Article(id=1149768568977404896, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149768563956826506, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2406233, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1724169600000, receivedDateStr=2024-08-21, revisedDate=1742313600000, revisedDateStr=2025-03-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1752055788510, onlineDateStr=2025-07-09, pubDate=1749312000000, pubDateStr=2025-06-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752055788510, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752055788510, creator=13701087609, updateTime=1752055788510, updator=13701087609, issue=Issue{id=1149768563956826506, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='16', pageStart='6587', pageEnd='7021', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752055787314, creator=13701087609, updateTime=1768456850262, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218559607937618069, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149768563956826506, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218559607937618070, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149768563956826506, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=6628, endPage=6641, ext={EN=ArticleExt(id=1149768569178731489, articleId=1149768568977404896, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Oil-water Distribution and Control Factors of Chang 7 in Heshuinan Area of Ordos Basin, columnId=1156262729351549255, journalTitle=Science Technology and Engineering, columnName=Papers·Astronomy and Geosciences, runingTitle=null, highlight=null, articleAbstract=

The reservoir of Chang 7 in Heshuinan area of Ordos Basin has high salinity of formation water and strong heterogeneity of mud content, which leads to unclear understanding of oil-water distribution and main controlling factors. It seriously restricts the efficient development of the oilfield. In order to improve the efficiency and accuracy of the identification of oil-water layer and clarify the distribution law of oil and water, the intelligent random forest method was used to interpret the fluid properties on the basis of logging, oil test and production test data, and defined the distribution law of oil and water in Chang 7 in Heshuinan area. In addition, the controlling factors of oil and water distribution were analyzed from various angles by combining the experiments of constant rate mercury injection, CT (computerized tomography) and nuclear magnetic resonance. The results show that the accuracy of the fluid properties interpretation can reach 78.9% by using random forest method. In the vertical direction, the oil layer developed in Chang 71 is better than that in Chang 72, and the oil-water layer and water layer are mainly developed in Chang 72. In the plane direction, the eastern oil layer is thicker and distributed more continuously, and the southwest oil layer near the B60 well area has higher water content. The fluid properties inside the reservoir are controlled by the shale content, the pore structure and the viscosity of crude oil. The pore size and the connectivity of pore throat of the reservoir are affected by the content of mud. The pore structure of the reservoir and the viscosity of crude oil together control the fluid mobility, thus affecting the spatial distribution of oil and water in Heshuinan area.

, correspAuthors=Xi-xin WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xing-zhao CHEN, Xi-xin WANG, Shao-hua LI, You-an HE, Tian-jing HUANG, Ting XUE, Si-yu YU, Mao-zhou HAN), CN=ArticleExt(id=1149768588401226386, articleId=1149768568977404896, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=鄂尔多斯盆地合水南地区长7段油水分布规律及控制因素, columnId=1156262730077163858, journalTitle=科学技术与工程, columnName=论文·天文学、地球科学, runingTitle=null, highlight=null, articleAbstract=

鄂尔多斯盆地合水南地区长7段储层地层水矿化度高、泥质含量非均质性强,导致油水分布规律及主控因素不清,严重制约了油田的高效开发。为提高油水层识别效率、精度,明确油水分布规律,以测井、试油、试采等数据为基础,利用随机森林智能方法对单井油水层进行了解释,明确了合水南地区长7段的油水分布规律。结合恒速压汞、CT(computerized tomography)扫描、核磁共振等实验,从多角度分析油水分布的控制因素。结果表明:应用随机森林方法解释合水南地区长7段油水层,精度可达到78.9%;垂向上长71砂组油层发育优于长72砂组,油水同层和水层主要发育在长72砂组;在平面上,东部油层厚度较大且分布连续,西南部B60井区附近含水程度较高;储层中泥质含量、孔隙结构与原油黏度共同控制了储层内部流体性质,泥质含量的高低影响了储层孔径大小和孔喉连通性,储层孔隙结构与原油黏度影响流体可动性,从而控制研究区油水的空间分布。

