践. 地质学报, 96(1): 155-171.

[159]

马永生,冯建辉,牟泽辉,等, 2012. 中国石化非常规油气资源潜力及勘探进展. 中国工程科学, 14(6): 22-30.

[160]

宁方兴, 2015. 济阳坳陷页岩油富集主控因素. 石油学报, 36(8): 905-914.

[161]

宁方兴,王学军,郝雪峰,等, 2015. 济阳坳陷页岩油甜点评价方法研究. 科学技术与工程, 15(35): 11-16.

[162]

蒲春生,郑恒,杨兆平,等, 2020. 水平井分段体积压裂复杂裂缝形成机制研究现状与发展趋势. 石油学报, 41(12): 1734-1743.

[163]

石林,张鲲鹏,慕立俊, 2020. 页岩油储层压裂改造技术问题的讨论. 石油科学通报, 5(4): 496-511.

[164]

宋国奇,张林晔,卢双舫,等, 2013. 页岩油资源评价技术方法及其应用. 地学前缘, 20(4): 221-228.

[165]

苏铁军,郑延成, 2007. 稠油族组成与黏度关联研究. 长江大学学报, 1: 60-62.

[166]

孙莎莎,董大忠,李育聪,等, 2021. 四川盆地侏罗系自流井组大安寨段陆相页岩油气地质特征及成藏控制因素. 石油与天然气地质, 42(1): 124-135.

[167]

王广才,王焰新,刘菲,等, 2022. 基于文献计量学分析水文地球化学研究进展及趋势. 地学前缘, 29(3): 25-36.

[168]

王敏,陈祥,严永新,等, 2013. 南襄盆地泌阳凹陷陆相页岩油地质特征与评价. 古地理学报, 15(5): 663-671.

[169]

王淑玲,吴西顺,张炜,等, 2016. 全球页岩油气勘探开发进展及发展趋势. 中国矿业, 25(2): 7-11.

[170]

王香增,张丽霞,雷裕红,等, 2018. 低熟湖相页岩内运移固体有机质和有机质孔特征——以鄂尔多斯盆地东南部延长组长7油层组页岩为例. 石油学报, 39(2): 141-151.

[171]

王勇,刘惠民,宋国奇,等, 2017. 济阳坳陷页岩油富集要素与富集模式研究. 高校地质学报, 23(2): 268-276.

[172]

王勇,宋国奇,刘惠民,等, 2015. 济阳坳陷页岩油富集主控因素. 油气地质与采收率, 22(4): 20-25.

[173]

武晓玲,高波,叶欣,等, 2013. 中国东部断陷盆地页岩油成藏条件与勘探潜力. 石油与天然气地质, 34(4): 455-462.

[174]

严德天,陆江,魏小松,等, 2019. 断陷湖盆富有机质页岩形成环境及主控机制浅析——以涠西南凹陷流沙港组二段为例. 中国海上油气, 31(5): 21-29.

[175]

杨华,李士祥,刘显阳, 2013. 鄂尔多斯盆地致密油、页岩油特征及资源潜力. 石油学报, 34(1): 1-11.

[176]

杨雷,金之钧, 2019. 全球页岩油发展及展望. 中国石油勘探, 24(5): 553-559.

[177]

杨志会,赵海波,黄勇,等, 2022. 地震信息约束的三维建模技术及其在松辽盆地古龙页岩油地质工程一体化中的应用. 大庆石油地质与开发, 41(3): 103-111.

[178]

杨智,侯连华,陶士振,等, 2015. 致密油与页岩油形成条件与“甜点区”评价. 石油勘探与开发, 42(5): 555-565.

[179]

姚红生,昝灵,高玉巧,等, 2021. 苏北盆地溱潼凹陷古近系阜宁组二段页岩油富集高产主控因素与勘探重大突破. 石油实验地质, 43(5): 776-783.

[180]

于学亮,胥云,翁定为,等, 2020. 页岩油藏“密切割”体积改造产能影响因素分析. 西南石油大学学报(自然科学版), 42(3): 132-143.

[181]

余志远,章新文,谭静娟,等, 2019. 泌阳凹陷页岩油赋存特征及可动性研究. 石油地质与工程, 33(1): 42-46.

[182]

昝灵,骆卫峰,印燕铃,等, 2021. 苏北盆地溱潼凹陷古近系阜宁组二段页岩油形成条件及有利区评价. 石油实验地质, 43(2): 233-241.

