Article(id=1274300093999112441, tenantId=1146029695717560320, journalId=1272208980697911299, issueId=1274300092707266809, articleNumber=null, orderNo=null, doi=10.3724/1000-6915.jrme.2025.0505, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752681600000, receivedDateStr=2025-07-17, revisedDate=1760284800000, revisedDateStr=2025-10-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1781746417759, onlineDateStr=2026-06-18, pubDate=1769875200000, pubDateStr=2026-02-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1781746417759, onlineIssueDateStr=2026-06-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1781746417759, creator=13701087609, updateTime=1781746417759, updator=13701087609, issue=Issue{id=1274300092707266809, tenantId=1146029695717560320, journalId=1272208980697911299, year='2026', volume='45', issue='2', pageStart='321', pageEnd='638', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1781746417452, creator=13701087609, updateTime=1781746463571, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1274300286466335306, tenantId=1146029695717560320, journalId=1272208980697911299, issueId=1274300092707266809, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1274300286466335307, tenantId=1146029695717560320, journalId=1272208980697911299, issueId=1274300092707266809, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=432, endPage=448, ext={EN=ArticleExt(id=1274300094259159291, articleId=1274300093999112441, tenantId=1146029695717560320, journalId=1272208980697911299, language=EN, title=Model interpretation of the multi-stage evolution characteristics of shale permeability during the injection of CO2, columnId=null, journalTitle=Chinese Journal of Rock Mechanics and Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Accurately predicting the dynamic evolution of permeability during CO2 injection into shale reservoirs is crucial for carbon sequestration and enhanced shale gas recovery. However, traditional permeability models often fail to comprehensively describe the full-range evolution of permeability throughout the entire CO2 injection process in shale—from the low-pressure gaseous state to the supercritical state. To address this limitation, this study develops a shale permeability evolution model based on a dual-elastic system comprising both the matrix and fractures, determined by component permeability weighting. By incorporating key factors such as mechanical degradation of the matrix, secondary adsorption, and strain hysteresis effects, we establish a governing equation for permeability evolution under multi-effect coupling. Utilizing an overlapping dual-elastic medium structure, we perform parallel cross-coupling numerical solutions, achieving an accurate representation of the nonlinear permeability evolution during full-pressure CO2 injection. Furthermore, a decoupled analysis of influencing effects reveals that the degradation of mechanical parameters of the matrix material due to CO2 defines the boundary thresholds for permeability fluctuation ranges. The asynchronous response between mechanical strain and adsorption strain significantly amplifies differences across evolutionary stages, leading to clearly distinguishable phase transitions. Additionally, the strain hysteresis effect prolongs the duration of evolution. Gas adsorption and mechanical responses jointly regulate the transition points between evolutionary stages, with the secondary adsorption-induced swelling strain particularly enhancing phase differentiation throughout the evolution process. This study also provides an in-depth analysis of the fundamental framework of fluid-solid coupled permeability modeling and explores the characteristics of different numerical simulation methods. The findings not only deepen the understanding of shale permeability evolution during CO2 injection but also offer valuable insights for theoretical modeling and numerical simulation of permeability in geological fluid sequestration.

, correspAuthors=Dengke WANG, authorNote=null, correspAuthorsNote=
* WANG Dengke (1980–), professor, is engaged in research work in safety science and engineering. E-mail:
, 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=Wenrui LI, Dengke WANG, Jianping WEI, Jinhao YU, Wenlin ZHAO, Zhihui WEN), CN=ArticleExt(id=1274300099254575384, articleId=1274300093999112441, tenantId=1146029695717560320, journalId=1272208980697911299, language=CN, title=页岩注入CO2渗透率多阶段演化特性的模型解析, columnId=1274300094359822588, journalTitle=岩石力学与工程学报, columnName=理论与试验研究, runingTitle=null, highlight=null, articleAbstract=

精准预测CO2注入页岩储层的渗透率动态演化规律对于碳封存和增强页岩气开采具有重要意义。针对传统渗透率模型难以准确描述CO2由低压气态到超临界态全压注入页岩过程中的渗透率全过程演化问题,基于基质–裂隙双弹性介质系统,构建由组分渗透率权重决定的页岩渗透率演化模型;通过引入基质力学劣化、二次吸附,以及应变滞后效应等关键因素,建立起多效应耦合控制的渗透率演化方程。基于双弹性介质体重叠结构开展并行交叉耦合数值求解,实现对CO2全压注入过程中页岩渗透率非线性演化过程的准确描述。进一步,影响效应解耦研究结果表明:CO2对基质材料力学参数的劣化界定渗透率波动范围的边界阈值,机械应变与吸附应变之间的非同步响应显著放大演化阶段差异,形成具有显著辨识度的阶段转换过程;应变滞后效应则显著延长演化时间跨度;气体吸附作用与力学响应共同调控各演化阶段的转变节点,尤其是二次吸附引发的额外膨胀应变明显增强了演化过程中的阶段划分程度。此外,本研究还深入分析流–固耦合渗透率建模基本框架和不同数值模拟方法的特性,不仅可以加深对CO2注入过程中页岩渗透率演化过程的理解,还为流体地质封存渗透率理论建模及数值模拟方法提供借鉴意义。

