Article(id=1156983786253669198, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156983783787421903, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2402157, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1711382400000, receivedDateStr=2024-03-26, revisedDate=1731859200000, revisedDateStr=2024-11-18, acceptedDate=null, acceptedDateStr=null, onlineDate=1753776030362, onlineDateStr=2025-07-29, pubDate=1739808000000, pubDateStr=2025-02-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753776030362, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753776030362, creator=13701087609, updateTime=1753776030362, updator=13701087609, issue=Issue{id=1156983783787421903, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='5', pageStart='1753', pageEnd='2192', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753776029774, creator=13701087609, updateTime=1769691857141, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223739602251436918, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156983783787421903, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223739602251436919, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156983783787421903, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1753, endPage=1763, ext={EN=ArticleExt(id=1156983787084141399, articleId=1156983786253669198, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Review on Particle Transport and Deposition Properties in Porous Medium, columnId=1177980717679128679, journalTitle=Science Technology and Engineering, columnName=Surveies·Petroleum and Natural Gas Industry, runingTitle=null, highlight=null, articleAbstract=

Particle profile control and blockage is recognized as an important method for enhancing oil recovery. The migration and deposition characteristics of particles in porous media are understood to facilitate the optimization of particle preparation, thereby improving compatibility with reservoir pore throats and blocking efficiency. Factors such as particle concentration, particle size, porous medium structure, particle size ratio, and fluid parameters within the medium were reviewed for their effects on migration and deposition. Research results from various simulation methods, including simplified geometry, mesoscopic simulation, lattice Boltzmann method-discrete element method (LB-DEM) and computational fluid dynamics-discrete element method(CFD-DEM) were summarized. It is indicated that the critical value of the particle size ratio influences the deposition location and blockage degree in porous media. Different particle sizes are subjected to significant differences in forces, with larger particles being notably affected by hydrodynamics, gravity, and fluid flow rates. The fluid flow model within porous media is not yet fully unified. However, the Brinkman-Forchheimer-Darcy model is noted for its strong applicability. The CFD-DEM method, approached from a microscopic perspective, has validated the flow-solid coupling of migration and deposition within the medium, providing a basis for profile control schemes in heterogeneous reservoirs.

, correspAuthors=Zhi-jun YAN, 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=Bo WANG, Zhi-jun YAN, Yi PAN, Shuang-chun YANG), CN=ArticleExt(id=1156983849755431844, articleId=1156983786253669198, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=颗粒在多孔介质内运移沉积特性研究进展, columnId=1177980717817540712, journalTitle=科学技术与工程, columnName=综述·石油、天然气工业, runingTitle=null, highlight=null, articleAbstract=

颗粒调剖堵水是提高原油采收率的重要途径。了解颗粒在多孔介质中的运移沉积特性,便于颗粒制备的优化,提高颗粒与地层孔喉配伍性和封堵效率。综述了颗粒浓度值、粒径、多孔介质结构、粒径比、介质内流体参数等因素对运移沉积的影响,总结了简化几何、介观模拟、LB-DEM(lattice Boltzmann method-discrete element method)、CFD-DEM(computational fluid dynamics-discrete element method)等模拟方法研究结果。分析表明,粒径比的临界值影响多孔介质的沉积位置和堵塞程度,粒径不同、所受力差异较大,大颗粒受水动力、重力、流体流速影响显著。多孔介质内流体流动模型尚未完全统一,Brinkman-Forchheimer-Darcy模型适用性较强,CFD-DEM方法从微观角度对介质内运移沉积流固耦合进行了验证,为非均质储层的调剖方案提供了依据。

, correspAuthors=闫治君, authorNote=null, correspAuthorsNote=
*闫治君(1997—),男,汉族,河南商丘人,硕士研究生。研究方向:油藏数值模拟。E-mail:
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王博(1983—),女,汉族,辽宁沈阳人,博士,讲师。研究方向:油田化学剂及提高采收率。E-mail:

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王博(1983—),女,汉族,辽宁沈阳人,博士,讲师。研究方向:油田化学剂及提高采收率。E-mail:

