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Influence factors and conduction mechanism of mature lacustrine shales: a case study of the first member of Qingshankou Formation in Changling Sag, South Songliao Basin

  • Wei DANG , 1 ,
  • DianShi XIAO , 2, * ,
  • ShiWen Han 3 ,
  • Liang YANG 1 ,
  • Zhuo LI 2 ,
  • LeHua ZHENG 2 ,
  • Rui WANG 2
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  • 1 Exploration and Development Research Institute of Jilin Oilfield, Songyuan 138000, China
  • 2 School of Earth Science and Technology, China University of Petroleum (East China), Qingdao 266580, China
  • 3 No. 2 Geo-Logging Company of Daqing Drilling Engineering Company, Songyuan 138000, China

Received date: 2023-12-25

  Online published: 2024-12-19

Copyright

Copyright ©2024 Progress in Geophysics. All rights reserved.

Abstract

High clay content, a variety of pore forms, and complicated fluid occurrence are characteristics of shale reservoirs. Shale's electrical conductivity is influenced by many factors, including its mineral composition, fluid type, physical properties and maturity, which leads to the weak correlation between electrical conductivity and oil content and physical properties. Therefore, it is critical to understand the conductive mechanism and influence factors of the electrical properties of shale. In this paper, the mature lacustrine shale of the first member of the Qingshankou Formation (Qing1 Member) in Changling Sag, south Songliao Basin is taken as an example. Using sealed coring, Two-dimensional nuclear magnetic resonance, field emission scanning electron microscopy, TOC, and X-ray Diffraction tests, combined with electrical logging curves, the impacts of fluid occurrence, physical properties and mineral composition on the electrical properties of the shale were analyzed, and then the conduction mechanism of mature lacustrine shale was addressed. The findings indicate that physical properties have a minor impact on shale electrical properties, while mineral composition (carbonates minerals, clay minerals) and fluid type have a significant impact. Silty-laminated shales (including shell limestone) are affected electrically by carbonate minerals, clay minerals, oil saturation, free water and bound water, argillaceous-laminated felsic shales and argillaceous-laminated clay shales are affected electrically by bound water, adsorbed oil, and clay minerals. For mature lacustrine shale, there are three different types of conductivity mechanisms: clay additional conduction (type Ⅰ), organic matter and clay complex conduction (type Ⅱ), and porous conduction of brittle mineral matrix (type Ⅲ). Silty-laminated shales mainly develop conductivity mechanisms of porous conduction of brittle mineral matrix and clay additional conduction, whereas argillaceous-laminated felsic shales and argillaceous-laminated clay shale primarily develop conductivity mechanisms of clay additional conduction and clay additional conduction. The findings provide guidance for enriching the electrical conductivity mechanism of shale and raising the accuracy of shale saturation interpretation.

Cite this article

Wei DANG , DianShi XIAO , ShiWen Han , Liang YANG , Zhuo LI , LeHua ZHENG , Rui WANG . Influence factors and conduction mechanism of mature lacustrine shales: a case study of the first member of Qingshankou Formation in Changling Sag, South Songliao Basin[J]. Progress in Geophysics, 2024 , 39(5) : 1935 -1950 . DOI: 10.6038/pg2024HH0464