, correspAuthors=王喜鑫, authorNote=null, correspAuthorsNote=
* 王喜鑫(1986—),男,汉族,黑龙江佳木斯人,博士,副教授。研究方向:储层智能表征与油气田开发地质。E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=yS8Q/2hYbvlQBRolfilnSA==, magXml=VuuSGYeTj0TpE3T65JVb9A==, pdfUrl=null, pdf=8Qh31BodudhaIU1DWtNXeg==, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=bR9olDhgoTkepPxZdAmaBQ==, mapNumber=null, authorCompany=null, fund=null, authors=

陈星兆(2001—),男,汉族,山西运城人,硕士研究生。研究方向:地质学。E-mail:

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陈星兆(2001—),男,汉族,山西运城人,硕士研究生。研究方向:地质学。E-mail:

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陈星兆(2001—),男,汉族,山西运城人,硕士研究生。研究方向:地质学。E-mail:

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球体代表孔隙;红、黄、绿色的球体半径较大,代表宏孔;蓝、紫色呈点状分布的球体分别代表介孔、微孔;球体的颜色和密集程度显示出不同的孔隙分布情况

, figureFileSmall=/EimjvhAi22MZOaAUVtt0Q==, figureFileBig=TvQy4xi8Ri4H5HjqyMF6Kg==, tableContent=null), ArticleFig(id=1177981104519787305, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149768568977404896, language=EN, label=Fig.9, caption=Pore throat connector models of typical sample, figureFileSmall=I2gEYlpaeDGwAGQIMzK1HA==, figureFileBig=SNF8lnmmTFeDIQF+fQcLKA==, tableContent=null), ArticleFig(id=1177981104586896170, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149768568977404896, language=CN, label=图9, caption=典型样品孔喉连通性模型

球体代表孔隙;红、黄、绿色的球体半径较大,代表宏孔;蓝、紫色呈点状分布的球体分别代表介孔、微孔;球体的颜色和密集程度显示出不同的孔隙分布情况

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T2为弛豫时间

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Characteristic parameters of constant velocity mercury injection curve

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 井名 深度/m 试油结论 孔喉半
径比
主流喉道
半径/μm
最大连通喉
道半径/μm
1 N140 1 622.3 油层 175.35 0.80 1.70
2 N143 1 626.1 油层 204.62 0.80 1.81
3 N143 1 648.9 油层 187.55 0.60 1.26
4 L27 1 637.8 油水同层 278.44 0.60 1.21
), ArticleFig(id=1177981105341870902, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149768568977404896, language=CN, label=表1, caption=

恒速压汞曲线特征参数

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 井名 深度/m 试油结论 孔喉半
径比
主流喉道
半径/μm
最大连通喉
道半径/μm
1 N140 1 622.3 油层 175.35 0.80 1.70
2 N143 1 626.1 油层 204.62 0.80 1.81
3 N143 1 648.9 油层 187.55 0.60 1.26
4 L27 1 637.8 油水同层 278.44 0.60 1.21
), ArticleFig(id=1177981105400591159, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149768568977404896, language=EN, label=Table 2, caption=

Oil test data of some samples of Chang 72 in Heshuinan area

, figureFileSmall=null, figureFileBig=null, tableContent=
井名 顶深/m 底深/m 试油
结论
原油黏度/
(mPa·s)
日产
油/t
日产
水/t
N31 1 675.5 1 681.5 水层 8.49 0 1.7
N131 1 657.0 1 661.0 油水同层 6.44 10.54 8.2
N140 1 657.0 1 661.0 油水同层 5.64 2.81 1.1
N158 1 568.0 1 621.5 油水同层 5.05 4.59 6.9
Z252 1 398.0 1 402.0 油层 4.93 6.38 0
Z251 1 668.0 1 672.0 油层 2.54 6.55 0
), ArticleFig(id=1177981105463505720, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149768568977404896, language=CN, label=表2, caption=