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Journal of the Taiwan Institute of Chemical Engineers, 2018, 82: 214-225., articleTitle=Numerical simulation of flow behavior of particles in an inverse liquid-solid fluidized bed with a jet using CFD-DEM, refAbstract=null)], funds=[Fund(id=1225467167001457488, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, awardId=LJKZ0417, language=CN, fundingSource=辽宁省教育厅基于改性膨润土智能钻井液研制及评价重点项目(LJKZ0417), fundOrder=null, country=null), Fund(id=1225467167160841051, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, awardId=LJKZ0372, language=CN, fundingSource=辽宁省教育厅科学研究经费项目(LJKZ0372), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1225467162610020909, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, xref=null, ext=[AuthorCompanyExt(id=1225467162622603823, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, companyId=1225467162610020909, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=College of Petroleum and Natural Gas Engineering, Liaoning Petrochemical University, Fushun 113001, China), AuthorCompanyExt(id=1225467162635186736, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, companyId=1225467162610020909, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=辽宁石油化工大学石油天然气工程学院, 抚顺 113001)])], figs=[ArticleFig(id=1225467165776720635, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=EN, label=Fig.1, caption=The classification schematic diagram of particle size distribution[3], figureFileSmall=m2vO9w+vmKXipMBVsNferg==, figureFileBig=vVjn+NDT54+9IN8lloJILg==, tableContent=null), ArticleFig(id=1225467165877383938, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=CN, label=图1, caption=颗粒粒径种类划分示意图[3], figureFileSmall=m2vO9w+vmKXipMBVsNferg==, figureFileBig=vVjn+NDT54+9IN8lloJILg==, tableContent=null), ArticleFig(id=1225467166007407373, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=EN, label=Fig.2, caption=The retention mechanism of fine particles[15], figureFileSmall=HWhLDszjnBeE37K3ic3QsQ==, figureFileBig=xX4nUhquy9liReOTnWuOPQ==, tableContent=null), ArticleFig(id=1225467166116459285, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=CN, label=图2, caption=微小颗粒滞留机理[15], figureFileSmall=HWhLDszjnBeE37K3ic3QsQ==, figureFileBig=xX4nUhquy9liReOTnWuOPQ==, tableContent=null), ArticleFig(id=1225467166250677027, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=EN, label=Fig.3, caption=Capillary model[24], figureFileSmall=rQQ/Vifhdr6MJboQAfx4Vg==, figureFileBig=4N8mgDAdqfaDwnDwEXUgEw==, tableContent=null), ArticleFig(id=1225467166363923246, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=CN, label=图3, caption=毛细管模型[24], figureFileSmall=rQQ/Vifhdr6MJboQAfx4Vg==, figureFileBig=4N8mgDAdqfaDwnDwEXUgEw==, tableContent=null), ArticleFig(id=1225467166493946678, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=EN, label=Table 1, caption=

Summary table of literature on particle transport under seepage flow

, figureFileSmall=null, figureFileBig=null, tableContent=
实验方法 多孔介质材料 采用方式 规律结论 文献
室内实验 砾石填料柱 改变渗流流速 渗流速影响颗粒穿透率 周永潮等[25]
室内实验 河砂柱 增大流速 颗粒滞留时间减少 Sasidharan等[26]
室内实验 高岭石砂柱 改变渗流流速 颗粒分布由入口至底部逐渐细化 Hammadi等[27]
室内实验 石英砂柱 改变渗流方向 颗粒脱离效果更明显 刘泉生等[28]
室内实验 土柱 不同渗流方向 重力影响渗流对颗粒的弥散 陈星欣等[2,29]
室内实验 粉砂柱 水平/竖向渗流 颗粒簇流失与水力梯度相关 张灿虹等[30]
室内实验 石英砂柱 水流停滞时间 胶体颗粒再迁移受水流停滞时间影响 袁瑞强等[31]
), ArticleFig(id=1225467166602998595, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156983786253669198, language=CN, label=表1, caption=

渗流作用下颗粒运移相关文献总结表

, figureFileSmall=null, figureFileBig=null, tableContent=
实验方法 多孔介质材料 采用方式 规律结论 文献
室内实验 砾石填料柱 改变渗流流速 渗流速影响颗粒穿透率 周永潮等[25]
室内实验 河砂柱 增大流速 颗粒滞留时间减少 Sasidharan等[26]
室内实验 高岭石砂柱 改变渗流流速 颗粒分布由入口至底部逐渐细化 Hammadi等[27]
室内实验 石英砂柱 改变渗流方向 颗粒脱离效果更明显 刘泉生等[28]
室内实验 土柱 不同渗流方向 重力影响渗流对颗粒的弥散 陈星欣等[2,29]
室内实验 粉砂柱 水平/竖向渗流 颗粒簇流失与水力梯度相关 张灿虹等[30]
室内实验 石英砂柱 水流停滞时间 胶体颗粒再迁移受水流停滞时间影响 袁瑞强等[31]
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颗粒在多孔介质内运移沉积特性研究进展
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王博 , 闫治君 * , 潘一 , 杨双春
科学技术与工程 | 综述·石油、天然气工业 2025,25(5): 1753-1763
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科学技术与工程 | 综述·石油、天然气工业 2025, 25(5): 1753-1763
颗粒在多孔介质内运移沉积特性研究进展
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王博 , 闫治君* , 潘一, 杨双春
作者信息
  • 辽宁石油化工大学石油天然气工程学院, 抚顺 113001
  • 王博(1983—),女,汉族,辽宁沈阳人,博士,讲师。研究方向:油田化学剂及提高采收率。E-mail:

通讯作者:

*闫治君(1997—),男,汉族,河南商丘人,硕士研究生。研究方向:油藏数值模拟。E-mail:
Review on Particle Transport and Deposition Properties in Porous Medium
Bo WANG , Zhi-jun YAN* , Yi PAN, Shuang-chun YANG
Affiliations
  • College of Petroleum and Natural Gas Engineering, Liaoning Petrochemical University, Fushun 113001, China
出版时间: 2025-02-18 doi: 10.12404/j.issn.1671-1815.2402157
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颗粒调剖堵水是提高原油采收率的重要途径。了解颗粒在多孔介质中的运移沉积特性,便于颗粒制备的优化,提高颗粒与地层孔喉配伍性和封堵效率。综述了颗粒浓度值、粒径、多孔介质结构、粒径比、介质内流体参数等因素对运移沉积的影响,总结了简化几何、介观模拟、LB-DEM(lattice Boltzmann method-discrete element method)、CFD-DEM(computational fluid dynamics-discrete element method)等模拟方法研究结果。分析表明,粒径比的临界值影响多孔介质的沉积位置和堵塞程度,粒径不同、所受力差异较大,大颗粒受水动力、重力、流体流速影响显著。多孔介质内流体流动模型尚未完全统一,Brinkman-Forchheimer-Darcy模型适用性较强,CFD-DEM方法从微观角度对介质内运移沉积流固耦合进行了验证,为非均质储层的调剖方案提供了依据。