0 引言

页岩油是指以游离烃和吸附烃赋存在富有机质页岩及其薄夹层(粉砂岩、白云岩、石灰岩或凝灰岩)中的液态烃类(姜在兴等,2014宁方兴,2015),需要借助压裂技术才能被有效采出(Zhao et al., 2020),页岩储层表现为特低孔、特低渗特征(Jarvie,2012Dong et al., 2023),储集空间为纳米级孔隙和层理缝(Jarvie,2012邹才能等,2013Sang et al., 2018),只有在物性、含油性、脆性均好的甜点层段实施水平井钻探,才有望实现经济开采,因此页岩含油性评价是页岩油甜点评价的关键内容,含油饱和度是含油性评价及储量计算的基本参数.电阻率测井常用于饱和度解释(Wang et al., 2022),然而,与常规储层相比,页岩具有黏土含量高、纹层及微孔发育、孔隙类型多样、流体赋存复杂等特点(Zhu et al., 2021Liu et al., 2022闫伟林等,2022),传统的泥质砂岩饱和度模型并不适用于页岩储层(Wang et al., 2022闫伟林等,2022),厘清页岩的电性响应因素,对于明确页岩导电机理、建立饱和度测井解释模型非常必要.
前人研究表明,页岩导电性主要受矿物组分、流体类型、成熟度、孔隙结构、物性等多种因素耦合控制(Tang et al., 2016陈进宇和杨晓松,2017赵军等,2017王京悉,2019Lin et al., 2019Jia et al., 2022Zhu et al., 2021).Zhang等(2017)孙建孟等(2018)针对页岩气储层低阻现象开展分析,认为页岩储层低阻主要受高黏土含量、过高成熟度、高黄铁矿含量、高地层水矿化度、微裂缝发育、储层物性差等多种因素影响;Zhu等(2021)针对我国南方海相页岩导电规律开展研究,认为碳酸盐矿物、未碳化有机质使岩石电阻率增加,黏土矿物、黄铁矿、碳化有机质使岩石电阻率降低,孔隙类型对岩石电阻率的影响不是单一的,亲油性的有机孔隙使页岩电阻率增大,黏土孔隙由于其亲水性使页岩电阻率降低,碎屑岩孔隙的增加主要是由于生物成因石英含量的增多,随着生物石英增加,有机质含量(TOC)和有机孔隙也随之增加,孔隙中油气含量的增大导致页岩电阻率增大.贾建亮等(2015)针对未成熟湖相页岩导电性展开研究,认为有机质与无机矿物的组合和分布控制了孔隙空间与孔隙结构的发育,在未成熟湖相页岩中,TOC<4.5%时,黏土附加导电性是岩石电阻率降低的主要原因;TOC>4.5%时,有机质填充孔隙空间,孔隙中非导电流体及固体有机物的增加使岩石电阻率增大.由此可见,页岩导电性受沉积环境(海相、陆相)、成熟度、矿物组成、流体分布、孔隙结构、储层物性等多种因素耦合影响,影响因素复杂且导电机理多样,导致电性曲线对含油性响应较弱(李宁等,2020),制约了电性曲线在泥页岩含油气性、TOC预测等方面的应用.目前针对成熟湖相页岩电性影响因素及导电机理方面研究较为缺乏.
研究泥页岩导电特征的实验方法主要包括常规岩电(去水法)、数字岩心模拟和直接对比法.常规岩电是将岩样洗油烘干后饱和水,测量水离心或挥发过程中电阻率变化,分析水赋存对电性影响(董旭,2017张波等,2022),该方法在洗油、饱和水过程中会破坏页岩孔隙结构,且无法还原页岩原始流体状态(赵小青等,2023);数字岩心模拟是基于CT、扫描电镜(SEM)等建立数字岩心,基于玻尔兹曼电性模拟、孔隙网络模拟、有限元法等模型分析孔隙网络、流体等对电性影响(简世凯等,2020刘宁等,2020Ruspini et al., 2021李潮流等,2022张乃毓,2023),该方法也存在无法恢复页岩原始流体赋存状态的问题;直接对比法是对新鲜页岩样品开展电阻率测试,直接建立电性与矿物、TOC、孔隙结构、含油性等关系(黄涛,2016翟刚毅等,2021),但多采用常规放置样品,其内流体也会存在挥发,影响含油性测试精度(Wang et al., 2022).
核磁共振技术作为一种新的含油性表征技术,具有无损、快速、对样品规格无要求等优点(Song and Kausik, 2019王民等,2022),其中二维核磁共振技术对于表征多类型氢组分(干酪根、吸附油、游离油、结合水、游离水等)的页岩储层的流体信息具有良好效果(Li et al., 2018白龙辉等,2021).但利用二维核磁对页岩进行流体识别的过程中仍然存在挑战,由于区域地质背景、页岩类型、成熟度、孔隙类型、流体赋存状态等差异,导致所建立的流体识别图版中各流体类型的位置及分布范围有所差异,图版具有区域性(Li et al., 2018).且目前多采用常规放置样品,处理与测试过程中流体的挥发导致样品与原始地层流体信息有所差异(覃莹瑶等,2022),因此,为尽可能的减少页岩样品中流体挥发并反应原始地层流体信息,本文联合保压密闭样品和二维核磁技术,对长岭凹陷青一段高成熟湖相页岩储层的流体信息进行表征.
为此,本文以松辽盆地南部长岭凹陷上白垩统青山口组一段为对象,通过保压密闭样品和二维核磁手段揭示页岩原始流体性质,再基于扫描电镜(FE-SEM)、总有机碳含量(TOC)测试、X衍射全岩分析(XRD)、薄片观察等实验,揭示矿物组分、储层物性、流体分布等因素对页岩电性的影响,进而探讨成熟湖相页岩导电机理,为该类型页岩含油性评价提供理论基础.