, correspAuthors=王登科, authorNote=null, correspAuthorsNote=
* 王登科(1980–),现任教授,主要从事安全科学与工程方面的研究工作。E-mail:
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LI Wenrui (1994–), assistant professor, is engaged in research on unconventional natural gas development and carbon dioxide geological storage. E-mail:

李文睿(1994–),现任讲师,主要从事非常规天然气开发及二氧化碳地质封存方面的研究工作。E-mail:

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2.State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo, Henan 454000, China
3.Key Laboratory of Coal Mine Disasters Prevention, Henan Polytechnic University, Jiaozuo, Henan 454000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1274368944395854343, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, authorId=1274368943171117568, language=CN, stringName=李文睿, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 3, address=1.河南理工大学 安全科学工程学院,河南 焦作 454000
2.河南理工大学 河南省瓦斯地质与瓦斯治理重点实验室–省部共建国家重点实验室培育基地,河南 焦作 454000
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LI Wenrui (1994–), assistant professor, is engaged in research on unconventional natural gas development and carbon dioxide geological storage. E-mail:

李文睿(1994–),现任讲师,主要从事非常规天然气开发及二氧化碳地质封存方面的研究工作。E-mail:

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LI Wenrui (1994–), assistant professor, is engaged in research on unconventional natural gas development and carbon dioxide geological storage. E-mail:

李文睿(1994–),现任讲师,主要从事非常规天然气开发及二氧化碳地质封存方面的研究工作。E-mail:

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2.State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo, Henan 454000, China
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articleId=1274300093999112441, language=CN, label=Fig.13, caption=Temporal evolution of permeability,volumetric strain,and displacement gradient under decoupled strain hysteresis effect, figureFileSmall=Sa8tt51jo9BhiDd+zp1gWA==, figureFileBig=dZt1wKcVrn7S5Nlx4ZzuqQ==, tableContent=null), ArticleFig(id=1274368975781831260, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Parameter pL1m/MPa pL2m/MPa εL1m/% εL2m/% εLf/% pc/MPa
Value range1~2.3[28]4~7[28]0.08~0.12[27]0.12~0.20.04~0.087.2~8.0
Value260.080.120.047.4
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Basis for parameter selection in numerical simulation

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Parameter pL1m/MPa pL2m/MPa εL1m/% εL2m/% εLf/% pc/MPa
Value range1~2.3[28]4~7[28]0.08~0.12[27]0.12~0.20.04~0.087.2~8.0
Value260.080.120.047.4
), ArticleFig(id=1274368976624886366, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
ParameterDegree of deterioration/%Literature sources
Young's modulus-24.60~26.79
-29.28~33.15
-20.23~37.39
Q. Lyu et al.[18]
H. Yin et al.[31]
Q. Lyu et al.[33]
Poisson's ratio29.41~58.82Q. Lyu et al.[33]
), ArticleFig(id=1274368977014956639, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=CN, label=Table 2, caption=

Degradation of mechanical parameters measured in the experiment

, figureFileSmall=null, figureFileBig=null, tableContent=
ParameterDegree of deterioration/%Literature sources
Young's modulus-24.60~26.79
-29.28~33.15
-20.23~37.39
Q. Lyu et al.[18]
H. Yin et al.[31]
Q. Lyu et al.[33]
Poisson's ratio29.41~58.82Q. Lyu et al.[33]
), ArticleFig(id=1274368977103037024, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Experiment typeEnvironment temperature T/KInitial porosity of matrix ϕm0Initial porosity of fracture ϕf0Maximum adsorption capacity of matrix partnmaxm/(m3·kg)Maximum adsorption capacity of fracture part nmaxf/(m3·kg)Poisson's ratio νYoung's modulus of matrix part Em/GPaYoung's modulus of fracture part Ef/GPa
N2 group[45]298.150.040.040.0150.005 00.1552
CO2 group[44]313.000.050.050.0800.008 70.2586
Supercritical CO2 group[8]320.000.040.040.0300.015 00.25108
Experiment typeBiot coefficient of matrix αBiot coefficient of fracture βInitial permeability of matrixi km0/m2Initial permeability of fracture kf0/m2Langmuir strain constant of matrix part εLm/%Langmuir strain constant of fracture part εLf/%Langmuir pressure constant of fracture part pLf/MPaLangmuir pressure constant of matrix part pLm/MPa
N2 group[45]0.300.603×10-181×10-170.40.242
CO2 group[44]0.650.851×10-191×10-170.80.482
Supercritical CO2 group[8]0.700.905×10-191×10-17 0.4(εL1m)  1.2(εL2m) 0.4(εLf) 4(pLf) 2(pL1m)  8(pL2m)
), ArticleFig(id=1274368977916732001, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=CN, label=Table 3, caption=