运移沉积  /  多孔介质  /  颗粒  /  粒径比  /  调剖堵水

Particle profile control and blockage is recognized as an important method for enhancing oil recovery. The migration and deposition characteristics of particles in porous media are understood to facilitate the optimization of particle preparation, thereby improving compatibility with reservoir pore throats and blocking efficiency. Factors such as particle concentration, particle size, porous medium structure, particle size ratio, and fluid parameters within the medium were reviewed for their effects on migration and deposition. Research results from various simulation methods, including simplified geometry, mesoscopic simulation, lattice Boltzmann method-discrete element method (LB-DEM) and computational fluid dynamics-discrete element method(CFD-DEM) were summarized. It is indicated that the critical value of the particle size ratio influences the deposition location and blockage degree in porous media. Different particle sizes are subjected to significant differences in forces, with larger particles being notably affected by hydrodynamics, gravity, and fluid flow rates. The fluid flow model within porous media is not yet fully unified. However, the Brinkman-Forchheimer-Darcy model is noted for its strong applicability. The CFD-DEM method, approached from a microscopic perspective, has validated the flow-solid coupling of migration and deposition within the medium, providing a basis for profile control schemes in heterogeneous reservoirs.

transport and deposition  /  porous media  /  particle  /  particle size ratio  /  profile control and water shutoff
王博, 闫治君, 潘一, 杨双春. 颗粒在多孔介质内运移沉积特性研究进展. 科学技术与工程, 2025 , 25 (5) : 1753 -1763 . DOI: 10.12404/j.issn.1671-1815.2402157
Bo WANG, Zhi-jun YAN, Yi PAN, Shuang-chun YANG. Review on Particle Transport and Deposition Properties in Porous Medium[J]. Science Technology and Engineering, 2025 , 25 (5) : 1753 -1763 . DOI: 10.12404/j.issn.1671-1815.2402157
由于受地质条件和开采方式的影响,油田注水波及传播不足是一个共性存在的问题,致使水沿着优势通道流通,大大降低了注水开发的利用效率。微球颗粒主要用于封堵高渗透层,扩大影响低渗透岩石层水流的范围,进而提高油田的开采寿命。此外,微球颗粒还能够优化注入液体和地层之间的流动力学特性,增强地层流体的位移效果,改善油田油水分离情况,进而提高油田整体开发效率。但由于微球粒径与多孔介质吼道的适配性难以把握,使其具有工程应用的局限性,因此需要加强该问题的研究。在调研国内外文献的基础上,现综合分析已有的实验方法和模拟方法,全面探讨颗粒在多孔介质中运移沉积特性并对存在问题进行剖析,以期对颗粒调剖堵水提供借鉴。
分析颗粒在多孔介质中的运移沉积特性的实验以现场实验和室内实验为主。现场实验与真实地层情况较符合,对颗粒在多孔介质中的运移规律和机理掌握更加准确,但其可控性较差。相关学者大多通过室内实验来研究此类问题。相比而言室内实验的多孔介质段与真实的含水地层存在一定的差异,但其影响参数的可控性更强,易于得到运移沉积的主要影响参数和一般性规律[1]