1 样品与方法

1.1 实验样品

长岭凹陷位于松辽盆地中央坳陷区南部,是松辽盆地南部重要生烃凹陷之一(张大千,2018柯钦等,2022马妍等,2023).上白垩统青山口组沉积期间发生大规模海侵,形成半深湖—深湖相泥页岩沉积(张金川等,2012柳波等,2018马妍等,2023),青一段泥页岩厚度约为50~120 m,以富有机质暗色页岩为主,夹少量粉砂岩、介壳灰岩薄层(陈杏霞和曲前中,2012张鹏辉等,2012王宏伟,2015张大千,2018).青一段泥页岩干酪根类型主要为Ⅰ-Ⅱ1型,有机质丰度(TOC)大于1%, 属于好烃源岩范畴;长岭凹陷青一段成熟度位于0.9% ~1.3%, 属于中高成熟阶段,利于页岩油富集,具备较好的页岩油开发潜质(李明等,2009张鹏辉等,2012).
本文以长岭凹陷青山口组一段中高熟湖相页岩为研究对象,从A井中优选42块保压密闭岩样,开展流体分布、储层物性、地化特征、岩石学特征(岩相特征、矿物组分)等相关测试,流体分布及物性实验主要基于密闭样品和二维核磁共振测试;地化实验主要为TOC测试;岩石学特征实验包括FE-SEM、薄片分析、XRD全岩分析;测井电性响应特征是对岩心进行归位后从实测电阻率曲线中获得.

1.2 实验方法

页岩岩心采用保压密闭取心技术获取,对其开展二维核磁共振测试,获取样品中流体信息,得到有效孔隙度;然后进行FE-SEM、TOC测试、XRD和薄片观察等测试,获取页岩的孔隙类型、有机质和无机矿物组成、岩相等信息(图 1).上述实验均在中国石油大学(华东)深层油气全国重点实验室完成,其中二维核磁共振实验步骤如下:
图1 长岭凹陷A井青一段页岩样品测试结果垂向分布

Figure 1 The vertical distribution of experimental results of Qing1 Member shale samples from well A in Changling Sag

应用MesoMR23-060H-I型核磁共振分析仪对42块保压密闭页岩岩样进行核磁共振测试,设置核磁共振分析仪频率为21.36 MHz,回波间隔和等待时间分别为0.06 ms、1500 ms,回波个数为3000.将地下取出的原始样品放置到液氮罐中保存、运输,在实验室中,将新鲜冷冻样品取出后,快速制成质量大于10 g的小块,按照2 min间隔进行一维核磁共振测试,当相邻两次测试结果差异不大时,采用IR-CPMG序列测得二维核磁共振信号,反演得到T1-T2谱,单个样品的测试时长大约20 min.
为建立该区页岩油的流体识别图版,用二氯甲烷及甲苯按照3∶1比例配置后对页岩岩心进行洗油10~15天,洗油后样品开展热解实验,确保样品残留油大部分洗出.样品洗油后进行烘干,测量干样的二维核磁共振信号,得到干酪根及结合水在二维核磁共振图谱中位置;然后,将岩样进行饱和水,测量其核磁信号,获得游离水位置,再将岩样烘干后饱和油,测量核磁共振信号,
得到游离油与吸附油位置,同时测量饱和油岩样的热解S2-1(吸附油)参数,准确厘定吸附油与游离油的界线.利用上述步骤,可得到长岭凹陷青一段页岩储层不同类型流体(游离油、吸附油、游离水、结合水)及干酪根的二维核磁共振流体识别图版(图 2a).其中干酪根:T2<0.2 ms,T1>10 ms;吸附油:0.2 ms<T2<2 ms,T1>10 ms;游离油:T2>2 ms,T1/T2>1;束缚水/结合水:T2<0.2 ms,T1<10 ms,T1/T2>10;游离水:0.2 ms<T2<2 ms,T1<10 ms,1<T1/T2<10.
图2 长岭凹陷青一段页岩二维核磁共振流体识别图版及信号-质量间转换关系

(a)二维核磁共振流体识别图版;(b)二维核磁共振信号-质量间转换关系.

Fig 2 2D-NMR fluid identification pattern and signal-mass conversion relationship of Qing1 Member shale in Changling Sag

(a)2D-NMR fluid identification pattern; (b)2D-NMR signal-mass conversion relationship.