Modeling parameters for the cases of shale during N2/CO2 injection

, figureFileSmall=null, figureFileBig=null, tableContent=
Experiment typeEnvironment temperature T/KInitial porosity of matrix ϕm0Initial porosity of fracture ϕf0Maximum adsorption capacity of matrix partnmaxm/(m3·kg)Maximum adsorption capacity of fracture part nmaxf/(m3·kg)Poisson's ratio νYoung's modulus of matrix part Em/GPaYoung's modulus of fracture part Ef/GPa
N2 group[45]298.150.040.040.0150.005 00.1552
CO2 group[44]313.000.050.050.0800.008 70.2586
Supercritical CO2 group[8]320.000.040.040.0300.015 00.25108
Experiment typeBiot coefficient of matrix αBiot coefficient of fracture βInitial permeability of matrixi km0/m2Initial permeability of fracture kf0/m2Langmuir strain constant of matrix part εLm/%Langmuir strain constant of fracture part εLf/%Langmuir pressure constant of fracture part pLf/MPaLangmuir pressure constant of matrix part pLm/MPa
N2 group[45]0.300.603×10-181×10-170.40.242
CO2 group[44]0.650.851×10-191×10-170.80.482
Supercritical CO2 group[8]0.700.905×10-191×10-17 0.4(εL1m)  1.2(εL2m) 0.4(εLf) 4(pLf) 2(pL1m)  8(pL2m)
), ArticleFig(id=1274368978373911138, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Initial porosity of matrix ϕmoInitial porosity of fracture ϕfoMaximum adsorption capacity of matrix part nmaxm/(m3·kg)Maximum adsorption capacity of fracture part nmaxf/(m3·kg)Biot coefficient of matrix αBiot coefficient of fracture βInitial permeability of matrix part km0/m2Initial permeability of fracture part kf0/m2Sensitivity exponent MInjected target pressure pin/MPa
0.040.040.120.050.650.85×10-191×10-18314
), ArticleFig(id=1274368979120497251, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=CN, label=Table 4, caption=

Common input parameters for four cases

, figureFileSmall=null, figureFileBig=null, tableContent=
Initial porosity of matrix ϕmoInitial porosity of fracture ϕfoMaximum adsorption capacity of matrix part nmaxm/(m3·kg)Maximum adsorption capacity of fracture part nmaxf/(m3·kg)Biot coefficient of matrix αBiot coefficient of fracture βInitial permeability of matrix part km0/m2Initial permeability of fracture part kf0/m2Sensitivity exponent MInjected target pressure pin/MPa
0.040.040.120.050.650.85×10-191×10-18314
), ArticleFig(id=1274368979514761828, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Basic expression of modelParameter interpretationLiterature sources
kk0=exp(3CfΔσαbiotΔp) Δσis the stress change;Cfis the fracture compression coefficient,1/MPaJ. Q. Shi and S. Durucan[49]
kk0=(1+αbiotϕ0Δεe)3f(Kn) Δεeis the effective strain change,f(Kn)is the slip correction coefficient related to the Knudsen numberM. Y. Wei et al.[50]
kk0=exp[3(1K1Kf)(ΔσΔp)+Δεlfs](ll0)2f(Kn)f(Kn0)L is the fracture length;εlfsis the fracture strain determined by the volume fraction of adsorbed gas invading the shale, gas diffusion coefficient, and diffusion distance, defined as a piecewise functionJ. Zeng et al.[51]
kk0={exp(3CfΔσe)          (Elastic stage)exp(3DλDCfΔσe)   (Plastic stage) Δσeis the effective stress change;λDis the influence coefficient of rock damage on permeability;Dis the damage coefficient, defined as a piecewise function based on tensile and shear strainsC. Y. Wang et al.[52]
kk0=(ϕϕ0)3exp(αkD) αkis the fitted value of the influence coefficient of rock mass damage on permeabilityW. C. Zhu et al.[47]
kk0=(ϕϕ0)M+1exp(ηz0ηz)M is the stress sensitivity constant obtained from experimental fitting,z is the initial coordination number of pores and fractures,andηis a constant related to the fractal dimension and M.D. Davudov and R. G. Moghanloo[41]
), ArticleFig(id=1274368979619619429, tenantId=1146029695717560320, journalId=1272208980697911299, articleId=1274300093999112441, language=CN, label=Table 5, caption=