颗粒运移沉积分布受粒径的大小影响显著,粒径与吼道的匹配性越好,封堵效果越明显。就颗粒粒径的范围而言,通常认为粒径在1~100 nm的颗粒属于胶体范围;有学者对粒径进一步细分,将直径小于1 μm的微粒称为胶体,而直径大于1 μm的微粒称为颗粒。另外,也有学者将10 μm作为胶体与颗粒之间的分界[2]。根据粒径的不同,颗粒的种类划分范围如图1所示[3]
颗粒粒径不同,运动时所受的力差异较大,进而影响多孔介质渗透率下降的速度。颗粒粒径在0.1~10 μm范围内颗粒运动时需要考虑所有的机理和力,且当粒径达到50 μm时吸附作用仍产生影响[4]。布朗运动的效果受粒径的影响较大,当颗粒粒径dp<1 μm时,颗粒的迁移受到布朗运动的影响较为显著,对于dp>1 μm时,布朗运动的影响在很大程度上受到流体黏性阻力的限制[5]。根据Frey等[6]的研究,当dp>10 μm时,惯性、重力和流体是影响颗粒在多孔介质内部或界面沉积的关键因素。当颗粒粒径较大时,会迅速造成沉积,但吼道堵塞程度较轻,此时渗透系数会急剧下降;相反,粒径小的颗粒进入多孔介质孔隙结构内部时会导致渗透系数缓慢减小进而降低渗透性[7]。雷海燕等[8]研究发现粒径较小时,颗粒界面沉积量与内部沉积差异明显;当粒径较大时内部沉积小于界面沉积,二者差值与流体浓度成正比。
为了提高颗粒的封堵效果,常采用改善颗粒的浓度进行优化。胡培政等[9]和王富华等[10]通过提高颗粒浓度,发现运移通道堵塞的发生概率增大且超过一定浓度后会发生更严重堵塞行为。在渗流速度恒定的情况下,当颗粒浓度低于某一临界点时,交叉曲线的相对浓度与颗粒浓度正相关;高于临界点时,二者则成反比,且渗流速度影响颗粒临界浓度[11]
颗粒进入多孔介质内部时,粒径比是影响颗粒沉积位置和堵塞方式的重要参数。颗粒在孔喉尺度下通过多孔介质有3种机制:筛分、表面沉积和拱桥,如图2所示。Herzig等[12]将介质表面视为一个光滑的球体,认为悬浮颗粒与多孔介质之比(dp/Dp)在筛分中的临界值为0.154;后来又研究发现,当临界值小于0.002时,此时筛分作用的影响仍然存在。Xu等[13]则通过实验进一步验证了dp/Dp存在一个临界点为0.008,但当dp/Dp<0.008时不考虑筛分作用。在筛分过程中,多孔介质的表面粗糙度、颗粒形状和孔隙水的化学成分都会对筛选结果产生一定的影响。表面沉积又称为“内部滤饼”,是指1/7<dp/Dp<1/3时,水流携带小颗粒进入孔隙内部并聚集。此时,颗粒和多孔介质表面通过范德华力和双层力相互作用,致使颗粒沉积在多孔介质表面,进而引起孔道直径的减小和渗透率的降低。拱桥又称为“外部滤饼”,是指穿过较大孔隙的颗粒同时到达通道,并沉积在多孔介质的界面上,形成类似 “桥” 的结构,此时dp/Dp>1/3。颗粒大小、惯性、流体、重力、扩散、吸附等许多因素主要与颗粒表面沉积过程和颗粒拱桥的形成有关。颗粒经过孔隙吼道时的沉积方式不同,对多孔介质内部的孔隙结构和渗透系数产生不同程度的影响[3,14]
此外,刘泉生等[16]还对多孔介质与颗粒的粒径比对颗粒沉积的影响进行了验证,发现随着该比值的增加,颗粒相对浓度的峰值和终值都呈上升趋势。依据该比值的不同,将颗粒运移沉积分为滤饼过滤型、迁移沉积型和自由迁移型。根据颗粒在多孔介质中的滞留机理,筛分、表面沉积和颗粒拱桥的形成是迁移过程中颗粒在多孔介质中滞留的主要原因[17]。赵伟等[18]研究表明,多孔介质的相对渗透系数 K/K0(其中K0为初始饱和含水率,K为不同时间的饱和含水率)的降低与石英砂颗粒的直径和浓度之间存在着显著的联系。
多孔介质内部孔隙结构的复杂性决定了颗粒沉积位置和形态的不确定性[3]。颗粒内部堆积会改变孔隙度和梯度压力,致使渗透率下降。Ahfir等[19]对比两种不同多孔介质发现多孔介质的内部结构特性影响小颗粒与介质颗粒的碰撞方式及小颗粒的捕获沉积量的大小。暴丽霞等[20]测试了不同材料构成的多孔介质孔径分布特点,微介孔材料对内部的孔径、吼道连通性和运移颗粒沉积分布影响较大。
流体流经多孔介质时,一方面受到流体自身流动特性的限制,同时也受多孔介质内部孔喉特性的影响。二者耦合作用下,决定了多孔介质渗透能力变化的快慢。通常而言,相较于恒定流量条件下,恒定水头条件下含水介质的渗透性下降速度更快[21]。崔明杰[22]分析了流体速度与颗粒沉积量关系,发现来流流体速度越大时,颗粒随流体流出多孔介质,颗粒的沉积量越小。Bradford等[23]研究发现,颗粒接触位置和较窄的吼道内部会形成低渗地带,易形成颗粒沉积区。此外,采用曲线拟合技术分析实验数据,发现颗粒的沉积速度与渗流速度之间存在函数关系,然而具体的函数形式会受颗粒种类和粒径大小的影响而有所差异[24]
在多孔介质中,颗粒在流体携带下进入吼道内部并发生不同维度的运移沉积。在这个过程中,颗粒的运移和堆积情况受到诸多因素的影响。主要通过改变渗流流速、渗流方向以及水流停滞等方法,分析了流体特性对颗粒运移沉积的影响。渗流作用下相关实验文献总结,如表1所示。
颗粒在多孔介质中微观运移的特性、沉积分布范围和沉积量大小是多种因素共同作用的结果。主要有多孔介质与颗粒粒径比、渗流作用、颗粒的浓度和粒径、流体流速以及多孔介质内部的连通性等它们对颗粒的沉积位置和沉积量都产生一定的影响。以上方法能在一定程度上分析出某种因素对颗粒沉积的作用,但单一影响因素分析与复杂的地层和流体特性存在一些差异。