合水南地区长72小层部分样品试油数据表

, figureFileSmall=null, figureFileBig=null, tableContent=
井名 顶深/m 底深/m 试油
结论
原油黏度/
(mPa·s)
日产
油/t
日产
水/t
N31 1 675.5 1 681.5 水层 8.49 0 1.7
N131 1 657.0 1 661.0 油水同层 6.44 10.54 8.2
N140 1 657.0 1 661.0 油水同层 5.64 2.81 1.1
N158 1 568.0 1 621.5 油水同层 5.05 4.59 6.9
Z252 1 398.0 1 402.0 油层 4.93 6.38 0
Z251 1 668.0 1 672.0 油层 2.54 6.55 0
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鄂尔多斯盆地合水南地区长7段油水分布规律及控制因素
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陈星兆 1 , 王喜鑫 1, * , 李少华 1 , 何右安 2 , 黄天镜 2 , 薛婷 2 , 喻思羽 1 , 韩茂洲 1
科学技术与工程 | 论文·天文学、地球科学 2025,25(16): 6628-6641
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科学技术与工程 | 论文·天文学、地球科学 2025, 25(16): 6628-6641
鄂尔多斯盆地合水南地区长7段油水分布规律及控制因素
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陈星兆1 , 王喜鑫1, * , 李少华1, 何右安2, 黄天镜2, 薛婷2, 喻思羽1, 韩茂洲1
作者信息
  • 1 长江大学地球科学学院, 武汉 430100
  • 2 中石油长庆油田勘探开发研究院, 西安 710018
  • 陈星兆(2001—),男,汉族,山西运城人,硕士研究生。研究方向:地质学。E-mail:

通讯作者:

* 王喜鑫(1986—),男,汉族,黑龙江佳木斯人,博士,副教授。研究方向:储层智能表征与油气田开发地质。E-mail:
Oil-water Distribution and Control Factors of Chang 7 in Heshuinan Area of Ordos Basin
Xing-zhao CHEN1 , Xi-xin WANG1, * , Shao-hua LI1, You-an HE2, Tian-jing HUANG2, Ting XUE2, Si-yu YU1, Mao-zhou HAN1
Affiliations
  • 1 School of Geosciences, Yangtze University, Wuhan 430100, China
  • 2 Exploration and Development Research Institute, PetroChina Changqing Oilfield, Xi'an 710018, China
出版时间: 2025-06-08 doi: 10.12404/j.issn.1671-1815.2406233
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鄂尔多斯盆地合水南地区长7段储层地层水矿化度高、泥质含量非均质性强,导致油水分布规律及主控因素不清,严重制约了油田的高效开发。为提高油水层识别效率、精度,明确油水分布规律,以测井、试油、试采等数据为基础,利用随机森林智能方法对单井油水层进行了解释,明确了合水南地区长7段的油水分布规律。结合恒速压汞、CT(computerized tomography)扫描、核磁共振等实验,从多角度分析油水分布的控制因素。结果表明:应用随机森林方法解释合水南地区长7段油水层,精度可达到78.9%;垂向上长71砂组油层发育优于长72砂组,油水同层和水层主要发育在长72砂组;在平面上,东部油层厚度较大且分布连续,西南部B60井区附近含水程度较高;储层中泥质含量、孔隙结构与原油黏度共同控制了储层内部流体性质,泥质含量的高低影响了储层孔径大小和孔喉连通性,储层孔隙结构与原油黏度影响流体可动性,从而控制研究区油水的空间分布。

合水南地区  /  延长组7段  /  随机森林  /  油水分布  /  控制因素

The reservoir of Chang 7 in Heshuinan area of Ordos Basin has high salinity of formation water and strong heterogeneity of mud content, which leads to unclear understanding of oil-water distribution and main controlling factors. It seriously restricts the efficient development of the oilfield. In order to improve the efficiency and accuracy of the identification of oil-water layer and clarify the distribution law of oil and water, the intelligent random forest method was used to interpret the fluid properties on the basis of logging, oil test and production test data, and defined the distribution law of oil and water in Chang 7 in Heshuinan area. In addition, the controlling factors of oil and water distribution were analyzed from various angles by combining the experiments of constant rate mercury injection, CT (computerized tomography) and nuclear magnetic resonance. The results show that the accuracy of the fluid properties interpretation can reach 78.9% by using random forest method. In the vertical direction, the oil layer developed in Chang 71 is better than that in Chang 72, and the oil-water layer and water layer are mainly developed in Chang 72. In the plane direction, the eastern oil layer is thicker and distributed more continuously, and the southwest oil layer near the B60 well area has higher water content. The fluid properties inside the reservoir are controlled by the shale content, the pore structure and the viscosity of crude oil. The pore size and the connectivity of pore throat of the reservoir are affected by the content of mud. The pore structure of the reservoir and the viscosity of crude oil together control the fluid mobility, thus affecting the spatial distribution of oil and water in Heshuinan area.