Basic model expression for fluid-solid coupling permeability

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Basic expression of modelParameter interpretationLiterature sources
kk0=exp(3CfΔσαbiotΔp) Δσis the stress change;Cfis the fracture compression coefficient,1/MPaJ. Q. Shi and S. Durucan[49]
kk0=(1+αbiotϕ0Δεe)3f(Kn) Δεeis the effective strain change,f(Kn)is the slip correction coefficient related to the Knudsen numberM. Y. Wei et al.[50]
kk0=exp[3(1K1Kf)(ΔσΔp)+Δεlfs](ll0)2f(Kn)f(Kn0)L is the fracture length;εlfsis the fracture strain determined by the volume fraction of adsorbed gas invading the shale, gas diffusion coefficient, and diffusion distance, defined as a piecewise functionJ. Zeng et al.[51]
kk0={exp(3CfΔσe)          (Elastic stage)exp(3DλDCfΔσe)   (Plastic stage) Δσeis the effective stress change;λDis the influence coefficient of rock damage on permeability;Dis the damage coefficient, defined as a piecewise function based on tensile and shear strainsC. Y. Wang et al.[52]
kk0=(ϕϕ0)3exp(αkD) αkis the fitted value of the influence coefficient of rock mass damage on permeabilityW. C. Zhu et al.[47]
kk0=(ϕϕ0)M+1exp(ηz0ηz)M is the stress sensitivity constant obtained from experimental fitting,z is the initial coordination number of pores and fractures,andηis a constant related to the fractal dimension and M.D. Davudov and R. G. Moghanloo[41]
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页岩注入CO2渗透率多阶段演化特性的模型解析
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李文睿 1, 2, 3 , 王登科 1, 2, 3, * , 魏建平 1, 2, 3 , 余金昊 1, 2 , 赵文霖 1, 2 , 温志辉 1, 2, 3
岩石力学与工程学报 | 理论与试验研究 2026,45(2): 432-448
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岩石力学与工程学报 | 理论与试验研究 2026, 45(2): 432-448
页岩注入CO2渗透率多阶段演化特性的模型解析
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李文睿1, 2, 3 , 王登科1, 2, 3, * , 魏建平1, 2, 3, 余金昊1, 2, 赵文霖1, 2, 温志辉1, 2, 3
作者信息
  • 1.河南理工大学 安全科学工程学院,河南 焦作 454000
  • 2.河南理工大学 河南省瓦斯地质与瓦斯治理重点实验室–省部共建国家重点实验室培育基地,河南 焦作 454000
  • 3.河南理工大学 煤矿瓦斯灾害防治应急管理部重点实验室,河南 焦作 454000
  • LI Wenrui (1994–), assistant professor, is engaged in research on unconventional natural gas development and carbon dioxide geological storage. E-mail:

    李文睿(1994–),现任讲师,主要从事非常规天然气开发及二氧化碳地质封存方面的研究工作。E-mail:

通讯作者:

* 王登科(1980–),现任教授,主要从事安全科学与工程方面的研究工作。E-mail:
Model interpretation of the multi-stage evolution characteristics of shale permeability during the injection of CO2
Wenrui LI1, 2, 3 , Dengke WANG1, 2, 3, * , Jianping WEI1, 2, 3, Jinhao YU1, 2, Wenlin ZHAO1, 2, Zhihui WEN1, 2, 3
Affiliations
  • 1.School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo, Henan 454000, China
  • 2.State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo, Henan 454000, China
  • 3.Key Laboratory of Coal Mine Disasters Prevention, Henan Polytechnic University, Jiaozuo, Henan 454000, China
出版时间: 2026-02-01 doi: 10.3724/1000-6915.jrme.2025.0505
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精准预测CO2注入页岩储层的渗透率动态演化规律对于碳封存和增强页岩气开采具有重要意义。针对传统渗透率模型难以准确描述CO2由低压气态到超临界态全压注入页岩过程中的渗透率全过程演化问题,基于基质–裂隙双弹性介质系统,构建由组分渗透率权重决定的页岩渗透率演化模型;通过引入基质力学劣化、二次吸附,以及应变滞后效应等关键因素,建立起多效应耦合控制的渗透率演化方程。基于双弹性介质体重叠结构开展并行交叉耦合数值求解,实现对CO2全压注入过程中页岩渗透率非线性演化过程的准确描述。进一步,影响效应解耦研究结果表明:CO2对基质材料力学参数的劣化界定渗透率波动范围的边界阈值,机械应变与吸附应变之间的非同步响应显著放大演化阶段差异,形成具有显著辨识度的阶段转换过程;应变滞后效应则显著延长演化时间跨度;气体吸附作用与力学响应共同调控各演化阶段的转变节点,尤其是二次吸附引发的额外膨胀应变明显增强了演化过程中的阶段划分程度。此外,本研究还深入分析流–固耦合渗透率建模基本框架和不同数值模拟方法的特性,不仅可以加深对CO2注入过程中页岩渗透率演化过程的理解,还为流体地质封存渗透率理论建模及数值模拟方法提供借鉴意义。

岩石力学  /  碳封存  /  页岩  /  渗透率演化  /  超临界态  /  二次吸附

Accurately predicting the dynamic evolution of permeability during CO2 injection into shale reservoirs is crucial for carbon sequestration and enhanced shale gas recovery. However, traditional permeability models often fail to comprehensively describe the full-range evolution of permeability throughout the entire CO2 injection process in shale—from the low-pressure gaseous state to the supercritical state. To address this limitation, this study develops a shale permeability evolution model based on a dual-elastic system comprising both the matrix and fractures, determined by component permeability weighting. By incorporating key factors such as mechanical degradation of the matrix, secondary adsorption, and strain hysteresis effects, we establish a governing equation for permeability evolution under multi-effect coupling. Utilizing an overlapping dual-elastic medium structure, we perform parallel cross-coupling numerical solutions, achieving an accurate representation of the nonlinear permeability evolution during full-pressure CO2 injection. Furthermore, a decoupled analysis of influencing effects reveals that the degradation of mechanical parameters of the matrix material due to CO2 defines the boundary thresholds for permeability fluctuation ranges. The asynchronous response between mechanical strain and adsorption strain significantly amplifies differences across evolutionary stages, leading to clearly distinguishable phase transitions. Additionally, the strain hysteresis effect prolongs the duration of evolution. Gas adsorption and mechanical responses jointly regulate the transition points between evolutionary stages, with the secondary adsorption-induced swelling strain particularly enhancing phase differentiation throughout the evolution process. This study also provides an in-depth analysis of the fundamental framework of fluid-solid coupled permeability modeling and explores the characteristics of different numerical simulation methods. The findings not only deepen the understanding of shale permeability evolution during CO2 injection but also offer valuable insights for theoretical modeling and numerical simulation of permeability in geological fluid sequestration.