对颗粒在多孔介质中的运移沉积规律进行实验研究时,由于受实验客观因素的限制,很难得出一般性的颗粒运移沉积规律。通常是基于已有的实验数据建立颗粒在多孔介质中的运移沉积的理论模型和多孔介质内流体流动模型。包括微小颗粒的运动方程、多孔介质内部流体的流动模型、颗粒堆积算法(涉及界面堆积和孔隙内部堆积)、涉及复杂边界条件的问题,以及研究流体与颗粒之间的耦合算法[22]
颗粒在多孔介质内的运移沉积的理论模型主要可以分为传统模型和经典模型。传统模型包括毛细管模型和球状模型两大类;经典模型由可逆和不可逆沉积方程构成。
图3所示的毛细管模型[24],颗粒穿过相同的毛细管结构单元体介质并沉降在类似毛细管的收集器中。球状模型是将多孔介质和颗粒均简化为圆形颗粒,每个单元体含有NC个圆球状收集体,在该模型中,收集器的直径被假设为与颗粒的平均直径(ac)相等[3]。其中球状收集器周围的流场可通过渗流流量函数ψ表示,即
E4ψ=0
式(1)中:E4为流场函数;ψ为流量函数。$E^{2}=\frac{\partial^{2}}{\partial r^{2}}+$ $\frac{\sin \theta}{r^{2}} \frac{\partial}{\partial \theta}\left(\frac{1}{\sin \theta} \frac{\partial}{\partial \theta}\right)$, (r,θ)为极坐标。
Happel模型[3]是研究颗粒材料的常用模型之一,主要考虑重力和流体的影响。根据该模型,多孔介质由许多球形单元组成,每个单元包含一个半径为ac的固体颗粒和覆盖在颗粒周围的液体层,液体层的半径为b。当特定条件得到满足时,acb会取特定数值[11,16],二者的关系式为
$a_{\mathrm{c}} / b=(1-\phi)^{1 / 3}$
式(2)中: φ为多孔介质孔隙度。
Kuwabara模型作用十分突出,该模型与Happel模型在很多方面相似,区别在于r=b时,则有
$\omega=\frac{\partial u_{\theta}}{\partial r}+\frac{u_{\theta}}{r}-\frac{1}{r} \frac{\partial u_{r}}{\partial \theta}$
式(3)中:ω为涡量分量。
在周期性收缩管模型[11,16,24]中,颗粒在孔隙通道的交叉点处沉积,此时孔隙通道方向与多孔介质的渗流流向是平行的。最终,在对不同尺寸的颗粒进行测试后,提出了新的模型——双曲收缩管模型,比较发现,双曲收缩管模型和周期收缩管模型的结果不相上下。
在数值求解方面,传统的颗粒运移沉积模型面临挑战,难以有效解决实际的工程问题。这些经典模型采用了多孔介质和颗粒平均化的方法来建立模型。经典颗粒运移沉积模型的动力方程,主要分为两类[32]:不可逆沉积和可逆沉积。不可逆沉积是指颗粒一旦在多孔介质中沉积后,不随多孔介质内的流体再次流动[12,33-34],其方程式为
$\frac{\partial \sigma^{\prime}}{\partial t}=\lambda C u$
式(4)中:σ'为沉积量;λ为过滤系数;C为固体颗粒的浓度;u为渗流速率值。
可逆沉积是指颗粒随水流沉积和被携带反复交替的过程,其动力方程[35]
$\frac{\partial \sigma^{\prime}}{\partial t}=K_{\mathrm{a}} C u-K_{\mathrm{d}} \sigma^{\prime}$
式(5)中:KaKd分别为吸附系数和解析函数。
颗粒沉积动力方程表明,可逆与不可逆在颗粒运移沉积的过程中是相排斥存在的。但Crittenden等[36]又提出颗粒在多孔介质中运移时,颗粒既有不可逆的成熟沉积阶段,又存在颗粒反复被吸附的可逆阶段的现象。
经典颗粒对流扩散方程是从宏观力学的角度进行分析,颗粒在多孔介质中的运移沉积主要是对流扩散的作用,在稳定流的情况下,宏观角度上颗粒在均匀、饱和下的多孔介质中运移沉积的对流扩散方程[37-38]
$\frac{\partial C}{\partial T}+\frac{\rho}{\theta} \frac{\partial S}{\partial T}=D \frac{\partial^{2} C}{\partial X^{2}}-u \frac{\partial C}{\partial X}$
式(6)中:C为颗粒浓度,mg/L;T为时间;ρ为介质密度,g/cm2;θ为介质孔隙率;S为固相中沉积的颗粒浓度,μg/g;D为弥散系数,cm2/min;X为颗粒输送距离,cm;u为过水断面平均流速,cm/s。
Tufenkji[39]鉴于颗粒在多孔介质界面沉积时的弥散效应,对颗粒沉积的动力学方程进行了改进。Eaf等[40]利用实验结果同样对颗粒沉积的动力方程和质量方程进行了改进,也考虑了弥散的影响并求出具体的此类问题的解析解。此外,Xu等[41]和Porubcan等[42]所提出的经验模型中都同时考虑到筛滤作用对颗粒运移沉积的影响。
虽然可以利用传统的理论模型在宏观层面模拟颗粒在多孔介质中的迁移和沉积过程,但各种经验模型的预测结果仍然存在一些缺陷和限制。理论模型化方式通常存在对多孔介质的模型简化不够准确、颗粒沉积率、沉积位置计算复杂、缺乏直观表征颗粒形状对运移沉积产生的影响等不足。
探讨多孔介质中流体流动模型问题时会遇到一个著名的定律,这是法国水利工程师达西最初提出的公式,其表达式为
$V=-\frac{K}{\mu} \frac{\partial p}{\partial x}$
式(7)中:V为渗流速度;K为多孔介质渗透率;μ为黏度。