利用不同质量的地层水(密度为1 g/cm3)和原油(来自页岩油产出井,密度为0.85 g/cm3),分别建立不同类型流体质量与核磁共振信号量间关系(图 2b),将核磁共振信号量转化为流体质量,计算得到流体体积;再将流体体积和碎块体积相比,计算得到页岩样品的有效孔隙度、有效含油饱和度等信息(图 1).
所建立的长岭凹陷青一段中高成熟页岩储层二维核磁共振流体识别图版与古龙凹陷青山口组高成熟页岩相比较(图 3),差异性主要体现在横向弛豫时间(T2)界线上,前者页岩游离水T2值大于0.2 ms,游离油T2值大于2 ms(图 3a),而古龙凹陷青山口组页岩游离水T2值大于0.1 ms,游离油T2值大于1.6 ms(图 3b),成熟度差异是主要原因.
图3 松辽盆地长岭和古龙凹陷青一段页岩二维核磁共振流体识别图版对比

(a)长岭凹陷青一段页岩储层二维核磁共振流体识别图版;(b)古龙凹陷青山口组页岩二维核磁共振流体识别图版(据白龙辉等,2021石玉江等,2023修改).

Fig 3 Comparisons of 2D-NMR fluid identification pattern of Qing1 Member shale in Changling and Gulong Sag of Songliao Basin

(a)2D-NMR fluid identification pattern of Qing1 Member shale in Changling Sag; (b)2D-NMR fluid identification pattern of Qingshankou Formation shale in Gulong Sag(Modified by Bai et al., 2021; Shi et al., 2023).

2 岩相类型、物性及含油性特征

2.1 岩相类型划分

青一段页岩矿物类型以长英质矿物和黏土矿物为主(均值分别为41.21%和41.18%),其次为碳酸盐矿物(均值为18.08%),黄铁矿少量发育,普遍发育纹层,偶见微裂缝.本文以矿物成分及粒度为主要依据,结合薄片鉴定结果,将长岭凹陷青一段页岩岩相划分为介壳灰岩、粉砂纹层页岩、泥纹层长英质页岩、泥纹层黏土质页岩四大类(图 4).其中,介壳灰岩以碳酸盐矿物为主(均值高达80%),介形虫或介屑颗粒含量大于50%, TOC较低,均值为0.65%;粉砂纹层页岩以长英质矿物为主,均值为51.05%, 该类岩相中粉砂纹层(纹层中大于4 μm颗粒含量超50%)占比在10% ~50%之间,TOC均值为1.34%;泥纹层长英质页岩的长英质矿物含量大于黏土矿物(长英质均值为44.52%, 黏土矿物均值为42.02%),粉砂纹层占比小于10%;泥纹层黏土质页岩的长英质矿物含量小于黏土矿物(长英质矿物均值为41.40%, 黏土矿物均值为54.26%),粉砂纹层占比也多小于10%.
图4 长岭凹陷A井青一段页岩岩相薄片特征

(a)粉砂纹层页岩(深度:2392.38 m);(b)介壳灰岩(深度:2370.18 m);(c)泥纹层长英质页岩(深度:2383.90 m);(d)泥纹层黏土质页岩(深度:2398.90 m).

Fig 4 Thin section characteristics of lithofacies of Qing1 Member shale in well A of the Changling Sag

(a)Silty-laminated shales(depth: 2392.38 m); (b)Shell limestone(depth: 2370.18 m); (c)Argillaceous-laminated felsic shales (depth: 2383.90 m); (d)Argillaceous-laminated clay shales(depth: 2398.90 m).