rock mechanics  /  carbon sequestration  /  shale  /  permeability evolution  /  supercritical state  /  secondary adsorption
李文睿, 王登科, 魏建平, 余金昊, 赵文霖, 温志辉. 页岩注入CO2渗透率多阶段演化特性的模型解析. 岩石力学与工程学报, 2026 , 45 (2) : 432 -448 . DOI: 10.3724/1000-6915.jrme.2025.0505
Wenrui LI, Dengke WANG, Jianping WEI, Jinhao YU, Wenlin ZHAO, Zhihui WEN. Model interpretation of the multi-stage evolution characteristics of shale permeability during the injection of CO2[J]. Chinese Journal of Rock Mechanics and Engineering, 2026 , 45 (2) : 432 -448 . DOI: 10.3724/1000-6915.jrme.2025.0505
页岩渗透率演化的精准预测是评估储层封存性能和强化页岩气开采的关键科学问题[1]。向深部储层中注入气体的过程,可将其抽象为恒定围压(constant confining pressure,CCP)边界条件模型,众多室内物理模拟试验围绕于此展开试验研究。稳态法测试渗透率结果表明,氮气、甲烷和CO2等吸附性气体注入,页岩渗透率普遍呈现“U型”演化特征,控制其演化的核心机制可归纳为:(1)孔隙压力驱动的有效应力重分布;(2)气体吸附引发的基质–裂隙变形竞争;(3)化学腐蚀导致的力学性质劣化;(4)气体多机制传输效应[2-3]。理想状态下,页岩渗透率演化范围上限由有效应力控制的多孔弹性变形决定,下限则由滑脱效应决定[4-6],有效应力和滑脱效应的共同作用划定了实际渗透率演化区间[7]。随着研究不断深入,发现存在相态转化的CO2注入,页岩渗透率呈现出多阶段演化特征,非简单的“U型”演化规律[8]
为深入揭示页岩渗透率演化规律,最初理论模型将页岩渗透率直接视为裂隙渗透率,由于忽略了基质–裂隙相互作用,导致模型计算结果与试验数据不完全匹配[9]。实际上,基质–裂隙相互作用受整体变形和裂隙开度变化共同控制[10]。基于这一认知,学者们引入了应变分配模型,用来区分吸附应变对基质膨胀和裂隙开度的独立影响,数学定义了应变分割系数[11]、内部膨胀因子[12]和气体非平衡因子[13]。研究结果表明,引入应变分配概念的双重孔隙介质渗透率模型,能很好地解释常围压条件下,渗透率上、下限包络区间内存在的不同“U型”演化趋势。W. X. Cheng等[14]还提出了一个多层纳米壳模型,通过模拟气体吸附过程中纳米管壁和基质外壳的竞争变形作用,发现了“U型”渗透率后期回弹不明显的特异性情况。然而,在全压CO2注入范围(低压气态到高压超临界态)内,CO2–页岩相互作用易导致矿物溶解、孔隙结构变化和基质力学性质劣化等现象[15-18],强扩散性超临界CO2尤其对微孔结构损伤明显[19]。此外,气楔效应驱动裂隙网络扩展形成优势渗流通道,诱发岩体局部应力集中与弱面损伤演化,易导致渗透率出现突变特征[20]。试验研究发现,孔隙比表面积和孔隙率会因矿物溶解和碳酸盐形成有所增加;在超临界CO2相变增能与孔隙匹配的机制下,CO2分子吸附空间向微孔演化,进而通过多层吸附与微孔填充等途径,实现了吸附能力的再次强化[21]。L. Hou和D. Elsworth[8]将这种现象称之为“二次吸附”,并通过含相态转化的CO2注入试验,推断二次吸附及其诱发的间歇性膨胀应变正是导致渗透率出现异常演化现象的根本原因。
当前,无论是基于应变分配的渗透率模型[815]、定义局部非均匀应变的模型[14],还是强调杨氏模量衰减的双孔介质模型[22],虽都与“U型”渗透率试验数据吻合良好,但均无法合理解释全压CO2注入过程中页岩渗透率呈现出类“W型”的多阶段演化特征。S. W. Zhang等[23]认为,基质和裂隙都有其独立的渗透率演化特征,仅依靠裂隙渗透率演化来代表页岩渗透率演化,结果可能不准确。L. Fan和S. M. Liu[24]考虑到外骨架和吸附矿物的体积模量差异,提出了一个概念性的双材料模型,该模型很好地展示了气体吸附诱发的微结构非均匀变形。M. Y. Wei等[25-26]综合考虑吸附诱发的非均匀应变滞后效应构建了煤渗透率演化模型,该模型不但阐明了控制渗透率“U型”演化的主要机制,还从理论上阐述了注气初期渗透率短暂增大的现象,对于页岩渗透率建模具有一定的借鉴意义。