在多孔介质中,流体的速度会随着压力梯度的增加而增加。Dracy的研究为多孔介质中流体流动问题提供了扎实的理论基础。后续的研究中,有关学者发现Darcy定律的适用范围仅限低渗透率、低流速和定常流动现象。
Wooding[43]通过对比N-S方程对Darcy定律进行了修正,这项研究主要考虑了高渗透率条件下流体的惯性阻力和加速效应,修正方程为
$\rho\left[\frac{1}{\varepsilon}+\frac{1}{\varepsilon^{2}}(\boldsymbol{V} \cdot \nabla \boldsymbol{V})\right]=-\nabla p-\frac{\mu}{K} \boldsymbol{V}$
式(8)中:V· V为惯性阻力;ρ为密度;ε为孔隙率; p为压差;μ为黏度;K为渗透率。
Forchheimer发现当流体速度较高时,将Darcy定律中的流动阻力部分与流速的平方项结合起来,即可得到Darcy-Forchheimer方程为
$\nabla p=-\frac{\mu}{K} \boldsymbol{V}-C_{\mathrm{F}} K^{\frac{1}{2}} \boldsymbol{\rho}|\boldsymbol{V}| \boldsymbol{V}$
式(9)中:CF为无量纲惯性阻力系数。
Lage等[44]提出,当多孔介质内的流体为湍流时无量纲惯性阻力系数CF与流速呈正相关。此外,雷诺数的大小也决定了流体流动时所克服力的大小,通常高雷诺数下,主要考虑惯性阻力的作用[45-46]。为了更好地满足固壁面无滑移的边界条件,Brinkman[47]对Darcy再次进行了修正,方程式为
$\nabla p=-\frac{\mu}{K} \boldsymbol{V}+\mu_{\mathrm{m}} \nabla^{2} \boldsymbol{V}$
式(10)中: μm为有效黏性阻力系数,μm=μ/εp
Vafai等[48]通过在表示单元上取N-S方程平均值的方式,并引入了一个合适的封闭方程。得到了Darcy-Brinkman-Forchheimer 方程,即
$\begin{array}{c} \rho\left[\frac{1}{\varepsilon} \frac{\partial V}{\partial \tau}+\frac{1}{\varepsilon^{2}}(\boldsymbol{V} \cdot \nabla \boldsymbol{V})\right]=\frac{1}{\varepsilon} \nabla(\varepsilon P)+ \\ \frac{\mu}{\varepsilon \rho} \nabla^{2} \boldsymbol{V}-\frac{\mu}{K} \boldsymbol{V}-\frac{1}{\sqrt{K}} C_{\mathrm{F}} \rho|\boldsymbol{V}| \boldsymbol{V} \end{array}$
式(11)动量方程描述了多孔介质中相对完整的流动情况,充分涵盖了惯性和加速度修正、Forchheimer修正以及Brinkman修正下的达西定律。
相较于颗粒运移沉积理论分析,数值模拟方法更能准确地描述颗粒运移沉积物理机理。微观模拟多孔介质中颗粒流动也经历了构建简化几何形态、介观方法、LB-DEM(lattice Boltzmann-discrete element method)、CFD-DEM(computational fluid dynamics-discrete element method)方法等阶段的发展,逐渐成为微观分析颗粒流动的主要手段。流体、颗粒和孔隙内壁结构的相互作用调节着颗粒在多孔介质中的运动。产生了孔隙结构尺度的复杂性和流体经过孔隙与颗粒碰撞所产生的复杂性行为。利用数值模拟进行微观的验证,可以在模拟结果的基础上,建立宏观参数经验公式来指导室内实验研究。
颗粒流经内有障碍物通道的研究是简易化模拟微观多孔介质孔隙内流体流动、颗粒运移沉积问题的方法之一。Brandon等[49]模拟了矩形通道中方柱上颗粒的沉积问题,雷诺数介于200~2 000,发现有20%的颗粒被方柱阻挡沉积,雷诺数对颗粒沉积量的影响较小,但对颗粒的分散和分布影响较大。Jafair等[50]用格子玻尔兹曼方法(LBM)研究了雷诺数为120和200时二维流体流经障碍物时颗粒在方柱上的扩散沉积现象,主要受到阻力、浮力和布朗运动的影响,发现当颗粒粒径小于0.1 μm时,布朗力对颗粒沉积速率的影响较大,此时颗粒在通道内的运动分布更均匀。在不考虑布朗力作用下,改变颗粒经过时障碍物的横纵比,发现横纵比对颗粒沉积变化不明显[51]
对颗粒进行受力分析时,流场是潜在不可忽略的因素之一。Kim等[52]模拟了颗粒在多孔介质孔隙尺度的传输和渗透,利用多重网格有限元差分法和嵌入式边界技术构建颗粒-流体耦合模型并求解了斯托克斯方程,发现颗粒的捕集效率与Stokes沉降速度有关。曾琦等[53]通过建立不同堆积方式的模型来分析流场对颗粒沉积的影响,指出交错堆积方式对流体阻力影响显著,毛细管状模型则可忽略不计。
介观模拟技术为处理涉及多个物理领域和尺度的复杂流体流动问题提供了巨大优势和前景。Biggs等[54]提出了一种基于格子气自动机(lattice gas automaton,LGA)的显示数值模拟(explicit numerical simulation,ENS)方法,通过对多孔介质中固/液悬浮液的沉积流动的研究,发现沉积颗粒之间的影响是相互的,并且沉积颗粒也制约着沉积颗粒运动轨迹的预测。Chen等[55]利用LGA方法分析了多孔介质内的流动问题,已成功地纳入了边界条件,并建立了二维和三维动态模型。耗散粒子动力学(dissipative particle dynamics,DPD)模型[56]中验证了胶体在多孔介质中的流固耦合作用,发现胶体旋转运动导致接触效率改变并且接触效率与流量和胶体浓度有关。平滑粒子流体力学(smoothed particle hydrodynamics,SPH)方法是从微观孔隙角度对各向同性的孔隙构造的研究,了解到了多孔介质内部的流动特性[57-58]