2.2 储集空间类型

基于扫描电镜观察,青一段页岩主要发育5类孔隙,包括粒间孔、粒间溶蚀孔、粒内溶蚀孔、晶间孔和有机质孔,其中晶间孔和溶蚀孔较为发育,有机孔隙少量发育,局部发育微裂缝.粒间孔主要发育在脆性矿物颗粒之间或者矿物与有机质的交界处,孔径相对较大,多呈三角形或不规则多边形及狭缝型等(图 5a),连通性较好,是游离油富集的主要场所(秦德超等,2023).长石或方解石等易溶矿物边缘发生溶蚀而形成粒间溶蚀孔,其孔径通常大于100 nm(图 5b),而粒内溶蚀孔主要发育在长石、方解石等矿物颗粒内部(图 5c),呈椭圆形、三角形和狭长形,孔径多集中在几十个纳米,溶蚀孔的存在对页岩储层物性具有明显的改善作用(许璟等,2013).晶间孔是黏土矿物、黄铁矿、方解石、白云石等矿物晶体间形成的孔隙,在该区类型多为黏土晶间孔(图 5d)并伴随少量的黄铁矿晶间孔(图 5e),晶间孔孔径相对较小且连通性较差,通常被有机质充填(图 5f)(张玥等,2023).同时可见发育于有机质颗粒间或内部的有机质孔,主要是随着液态或气态烃类物质的生成而形成,是页岩储层油气聚集的重要场所(张盼盼等,2021秦德超等,2023),研究区有机质孔多呈蜂窝状,孔径位于120~500 nm之间(图 5g).另外,可见局部发育的微裂缝(图 5h),类型多为层理缝或构造缝(图 4c),是连通各类孔隙空间的重要通道,能够显著提高页岩渗流能力(雷海艳等,2022).
图5 长岭凹陷A井青一段页岩主要孔隙类型镜下特征

(a)粒间孔,粉砂纹层页岩(深度:2369.96 m);(b)粒间溶蚀孔,粉砂纹层页岩(深度:2382.25 m);(c)粒内溶蚀孔,泥纹层长英质页岩(深度:2378.90 m);(d)黏土晶间孔,泥纹层长英质页岩(深度:2378.90 m);(e)黄铁矿晶间孔,泥纹层长英质页岩(深度:2382.25 m);(f)黏土晶间孔被有机质填充,泥纹层黏土质页岩(深度:2404.16 m);(g)有机质孔,粉砂纹层页岩(深度:2369.96 m);(h)微裂缝,含介壳粉砂纹层页岩(深度:2409.50 m);(i)有机质与黏土复合体,泥纹层黏土质页岩(深度:2404.16 m).

Fig 5 Microscopic characteristics of main pore types of Qing1 Member shale in well A of Changling Sag

(a)Intergranular pore, silty-laminated shales(depth: 2369.96 m); (b)Intergranular dissolution pore, silty-laminated shales(depth: 2382.25 m); (c)Intragranular dissolution pore, argillaceous-laminated felsic shales(depth: 2378.90 m); (d)Clay intercrystalline pore, argillaceous-laminated felsic shales(depth: 2378.90 m); (e)Pyrite intercrystalline pore, argillaceous-laminated felsic shales(depth: 2382.25 m); (f)Clay intergranular pores are filled with organic matter, argillaceous-laminated clay shales(depth: 2404.16 m); (g)Organic pore, silty-laminated shales(depth: 2369.96 m); (h)Microfracture, Silt-laminated shale with shell(depth: 2409.50 m); (i)Organic matter and clay complex, argillaceous-laminated clay shales(depth: 2404.16 m).

2.3 物性及含油性特征

对42块页岩岩样进行二维核磁实验,得到有效孔隙度、含油饱和度、游离油含量、吸附油含量、游离水含量、结合水含量等信息(表 1),其中,有效孔隙度分布范围为1.19% ~10.23%, 均值为7.09%;含油饱和度分布范围为30.79% ~75.90%, 均值为48.71%;游离油分布范围为1.62% ~13.08%, 均值为7.81%;吸附油分布范围为1.05% ~10.49%, 均值为4.51%;游离水分布范围为2.11% ~30.47%, 均值为17.21%;结合水分布范围为4.32% ~54.32%, 均值为27.98%.介壳灰岩及粉砂纹层页岩的有效孔隙度明显低于其他岩相;四类岩相的含油饱和度相差不大,但介壳灰岩、粉砂纹层页岩及泥纹层长英质页岩岩相的游离油占比(与总油比值)较高,泥纹层黏土质页岩的吸附油占比较高;介壳灰岩与粉砂纹层页岩岩相的游离水占比(与总水比值)较高,泥纹层长英质页岩与泥纹层黏土质页岩岩相的结合水占比较高.由此可见,岩相对长岭凹陷青一段页岩储层的物性及含油性具有一定的控制作用.矿物组分影响页岩的孔隙空间类型及发育特征,也控制着油水微观赋存特征,高脆性矿物含量导致介壳灰岩及粉砂纹层页岩的中大孔较为发育(图 5ab),导致游离油及游离水相对富集(表 1),而黏土对有机质有吸附作用(Zhao et al., 2023),有机质表面多被吸附油占据,导致黏土矿物含量较高的泥纹层黏土质页岩吸附油及结合水富集(表 1).
表1 长岭凹陷A井青一段页岩物性及含油性特征分布