[183]

曾联波, 吕文雅, 徐翔,等,2022a. 典型致密砂岩与页岩层理缝的发育特征、形成机理及油气意义. 石油学报, 43(2):180-191.

[184]

曾联波,马诗杰,田鹤,等, 2022b. 富有机质页岩天然裂缝研究进展. 地球科学: 1-15.

[185]

张斌,毛治国,张忠义,等, 2021. 鄂尔多斯盆地三叠系长7段黑色页岩形成环境及其对页岩油富集段的控制作用. 石油勘探与开发, 48(6): 1127-1136.

[186]

张东晓,杨婷云, 2015. 美国页岩气水力压裂开发对环境的影响. 石油勘探与开发, 42(6): 801-807.

[187]

张金川,林腊梅,李玉喜,等, 2012. 页岩油分类与评价. 地学前缘, 19(5): 322-331.

[188]

张鹏飞,卢双舫,李文浩,等, 2016. 江汉盆地新沟嘴组页岩油储层物性下限. 石油与天然气地质, 37(1): 93-100.

[189]

张顺,刘惠民,刘雅利,等, 2021. 渤海湾盆地济阳坳陷页岩油地质甜点类型划分. 地质论评, 67(S1): 237-238.

[190]

赵文智,胡素云,侯连华,等, 2020. 中国陆相页岩油类型、资源潜力及与致密油的边界. 石油勘探与开发, 47(1): 1-10.

[191]

赵贤正,周立宏,蒲秀刚,等, 2018. 陆相湖盆页岩层系基本地质特征与页岩油勘探突破——以渤海湾盆地沧东凹陷古近系孔店组二段一亚段为例. 石油勘探与开发, 45(3): 361-372.

[192]

支东明,宋永,何文军,等, 2019a. 准噶尔盆地中—下二叠统页岩油地质特征、资源潜力及勘探方向. 新疆石油地质, 40(4): 389-401.

[193]

支东明,唐勇,郑孟林,等, 2019b. 准噶尔盆地玛湖凹陷风城组页岩油藏地质特征与成藏控制因素. 中国石油勘探, 24(5): 615-623.

[194]

周济民,张海晨,王沫然, 2021. 基于物理经验模型约束的机器学习方法在页岩油产量预测中的应用. 应用数学和力学, 42(9): 881-890.

[195]

周立宏,陈长伟,韩国猛,等, 2019. 渤海湾盆地歧口凹陷沙一下亚段地质特征与页岩油勘探潜力. 地球科学, 44(8): 2736-2750.

[196]

周立宏,蒲秀刚,肖敦清,等, 2018. 渤海湾盆地沧东凹陷孔二段页岩油形成条件及富集主控因素. 天然气地球科学, 29(9): 1323-1332.

[197]

朱德燕,王学军,郝雪峰,等, 2016. 东营凹陷泥页岩层序地层划分. 油气地质与采收率, 23(2): 52-56.

[198]

邹才能,翟光明,张光亚,等, 2015a. 全球常规-非常规油气形成分布、资源潜力及趋势预测. 石油勘探与开发, 42(1): 13-25.

[199]

邹才能,马锋,潘松圻,等, 2022a. 全球页岩油形成分布潜力及中国陆相页岩油理论技术进展. 地学前缘: 1-16.

[200]

邹才能,杨智,崔景伟,等, 2013a. 页岩油形成机制、地质特征及发展对策. 石油勘探与开发, 40(1): 14-26.

[201]

邹才能,杨智,董大忠,等, 2022b. 非常规源岩层系油气形成分布与前景展望. 地球科学, 47(5): 1517-1533.

[202]

邹才能,杨智,陶士振,等, 2012a. 纳米油气与源储共生型油气聚集. 石油勘探与开发, 39(1): 13-26.

[203]

邹才能,张国生,杨智,等, 2013b. 非常规油气概念、特征、潜力及技术——兼论非常规油气地质学. 石油勘探与开发, 40(4): 385-399.

[204]

邹才能,朱如凯,白斌,等, 2015b. 致密油与页岩油内涵、特征、潜力及挑战. 矿物岩石地球化学通报, 34(1): 3-17.

[205]

邹才能,朱如凯,吴松涛,等, 2012b. 常规与非常规油气聚集类型、特征、机理及展望——以中国致密油和致密气为例. 石油学报, 33(2): 173-187.

基金资助

湖北省自然科学基金创新群体项目(2021CFA031)

AI Summary AI Mindmap
PDF (8332KB)

392

访问

0

被引

详细

导航
相关文章

AI思维导图

/