液固两相流问题体现在颗粒与颗粒、颗粒与流体或多孔介质的孔隙壁发生碰撞上,相较于单相流问题,其运动特性更加复杂。多孔介质的局部微观结构可以使用传统的CFD方法进行模拟验证。然而,由于采用复杂的网格计算方程并描述颗粒边界条件,从而导致固体网格数量大幅度增加,使得CFD方法的计算复杂性增加。相比之下,使用格子Boltzmann方法具有多个独特优点,比如在并行计算方面表现出色、计算效率高以及易于处理复杂的固体边界条件等[59-60]
Ladd[61]利用有限体积颗粒的格子Boltzmann方法来解决液固两相流问题。之后又提出一种增强的格子Boltzmann方法[56,62],主要探究多孔介质内部复杂基质对于流体和其本身特性的影响。同时Pazdniakou等[63]采用格子Boltzmann方法研究了多孔介质的动态透水率,并模拟了周期性多孔介质中的振荡流动现象。模拟结果显示,泊松流动与理论预测值之间达到了良好的一致性。Mou等[64]采用浸没边界耦合格子Boltzmann方法,引入多孔介质弹簧系数K来考虑变形的影响,发现孔隙率随变形量的增大而减小,同时发现变形量越大,K和雷诺数(Re)越大,流动阻力越小。对于黏性流动问题,则利用固液两相的格子Boltzmann方法对细粒流动进行了验证,基于传统数值模型之上提出了细颗粒引起表观渗透率降低的统一模型[65],此外也重点研究了流体与颗粒在多孔介质中的相互作用,并将模拟结果与理论分析、经验公式以及实验数据进行了相互验证[56,66]
与其他方法相比,格子Boltzmann方法提供了详细的粒子轨迹和机械特性信息。这种方法为深入理解多孔介质中的液固流动提供了基础,为了解颗粒和流体在这种介质中行为提供了一个有效的框架。多孔介质具有两个关键特性,即孔隙度和渗透性。当颗粒穿过多孔介质时,流体阻力和应变的存在会导致孔隙率和渗透率下降[56]。所以掌握颗粒在多孔介质中的微观传输和沉积力学是十分有用的,可以帮助预测颗粒阻塞情况并指导工程剖面的调整。
DEM即离散单元方法,逐渐成为非连续性介质数值模拟的主要方法,并广泛应用于颗粒运移沉积和岩石裂缝渗流等领域[67-69]。利用DEM法,进行了关于小颗粒通过大颗粒周期性松散堆积的渗透过程的模拟。结果显示多孔介质的典型特征很大程度上取决于颗粒粒径的均匀周期性堆积[70]。此外,当小颗粒的平均速度和垂直速度均为常数时,颗粒速度会达到稳态。
Feng等[71]创建了流体颗粒边界相互作用模型,DEM和LBM(LB-DEM)的组合实现了固体颗粒和流体之间的二维耦合,可以对固体颗粒周围的流场进行微观的刻画。Parvan等[72]采用格子Boltzmann方法模拟流体流动,颗粒运动采用DEM法模拟,提出了基于颗粒表面速度变化颗粒沉积位置预测的方法,发现渗透率在临界孔隙率趋向于0,每个域的临界孔隙率不同。LBM-DEM方法分析了颗粒在多孔介质中的运移和沉积对孔隙率和渗透性的影响,同时也为非均质油层的调剖堵水提供了借鉴[73]。该方法也用于研究多孔介质中微球颗粒的运移情况,液相模拟利用LBM,固体颗粒接触则用DEM,二者的耦合作用则通过浸没移动边界(immersed moving boundary,IBM)[74]。此外,利用LBM-DEM-IBM模拟方法,可以分析颗粒粒径、流体速度等参数对于颗粒在多孔介质中沉积所带来堵塞程度的大小[70,75]。LBM-DEM方法与传统的CFD方法相比,其计算复杂度减少了一个数量级。不过,在处理大量固体颗粒时,该方法的计算效率仍有改进空间。
早期,处理颗粒在多孔介质中的运移问题大多采用孔隙网络方法和毛细管数概念。近年来,利用新型数值模拟技术和颗粒骨架孔隙模型研究颗粒在多孔介质中的输运和沉积过程在研究中发生了显著变化。实际上多孔介质的几何结构与颗粒骨架孔隙模型极为相似,因此这种模拟方法可用于研究颗粒与流体之间的相互作用。利用颗粒流构建颗粒骨架模型是常用方法之一。因其涉及复杂多孔介质空间模型和复杂孔隙的生成问题,粒子生成算法受到越来越多的关注;一些经典的粒子生成技术包括扩展容器法、粒子还原法、随机生成法和漏斗生成法。虽然随机生成法生成粒子的效率更高,但粒子之间有很大的孔隙。而其余方法则对力学计算要求比较高,如离散元计算(DEM)和不连续变形分析法(discontinuous deformation analysis,DDA),生成的颗粒充实率较高,但生成过程耗时较长,导致颗粒的生成效率较低[76]。Feng等[76]提出了一种用于创建二维圆形粒子的算法,将粒子的形成看作一个几何问题,粒子的合成率相对较高。在二维前向曲面方法的基础上,耿庆东[77]引入了三维方法,并给出了粒子生成的精确执行步骤,形成了一种在三维区域内生成粒子的有效算法。