Heshuinan area  /  Chang 7  /  random forest  /  oil-water distribution  /  control factors
陈星兆, 王喜鑫, 李少华, 何右安, 黄天镜, 薛婷, 喻思羽, 韩茂洲. 鄂尔多斯盆地合水南地区长7段油水分布规律及控制因素. 科学技术与工程, 2025 , 25 (16) : 6628 -6641 . DOI: 10.12404/j.issn.1671-1815.2406233
Xing-zhao CHEN, Xi-xin WANG, Shao-hua LI, You-an HE, Tian-jing HUANG, Ting XUE, Si-yu YU, Mao-zhou HAN. Oil-water Distribution and Control Factors of Chang 7 in Heshuinan Area of Ordos Basin[J]. Science Technology and Engineering, 2025 , 25 (16) : 6628 -6641 . DOI: 10.12404/j.issn.1671-1815.2406233
随着油气勘探开发理念的不断创新和进步,非常规油气逐渐转变为资源开发的重点[1-3]。自页岩气的开发取得多次成功实践之后,页岩油也开始受到科学界的广泛关注,针对页岩油的富集方式及控制因素,各种具有创新性的研究手段应运而生[4-6]。鄂尔多斯盆地延长组7段页岩油资源总量约为2×109 t,是页岩油勘探开发的重点层位[7]。长7段经历了复杂的沉积过程,在长71和长72亚段发育大量页岩和泥岩,它们作为烃源岩与薄层砂岩直接接触,组合出多套烃源岩与储集层在空间上叠置共生的“源-储结构”[8-10]。针对此类页岩油,前人已开展了大量的研究和攻关,逐渐形成了成熟的勘探技术和稳定的开发模式,尤其是长庆油田分公司针对长7段油藏已取得显著的开发成效,建成中国第一个百万吨页岩油开发示范区[11-12]
鄂尔多斯盆地延长组主要发育低渗透油藏,其油水分布情况受储层性质、流体性质和圈闭条件等多因素控制。过去20多年里,针对鄂尔多斯盆地蟠龙、华庆、陇东等地区,学者们对延长组低渗透油藏的油水分布控制因素进行了充分的研究。通过储层表征、测井、地震解释等手段明确了孔隙结构[13]、构造作用[14-15]、源储接触关系[16-18]等因素对油水空间分布的控制作用。
合水南地区构造稳定,地层平缓,以岩性油气藏为主[19-20],长7段发育典型的深水重力流沉积体系[21-22],在埋藏时期先后经历了压实、胶结、溶蚀等复杂的成岩作用[23-24],储层物性差,孔隙结构复杂[25-26]。本区的重力流沉积物包括砂质碎屑流沉积、浊流沉积、泥质碎屑流沉积、滑塌沉积4种类型,以砂质碎屑流、浊流沉积为主[27-29]。砂质碎屑流和浊流沉积物在岩性、粒度上有显著区别,两种沉积物在空间上的不同组合及后期强烈的成岩作用导致本区岩石类型复杂、储层非均质性强,并且受到地层水矿化度高、泥质分布不均等因素的影响,单井油水层的解释精度低,油水分布规律认识不清,主控因素认识不明。
鉴于此,以测井、试油、试采数据为基础,应用随机森林方法进行油水层解释,解释精度达到78.9%,进一步明确合水南地区长7段在空间上的油水分布规律,并结合计算机断层扫描(computerized tomography,CT)、恒速压汞、核磁共振技术总结了油水分布的主控因素,为相似地质背景下的油水分布规律分析和本区长7段页岩油开发区块的优选提供依据。