综上所述,传统渗透率模型无法准确描述页岩注入CO2过程中的渗透率非线性演化问题。本研究综合考虑基质–裂隙跨尺度流动、力学性质劣化、基质二次吸附膨胀应变,以及应变滞后效应等关键因素;构建了基质–裂隙平行竞争耦合渗透率演化模型,应用重叠连续介质数值模拟方法,揭示了全压CO2注入过程中的渗透率多阶段演化基本模式,并厘清了各阶段演化的主控机制,从而为页岩储层封存效率优化与渗流稳定性评估提供理论工具。
在页岩储层多物理场耦合分析中,本研究构建了裂隙–基质并联的双介质材料模型,其中,软质裂隙系统呈现低吸附性特征,而硬质基质系统具有强吸附性特征。如图1(a),(b)所示,该模型将页岩实体离散为分布式物理节点网络,每个节点均包含裂隙系统与基质系统的交互作用单元。
图1(c)所示,采用重叠连续介质方法,将每个物理节点解耦为4个数学节点,分别对应裂隙/基质变形方程、裂隙/基质体内流动方程,建立包含4个相互作用物理场的控制方程组,并通过3组交叉耦合关系实现全耦合求解:基质–裂隙界面处的局部力平衡条件、变形协调条件以及气体质量交换项。图1(d)为页岩岩心轴向剖面图,尺寸为5 cm×10 cm,pin为注气压力,pout为出口压力;pi为注气压力变量,下标i取m和f时分别表示基质系统和裂隙系统;pa为大气压力;p为孔隙压力;n为边界的单位法向量;u为位移向量;Ω指代几何边界,Ω1Ω4分别为下、左、右和上边界。
数值模拟在CCP条件下进行,CO2从顶部注入,左右两侧施加恒定外部应力限制变形,底部无流出,计算域内初始孔隙压力设定为0.1 MPa。
裂隙和基质系统中体积变形与气体流动的控制方程基于以下假设:(1)页岩由基质和裂隙连续介质材料组成,且均为孔隙介质弹性系统;(2)应变属于微应变;(3)计算域等温且气体完全饱和;(4)不考虑页岩的含水情况。
弹性介质的应变–位移满足如下基本关系:
εij=(uij+uji)/2
式中:εij为总应变张量,uijuji均为位移分量。
固体材料的应力平衡基本方程为
σijj+fi=0
式中:σijj为应力张量,fi为体积力。
基于多孔弹性线性本构关系,将体积应变分解为气体吸附应变与局部应变,并考虑基质–裂隙间压力差的相互作用,根据连续介质理论可定义页岩基质与裂缝的变形本构关系[23]分别为
εmij=σmij2Gm(16Gm19Km)σkkδij+         (αpmΔp3Km+εfs3)δij
εfij=σfij2Gf(16Gf19Kf)σkkδij+        (βpfΔp3Kf+εfs3)δij
式中:δij为克罗内克符号;εmijεfij分别为基质与裂隙吸附应变;Δp为基质内孔隙压力pm与裂隙内孔隙压力pf之差,Δp=pfpmKiGi分别为弹性体的体积模量和剪切模量,Ki=Ei/[3(12νi)]Gi=Ei/[2(1+νi)]Eiνi分别为杨氏模量和泊松比;αβ分别为基质和裂隙系统的Biot系数;σkk为弹性体所受的总应力,具有方向性。参数下标i为m和f,分别代表基质系统、裂隙系统。
联立式(1)~(4),分别得到如下所示基质和裂隙变形的纳维斯托克斯型方程:
Gmuikk+2Gm12νmukkiαpmiKmεmsi+Δpi+Fi=0
Gfuikk+2Gf12νfukkiβpfiKfεfsiΔpi+Fi=0
(1)全压力范围内CO2吸附及吸附应变
采用结合了吸附密度修正因子的超临界Dubinin- Astakhov(SDA)模型来量化全压范围内CO2吸附量变化,数学表达式[21]如下:
nex=nmaxexp{γ[ln(ρaρg)]2}(1ρgρa)
式中:nex为过剩吸附量(m3/kg),nmax为最大吸附量,(m3/kg),ρa为CO2真实密度(kg/m3),γ为特征能量和吸附势拟合常数。其中,nmaxexp{γ[ln(ρa/ρg)]2}为微孔填充吸附模型(SDA)的绝对吸附量nab1ρg/ρa为密度修正项。
将SDA模型分别应用于具有不同吸附特性的基质系统和裂隙系统,得到以下结果:
Gmuikk+2Gm12vmukkiαpmiKmεmsi+Δpi+Fi=0
Gfuikk+2Gf12νfukkiβpfiKfεfsiΔpi+Fi=0
在低压气态向超临界态高压等温注入过程中,CO2密度和动力黏度会发生阶跃性突变(见图2),本文采用内置Span-Wagner算法的REFPROP软件,联合COMSOL数值,分别计算基质系统和裂隙系统内的密度ρgmρgf
图2所示,CO2吸附应变可划分为气态区和超临界区2个阶段。S. Zhi等[27]试验研究表明,各自区域内的吸附应变均遵循Langmuir型函数:εs=εLp/(p+pL),式中,εs为吸附应变,εL为Langmuir应变常数,pL为Langmuir压力常数。因此,在数值模拟CO2全压注入过程中,基质系统和裂隙系统的吸附应变可表示为