为了解决DEM存在的计算效率低的问题,采用CFD-DEM方法受到青睐,利用CFD技术处理流体问题,利用DEM技术处理颗粒问题,并同时考虑颗粒与流体之间的相互作用关系,较好地提升了耦合效率[67,78-79]。伴随着数值模拟技术的发展,PFC-CFD方法逐渐成为处理耦合问题的主要手段之一。颗粒基于PFC软件的DEM更新计算时步,CFD模拟流体流动二者借助半经验公式构建耦合模型,发现该方法可以从低雷诺数到高雷诺数大范围的进行流固耦合的模拟,而且无须刻画颗粒边界,较大地提升了计算效率。通过在DEM和CFD之间交换拖拽力和浮力之间的相互作用力来考虑颗粒与流体之间的耦合作用,发现流体主要存在于结构均匀的多孔介质内,同时颗粒间的滚动阻力会导致单尺寸较大的相对压力下降[80-81]
任石磊等[82]利用自主开发的三维CFD-DEM软件,研究了颗粒在多孔介质中堆积时的流场情况,计算并分析了多孔介质的惯性阻力系数和黏性阻力系数,结果与CFD验证一致。同样利用该方法分析不同流动速度下粗颗粒的流动特性后,发现粗颗粒流动对管道内颗粒的流动状态和颗粒的平均浓度分布影响较大,当颗粒发生堆积时,沉降速度达到最高点[83]。Ji等[84]也研究了颗粒运动轨迹和近壁流场问题,通过相互作用力和含气率实现二者之间数据交互,发现颗粒轨迹在中心区域速度最低,而且低黏度流体更容易实现均匀接触效果。
颗粒的固态特征对其沉积效果作用明显。借助CFD-DEM耦合方法对大粒径颗粒的运移规律进行了验证[67,85]。结果表明在等体积下形状不同的颗粒被携带的难易程度:球状➝片状➝立方体形(由易到难);颗粒对井壁的冲击程度:立方体形➝片状➝球状(由大到小)。陈先超等[86]建立了骨架颗粒流固耦合孔隙网络的模型,发现小粒径的颗粒运移更深,更分散,对地层渗透率影响较大;高孔隙率下,渗透率下降更为急剧。Wang等[87]采用CFD-DEM方法模拟了颗粒在多孔介质中的流动行为,结果表明:随孔隙率增大,颗粒停留的时间先大后小,颗粒温度则相反;随着液体流速的增加,颗粒温度和接触力增加,颗粒的停留时间减少。
综合运用3种分析方法,研究了颗粒在多孔介质中运移沉积的影响因素,包括颗粒粒径、孔隙结构和渗流条件。同时,对简化几何模拟方法、介观方法、LB-DEM方法和CFD-DEM方法等进行了详细机理分析,为多孔介质中的调剖堵水和提高原油采收率提供了理论依据,并为颗粒在多孔介质中的研究提供了参考。主要结论如下。
(1)颗粒粒径不同迁移时,所受力差异较大;颗粒临界浓度较大时,易发生封堵;dp/Dp决定颗粒的沉积位置。
(2)多孔介质中渗流模型形式多样,其中Brinkman-Forchheimer-Darcy模型最全面,适用于各种流动模型。颗粒的滞留量与渗流速度、方向相关。
(3) CFD-DEM方法从微观角度刻画了颗粒堆积和流场变化的流固耦合模型,并对介质内的复杂流场和力学行为进行了验证。
(1)颗粒迁移沉积受到许多影响因素的影响,包括生物因素、化学因素、pH、孔隙结构特征和颗粒大小等。目前的研究大多只从单一角度分析某种因素的影响,而缺乏多因素综合研究,这样无法准确反映真实多孔介质地层的情况。因此,未来需要更多考虑多因素,并进行定量分析关键变量。
(2) 实验研究中常采用圆柱填充多孔介质模型,但这会导致壁面效应的产生。为了更真实地验证地层多孔介质内的稳定渗流,有必要验证存在壁面效应的流动稳定性。此外,在真实地层条件下,裂缝是不可避免存在的,颗粒也会沉积在裂缝中。因此,研究存在壁面效应和裂缝的多孔介质段的流体稳定性和数学模型建立也是未来研究的重要方向。
(3) 微观尺度下,需要从线性渗流理论发展到物理化学、非牛顿、多尺度的非线性渗流理论,对多孔介质内的流固耦合进行理论研究和数值模拟。由于多孔介质内的孔隙结构复杂且大多为纳米级别,流体在多孔介质中的运动易受到界面和微观力的影响。因此,未来的研究应聚焦在微观力学和渗流力学方面,深入研究多孔介质中微观运移特征的特性。
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2025年第25卷第5期
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doi: 10.12404/j.issn.1671-1815.2402157
  • 接收时间:2024-03-26
  • 首发时间:2025-07-29
  • 出版时间:2025-02-18
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  • 收稿日期:2024-03-26
  • 修回日期:2024-11-18
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辽宁省教育厅基于改性膨润土智能钻井液研制及评价重点项目(LJKZ0417)
辽宁省教育厅科学研究经费项目(LJKZ0372)
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    辽宁石油化工大学石油天然气工程学院, 抚顺 113001

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*闫治君(1997—),男,汉族,河南商丘人,硕士研究生。研究方向:油藏数值模拟。E-mail:
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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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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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