鄂尔多斯盆地是位于中国中西部的大型克拉通盆地,具有坡度平缓、构造简单的特征,可被划分为伊陕斜坡、伊盟隆起、晋西挠褶带、渭北隆起、天环坳陷和西缘逆冲带6个一级构造单元[6,30-31]。合水地区位于盆地的西南部[图1(a)],是构造平缓的西倾单斜构造[32-33]。鄂尔多斯盆地延长组为河流-三角洲-湖泊沉积体系,其层序反映了一套大型湖盆从形成、发育到消亡的全过程,是鄂尔多斯盆地主要的含油层系[34-35]。根据不同层位的沉积及旋回特征,可以将延长组分为10个油层组,从上至下依次命名为长1段-长10段。长7段是本文研究的目的层,沉积时期为湖盆发育的全盛期,在这种深湖沉积环境下发育的烃源岩主要为黑色页岩和暗色泥岩,其中在长71、长72同时发育暗色泥岩和黑色页岩,长73多发育黑色页岩,具有良好的生烃潜力。此外,在长71和长72也发育着以砂质碎屑流沉积为主、浊流沉积次之的致密砂岩[36-37],因此常存在薄层砂岩与黑色页岩、暗色泥岩相互叠加的良好源-储空间配置[图1(b)]。
合水南地区长7段为深水重力流沉积体系,垂向上发育砂质碎屑流、浊流沉积控制下的砂泥岩薄互层。储层岩性以细砂岩、粉砂岩为主,岩石类型主要为长石岩屑砂岩和岩屑长石砂岩,整体粒度较细,孔渗相关性较好,属于低孔低渗的致密砂岩储层。沉积后经历了强烈的成岩作用,导致储层泥质含量高、孔隙结构复杂,在发育粒间孔、晶间孔、溶蚀孔、微裂缝等多种孔隙类型,具有较强非均质性。
受地层水矿化度高、储层泥质含量非均质性强等因素的影响,电阻率曲线在识别油水层方面不确定性较高,重叠图法、交会图法和Archie公式等常规油水层识别方法在本区不适用。随机森林是一种基于决策树的典型集成学习算法,它以高效、便捷、准确为特征,现已被广泛运用在众多科学领域中,并且适用于解决岩性识别、构造预测等地质问题[38-40]。利用随机森林方法,可以较好地解决研究区岩性复杂、油水分布规律不明的情况。
决策树是一种树状结构的分类算法,可以针对离散型数据归纳出其中的规律,在分类的过程中自上而下地依据规律选择最优特征,树中的每个节点代表一种分类,非节点代表在某属性的划分,根据样本在该属性的不同取值将样本不断分类,直到达到建树的停止条件。随机森林以决策树为基分类器,将多个决策树和他们的分类结果集合起来,并用投票的方式选出最终分类结果(图2)[41-43]。以试油、试采数据为数据基础,选择多条测井曲线建立学习样本,应用随机森林方法对研究区油水层进行解释。
密度测井(DEN)曲线和声波测井(AC)曲线可以有效反应地层孔隙度[44],合水南地区长7段储层致密,物性较差,在测井曲线上表现为高DEN、高AC,另外,含油储层在测井曲线上表现为高自然电位(RT)。受沉积和成岩作用控制,长7段储层泥质含量较高,测井响应为高自然伽马(GR)[45]。综上,选择DEN、AC、RT及GR测井曲线作为随机森林的训练数据,其中80%的样本作为训练集、20%的样本作为验证集,训练后的模型对油水层的识别精度达到78.9%。应用训练好的模型对研究区5642个砂岩段进行了油水层解释。
以N118井与N115井为例,N115井在1 636~1 641、1 655~1 658、1 686.6~1 690 m试油结论为油层,原油日产量10.88 t,初次解释结论分别为油层、干层和差油层,随机森林解释结果均为油层[图3(a)]。N118井在1 532~1 537 m、1 550~1 552 m两段不产油,试油结论为水层,初次解释结论分别为油层和差油层,随机森林解释结果均为水层[图3(b)]。可以看出,训练后的随机森林模型解释结论更符合实际。
油水分布剖面图表明长71砂组和长72砂组在垂向上油水分布情况差异较大:长71砂组发育油层最多,并且油层分布较连续;长72砂组主要发育油水同层和干层,连续性较差;水层多产出于长72砂组,主要发育在研究区西南部B60井区附近,长7段从下至上含油性逐渐变好,如图4图5所示。
油层厚度平面分布图(图6)表明,4个小层油藏分布连续性好,整体上沿物源方向呈条带状分布。研究区东部油层厚度较大且油层发育较连续,西部含油性较差;长71砂组含油面积较连续,50%以上油层厚度大于8 m;长72砂组油层发育较分散,尤其是长 7 2 2小层东部的油层厚度普遍小于4 m,与长71砂组含油性差异明显。