Table 1 Physical properties and oil bearing characteristics distribution of Qing1 Member shale in well A of Changling Sag

物性及含油性参数 总体 介壳灰岩 粉砂纹层页岩 泥纹层长英质页岩 泥纹层黏土质页岩
有效孔隙度/% 分布范围 1.19~10.23 1.19~8.49 4.15~7.16 4.05~9.76 5.26~10.23
均值 7.09 5.51 5.83 7.47 7.56
含油饱和度/% 分布范围 30.79~75.90 31.10~67.55 35.72~55.36 37.53~75.90 30.79~71.79
均值 48.71 48.60 48.10 50.10 47.42
游离油含量/(mg/g) 分布范围 1.62~13.08 1.62~11.78 4.57~10.17 6.03~13.08 4.94~9.26
均值 7.81 6.64 6.90 9.36 6.79
吸附油含量/(mg/g) 分布范围 1.05~10.49 1.05~3.13 2.67~4.88 1.93~9.25 2.20~10.49
均值 4.51 2.01 3.76 4.36 5.69
游离油占比/% 分布范围 38.29~86.88 57.57~86.88 56.89~70.54 39.55~86.17 38.29~79.75
均值 63.61 71.56 64.52 68.37 55.75
游离水含量/(mg/g) 分布范围 2.11~30.47 2.11~26.07 9.54~17.49 6.53~28.97 9.04~30.47
均值 17.21 14.19 14.30 18.29 17.88
结合水含量/(mg/g) 分布范围 4.32~66.14 4.32~51.38 22.75~42.60 27.09~66.14 46.94~63.91
均值 46.70 22.72 31.24 48.00 57.45
游离水占比/% 分布范围 8.99~54.32 28.46~54.32 23.96~37.91 8.99~40.75 12.62~34.79
均值 27.98 40.88 31.67 27.46 23.43

3 页岩电性特征及影响因素

3.1 页岩电性响应特征

岩心归位是建立实验结果与电性曲线关系的纽带.本次选取取心收获率90%以上的岩心段作为关键层段,以测井深度为标准,利用岩心岩性变化,找到A井岩性发生明显变化的深度段(2405.52~2405.57 m、2405.99~2406.05 m),岩心观察为介壳灰岩及介壳灰岩与页岩互层(图 6bc),对应成像测井呈明亮及明暗相间的条纹(图 6a),其测井深度分别为2404.89~2404.94 m、2405.36~2405.42 m,确定岩心归位深度为-0.63 m,在岩心归位的基础上获取到与取样点对应的测井曲线(图 7ab).42块页岩样品的电阻率(RLLD)整体分布在4.00~24.18 Ω · m之间,声波时差(AC)分布在258.53~348.74 μs/m之间,泥纹层黏土质页岩具有极低RLLD和最高AC,粉砂纹层页岩(介壳灰岩)对应最高RLLD和最低AC,表明岩相对页岩电阻率有明显影响.由于介壳灰岩数量较少,且在测井电性、含油性特征上与粉砂纹层页岩相差不大,因此在后续分析时,将粉砂纹层页岩与介壳灰岩岩相进行了合并.
图6 长岭凹陷A井青一段页岩岩心深度归位

(a)成像测井图(A井,2403.00~2406.00 m);(b,c)取心介壳灰岩岩心照片(A井,深度段分别为2405.52~2405.57 m、2405.99~2406.05 m).

Figure 6 Shale core-depth homing process of Qing1 Member shale in well A of Changling Sag

(a)Imaging logging(well A, 2403.00~2406.00 m); (b, c)Core photograph of shell limestone(well A, The depth segments are 2405.52~2405.57 m、2405.99~2406.05 m).

图7 长岭凹陷A井青一段不同岩相RLLD、AC频率分布直方图

Fig 7 The frequency distribution histogram of RLLD and AC of different lithofacies for Qing1 Member shale in well A of Changling Sag