随机森林模型可以反映各参数对含油性解释的影响程度,其中20项决策树中4项测井参数对比结果显示,自然伽马曲线的权重系数最大,达到0.29,如图7所示。
合水南地区长7段发育碎屑成分复杂的重力流砂体,在成岩过程中经历了强烈的胶结作用,形成大量以伊利石、伊蒙混层为主的泥质胶结物,因此储层泥质含量较高。高泥质含量不仅占据孔隙空间,甚至堵塞喉道,使储层孔隙结构复杂,储层质量非均质强,限制流体在储层中流通和聚集,导致油水分布不均。
合水南地区长7段经历了复杂的成岩作用,混杂的碎屑组分和后期改造导致储层孔隙结构复杂。分别使用CT扫描、恒速压汞和核磁共振实验对储层孔隙结构进行表征,并对比油层和油水同层样品的孔隙结构参数和孔喉分布特征,分析孔隙结构对流体可动性的影响。
CT扫描是建立微观孔隙结构的技术之一。该技术可以通过X射线扫描建立样品的孔隙网络模型,能够实现无损测量,便于直观观察储层的孔喉大小和连通情况[46]。分别在N143井、LY18井选取原油黏度相同的油层、油水同层样品进行CT扫描实验,得到三维构建的孔隙网络模型(图8)和孔喉连通性模型(图9)。两个样品的孔隙尺寸和连通性差异较大,油层样品孔隙发育较好,平均孔径较大,表现出多孔、高连通性的特征;油水同层样品孔隙发育较差,极少发育宏孔,表现出少孔、连通性差的特征。在原油黏度相当的情况下,储层中孔径越大、连通性越好,储层的渗流能力就越好,孔隙尺寸和连通性控制了储层的含油性质。
恒速压汞实验是在界面张力和接触角保持不变的前提下以恒定的低速向样品注入汞,形成一个准静态进汞过程,在此过程中测量进汞压力和汞饱和度的变化,并得到评价孔隙结构的参数[47]。选取4块岩心样品,通过恒速压汞实验得到压汞曲线(图10)和特征参数(表1)。油层、油水同层样品之间的孔喉特征参数存在差异:与4号样品相比,1、2、3号样品的孔喉半径比较小,主流喉道半径和最大连通喉道半径较大,尤其是孔喉半径比具有明显差异,孔喉半径比偏小的样品试油结论均为油层。1、2、3号样品的微观非均质性和孔喉连通性优于4号样品,表明孔喉结构在微观上控制流体的运移和分布。
核磁共振技术是表征储层岩石物理性质和流体流动特征的重要方法,具有快速、灵敏、无损的优点,并且测试范围大,可以进行全孔径表征。岩石孔隙在饱和流体状态下,其氢原子恢复到平衡所需要的弛豫时间T2不同,弛豫时间大小与孔隙大小呈正相关关系,根据样品T2谱图离心前后的变化可以计算出可动流体饱和度,反映储层内部的流体可动性[47-48]。恒速压汞实验结果表明1、4号样品孔隙结构差异明显,选取1、4号的平行深度样品,进行核磁共振与离心实验。
首先用3 mPa·s的煤油饱和样品并测量T2谱,然后采用120 r/s的转速对样品进行离心处理,测量T2谱,对比核磁共振T2谱图的变化(图11)。结果显示,样品1的T2谱图变化更大,低黏度离心后孔隙分量减小较多,指示较大的可动流体饱和度,这表明孔隙结构与流体可动性有重要关联,孔隙结构越复杂,流体可动性越差。
综上所述,储层的孔隙结构是影响油水层分布的重要因素。孔隙是原油的主要储集空间,喉道是原油在孔隙之间的运移通道,具有较好孔喉连通性的储层,其内部流体具有更好的可动性。此外,储层的微观非均质性会使不同区域的孔隙结构存在差异,导致油水层在空间上分布复杂。
通过分析125个样品的黏度数据,统计出原油黏度分布在2.34~15.87 mPa·s,平均黏度为5.89 mPa·s,高黏度是合水南地区长7段页岩油的重要特征。
长72小层的油层、油水同层和水层中原油黏度具有明显差异,油层的平均原油黏度为5.1 mPa·s,油水同层的平均原油黏度为5.8 mPa·s,水层的平均原油黏度为8.49 mPa·s(图12)。在研究区选取并统计部分样品的试油数据,同样显示出含油性不同的储层之间具有明显的原油黏度差异(表2)。
在N27、N23、L27、N143井中选取典型岩心样品,分别用黏度为3 mPa·s的煤油和黏度为5、7、9 mPa·s的原油对样品进行饱和处理,利用核磁共振实验得到各样品离心后的T2谱图(图13),并统计出可动流体饱和度。结果显示,流体黏度与可动流体饱和度之间呈负相关关系:当流体黏度为3 mPa·s时,可动流体饱和度平均为31.3%;当流体黏度为9 mPa·s时,可动流体饱和度平均为12.5%。流体黏度每增加2 mPa·s,可动流体饱和度平均下降6%。
黏度作为表征储层流体特征的参数,它的大小不仅对原油渗流能力有重要影响,更是直接控制着原油的开采难易程度[49]。研究区长7段原油黏度与日产油具有明显的相关性,随着原油黏度增加,探井日产油量呈降低趋势(图14)。上述结果表明,原油黏度与储层含油性和流体可动性有重要关联,黏度控制流体渗流,影响了储层的产出能力。
(1)对于研究区长7段岩性复杂、泥质含量高、非均质性强的储层,随机森林方法可以较好地解决油水层识别的问题。基于试油、试采数据,选择DEN、AC、RT、GR测井曲线作为学习标签,建立随机森林模型解释单井油水层,解释精度可达78.9%。
(2)根据随机森林解释结论,分别在垂向和平面上分析出合水南地区长7段油水分布规律。垂向上,长71砂组油层发育最连续且油层厚度较大,长72砂组含油层系较分散,多发育油水同层和水层;平面上,研究区东部油层厚度较大且含油面积较连续,水层多发育在西南部B60井区附近。
(3)控制研究区油水分布的主要因素包括储层泥质含量、孔隙结构以及原油黏度。GR在测井解释中占到0.29的权重,储层泥质含量对油水层分布有重要影响;具有较好孔隙结构的储层渗流能力较好,孔隙结构复杂的储层流体可动性较差;原油黏度影响储层含油性和流体可动性,原油黏度差异会导致油水层分异。
  • 中国石油科技创新基金(2021DQ02-0106)
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2025年第25卷第16期
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doi: 10.12404/j.issn.1671-1815.2406233
  • 接收时间:2024-08-21
  • 首发时间:2025-07-09
  • 出版时间:2025-06-08
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  • 收稿日期:2024-08-21
  • 修回日期:2025-03-19
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中国石油科技创新基金(2021DQ02-0106)
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    1 长江大学地球科学学院, 武汉 430100
    2 中石油长庆油田勘探开发研究院, 西安 710018

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* 王喜鑫(1986—),男,汉族,黑龙江佳木斯人,博士,副教授。研究方向:储层智能表征与油气田开发地质。E-mail:
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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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