3.2 页岩电阻率影响因素分析

(1) 矿物组分
页岩的骨架矿物主要由碳酸盐(方解石、白云石等)、长英质(石英、长石等)、黏土矿物(伊利石、伊蒙混层、绿泥石等)、黄铁矿等构成(Rimstidt et al., 2017),前人研究表明,矿物对页岩导电性具有直接影响(华博广,2019),碳酸盐与长英质矿物作为不导电矿物会使岩石电阻率增大(齐宝权等,2007),黏土矿物由于其附加导电性而使岩石电阻率降低(Waxman and Thomas, 1974),黄铁矿呈连续分布时会增加岩石导电性(Zhu et al., 2021).通过XRD矿物含量与测井电性曲线对应,分岩相建立各类矿物组分与RLLD关系(图 8ad).碳酸盐和黏土矿物对长岭凹陷青一段页岩电性影响最大,长英质矿物与黄铁矿对其影响较弱,其中碳酸盐矿物对粉砂纹层页岩和介壳灰岩影响最明显,黏土矿物对所有岩性影响均较大,由此可见,矿物组分(碳酸盐矿物、黏土矿物)对页岩的电性起到重要控制.
图8 长岭凹陷A井青一段不同岩相矿物组分与RLLD关系图

Figure 8 Relationship between mineral components and RLLD of different lithofacies for Qing1 Member shale in well A of Changling Sag

(2) 物性及流体类型
水与油气共存于页岩储层纳米孔隙中(周龙政等,2022),页岩油主要以游离态和吸附态赋存(张晋言,2012),水则以游离水和结合水(含束缚水)的形式分布于页岩孔隙内,油水微观赋存特征会影响页岩导电性.基于二维核磁实验获取页岩样品中的各类流体信息,分岩相建立有效孔隙度、含油饱和度、游离油、吸附油、游离水、结合水与RLLD曲线关系(图 9).有效孔隙度与电阻率基本无相关性,仅粉砂纹层页岩(含介壳灰岩)电阻率与有效孔隙度表现出一定的负相关(图 9a),说明青一段页岩的导电性受有效孔隙度的影响较弱,这主要与页岩有机和无机孔隙并存、纳米级孔隙主导、孔隙连通性差等因素有关.粉砂纹层页岩(含介壳灰岩)的电阻率受含油饱和度、游离水含量、结合水含量影响较大(图 9b),受吸附油含量与游离油含量影响较小,整体上该类岩相的电阻率受含水量影响,而泥纹层长英质页岩和黏土质页岩的电阻率受吸附油含量、结合水含量影响较大,受含油饱和度、游离油含量和游离水含量影响较小.由此可知,结合水对不同岩相页岩电阻率均有影响,吸附油含量对泥纹层长英质页岩和黏土质页岩表现出较强的影响(导致电阻率增加),而游离水对粉砂纹层页岩(含介壳灰岩)的电阻率影响较大.
图9 长岭凹陷A井青一段不同岩相页岩流体类型与RLLD曲线关系图

Figure 9 The relationship between fluid types and RLLD curves of different lithofacies for Qing1 Member shale in well A of Changling Sag

4 高成熟阶段湖相页岩导电机理探讨

以上研究表明,长岭凹陷青一段成熟湖相页岩导电性受岩相、矿物组成、流体类型等因素的耦合控制,对于粉砂纹层页岩(含介壳灰岩)来说,碳酸盐、黏土矿物共同主导电阻率,导电性还受结合水和游离水含量影响;对于泥纹层长英质和黏土质页岩来说,黏土矿物是影响电阻率的主要因素,导电性还受结合水和吸附油控制.根据导电能力,可将湖相页岩划分出不导电组分和导电组分,前者主要包括碳酸盐矿物、长英质矿物、孔隙内烃类、孤立有机质等,后者主要包括黏土矿物、黄铁矿、地层水等,有机质单独存在时作为不导电成分,但与黏土结合形成复合体后认为是半导体(赵小青等,2023),因此,在应用电性曲线进行饱和度解释时,应考虑岩相的差异,建立黏土附加导电、脆性矿物孔隙地层水、黄铁矿、有机质和黏土复合体等多种成分的页岩导电岩石物理模型(图 10).从页岩物质组成对导电性影响角度出发,总结出研究区页岩中存在的三类主要导电机制:黏土附加导电(Ⅰ型)(孙建孟等,2018)、脆性矿物基质孔隙导电(Ⅱ型)(贾建亮等,2015田瀚等,2020)、有机质和黏土复合体导电(Ⅲ型)(贾建亮等,2015Kadkhodaie and Rezaee, 2016赵小青等,2023).
图10 青一段页岩导电岩石物理模型示意图

Fig 10 The shale conductivity petrophysical model of Qing1 Member

(1) 黏土附加导电(Ⅰ型)
黏土矿物粒度细,具有较大的比表面积(邱正松等,1999梁健伟和曾锐碧,2016),且黏土矿物表现出较强亲水性,孔隙表面会被结合水占据,因此随黏土含量增加,结合水含量快速增大(图 11).黏土矿物聚合体间发育大量黏土晶间孔(图 5d),但连通性较差,其主要依靠颗粒表面存在的离子双电子层导电,在外电场作用下双电子层发生阳离子交换作用而产生附加导电性,极大降低了泥页岩的电阻率(孙建孟等,2018韩学辉等,2019).黏土附加导电是湖相页岩最主要的导电机制之一,在该机制影响下,随黏土矿物含量增加,粉砂纹层页岩、泥纹层长英质页岩和黏土质页岩电阻率整体呈现降低趋势.
图11 长岭凹陷A井青一段不同岩相页岩黏土矿物与结合水含量间关系

Fig 11 Relationship between clay mineral and bound water content of different lithofacies for Qing1 Member shale in well A of Changling Sag

(2) 脆性矿物基质孔隙导电(Ⅱ型)
脆性矿物(碳酸盐、长英质)属于固体电解质,导电性差,具有较高的电阻率(齐宝权等,2007).脆性矿物本身导电性差,但它们会促进粒间孔、溶蚀孔及微裂缝的发育(图 5ach),形成连通的基质孔隙网络,其导电性主要依靠基质孔隙内地层水导电,表现出类砂岩储层导电特征.此类机制的导电性除受碳酸盐及长英质矿物含量影响外,还受有效孔隙度及流体性质(含油饱和度、游离油、游离水、结合水)控制(图 8ac图 9adf).脆性矿物越多,粒间孔及溶蚀孔越发育,游离油相对富集,游离水含量减小,含油饱和度增高(表 1),导致页岩电阻率增大.该类导电机制主要出现在粉砂纹层页岩或介壳灰岩中.
(3) 有机质和黏土复合体导电(Ⅲ型)
有机质是页岩重要的组成部分,除了沉积型有机质呈块状或条带状分布外,还有很多迁移有机质或沥青充填在黏土矿物层间缝或粒间孔中,形成有机质和黏土复合体(Mayer,1994Kennedy et al., 2002Chenu and Plante, 2006)(图 5i).湖相页岩中TOC与吸附油呈明显正相关,说明有机质表面及有机孔壁多被吸附油占据(图 12a),黏土矿物间被迁移有机质充填后(图 5f),有机质表面的吸附油将会影响复合体中黏土矿物的附加导电性.吸附油与吸附在黏土矿物表面的水分子发生竞争,引起孔隙流体离子导电和黏土附加导电性的变化(徐敏,2013).随TOC增多,吸附油含量增加,有机质和黏土复合体导电机制影响增大,页岩电阻率增高(图 12b),该类机制主要出现在中高有机质的泥纹层长英质页岩和黏土质页岩中.
图12 长岭凹陷A井青一段不同岩相页岩TOC与吸附油(a)、RLLD(b)关系图

Fig 12 Relationship of TOC with adsorbed oil (a) and RLLD (b) of different lithofacies for Qing1 Member shale in well A of Changling Sag

5 结论

本文以松辽盆地长岭凹陷青一段页岩为研究对象,基于保压密闭样品和二维核磁、FE-SEM、TOC测试、XRD、薄片观察等实验手段,结合测井资料对成熟湖相页岩的电性影响因素及导电机理开展研究,得出以下认识:
(1) 基于密闭取心样品和二维核磁共振实验可最大限度的还原原始地层不同类型流体含量,有助于分析岩石流体赋存对页岩电阻率的影响.
(2) 矿物(碳酸盐、黏土矿物)及流体性质对页岩电性具有较强影响,物性影响较弱;对于粉砂纹层页岩、介壳灰岩,电性主要受矿物组分(碳酸盐、黏土矿物)、流体性质(含油饱和度、游离水含量、结合水含量)、物性(有效孔隙度)影响,对于泥纹层长英质页岩或黏土质页岩,电性主要受矿物组分(黏土矿物)、流体性质(吸附油含量、结合水含量)影响.
(3) 湖相页岩至少存在三类导电机制:黏土附加导电(Ⅰ型)、脆性矿物基质孔隙导电(Ⅱ型)、有机质和黏土复合体导电(Ⅲ型).粉砂纹层页岩主要发育Ⅲ型和Ⅰ型导电,泥纹层长英质或黏土质页岩主要发育Ⅰ型和Ⅱ型导电.

感谢审稿专家提出的修改意见和编辑部的大力支持!

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