εis={εL1i(pipi+pL1i)   (pipc)εL2i(pipi+pL2i)   (pcpi)
式中:pL1εL1i分别为气态阶段的Langmuir压力和应变常数;pL2εL2i分别为超临界阶段的Langmuir压力和应变常数;pc为CO2相变临界压力,也是力学参数出现显著劣化的特征压力值。鉴于基质和裂隙吸附能力差异特性,二次吸附应变仅发生于基质系统。因此,pL1mpL2mpL1f=pL2fεL1mεL2mεL1f=εL2f。为简化计算,裂隙Langmuir应变和压力分别统一改写为εLfpLf表1列出了数值模拟参数取值范围,作为后续数值模拟参数取值的依据。
(2)基质力学参数性能劣化
三轴加载条件下实施强吸附性气体注入,低渗煤试样复合损伤因子变化呈现出典型的3个阶段过程[29],如图3所示。倪红坚等[30]通过超临界态CO2浸泡页岩试验发现,宏观力学损伤变化与页岩复合损伤因子呈现的3个阶段过程相吻合。
假设页岩–CO2耦合过程中基质与岩体损伤程度一致,则弹性模量存在如下劣化过程[29]
Ei=E0(1D)
式中:D为参数的劣化损伤因子,取值0~1;EiE0分别为弹性模量参数的动态值和初始值。式(11)是弹性损伤理论里弹性模量变量的核心定义,即通过损伤变量D量化材料微缺陷累积,以及对弹性模量的线性衰减效应。在经过广泛试验验证后成为连接微观损伤机制与宏观性能的关键桥梁。
考虑到有限元数值模拟过程中连续介质不存在无限制性损伤,因此以渐进式线性损伤定义参数变化,Ei可设定为分段函数:
Ei={E0(pinpc)EsE0pdpc(ppc)+E0(pcpinpd)Es(pdpin)
式中:pc为CO2相变临界压力,也是力学参数出现显著劣化的特征压力值,pc= 7.4 MPa;pd为力学参数劣化达到稳定时的气体特征压力,pd= 12 MPa[31]E0为未发生损伤的初始弹性模量;Es为损伤稳定后的弹性模量。无论弹性模量是否变化,泊松比增加都会扩大渗透率波动范围[32]。因此,劣化泊松比也定义为
νi={ν0(pipc)νsν0pdpc(ppc)+ν0(pcpinpd)νs(pdpin)
式中:ν0为未发生损伤的初始泊松比,νs为损伤稳定后的泊松比。对于劣化参数的变化范围,笔者做了相应的数据收集,如表2所示。需要说明,pc为注入岩体气体达到压力平衡的目标值,而不是瞬态气压值。
Knudsen数作为页岩气滑脱流动和多种气体扩散机制的分类依据,其表达式为
Kni=KBTdi2πδ2pi
式中:Kni为Knudsen数;KB为Boltzmann常数,KB= 1.38×10-23 J/K;di为多孔介质本质渗透率ki和初始孔隙度ϕi0决定的等效水力直径,di=32ki/ϕi0T为储层温度(K);δ为分子直径(m);pi为孔隙压力(Pa)。
涵盖多尺度孔裂隙结构的页岩,在其等效水力直径d内存在气体的连续和非连续流动传输,两类流动控制方程可分别表示为
Jc=f(Kn)JDJdc=De(MCd)}
式中:Jc为气体连续流动通量;JD为达西流动通量;M为气体相对分子质量;Jdc为由时变有效扩散系数De控制的非连续流动质量通量,Cd为气体浓度(g/m3)。对于管状孔隙,f(Kn)=1+8Kn。当Kn<0.001时,连续流动等同于达西流,此时Jc=JD=d2ρg/(32μp),kg/(m2·s)[34]ρg为气体密度(kg/m3),μ为气体动力黏度(Pa/s),p为孔隙压力梯度(Pa/m)。
气体时效扩散系数受气体浓度、分子位置、孔隙结构和扩散时间等多因素影响[35]。综合考虑多种时间依赖型扩散方程,采用W. Zhao等[36]所提出的有效解吸扩散系数计算模型:
De(t)=D0τ1eξtt(1eξt)/ξ
式中:De(t)为有效解吸扩散系数(m2/s);D0为初始扩散系数(m2/s);τ为解吸时间参数;ξ为与孔径、气体密度和黏度相关的综合因子,当ξ趋向于无穷大时,De(t)=D0τ/t
气体分子在受限微管中的一次完整碰撞运动中,通过引入分子碰撞权重,可实现连续、非连续流动总质量通量的加权叠加[7]
Ja=wsJc+(1ws)Jdc
式中:ws为连续流动的碰撞权重,计算式为
ws=Kn/(Kn+2)
进一步基于量纲等效转换原则:kia=Jiaμ/(ρgipi)(式中,kmakfa分别为基质系统和裂隙系统的等效视渗透率;JmaJfa分别为基质系统和裂隙系统的连续、非连续流动总质量通量的加权叠加),联立式(15)~(17)可得到基质、裂隙系统各自质量通量的等效视渗透率分别为
kma=wsmdm2f(Knm)32+(1wsm)D0τμtpm
kfa=wsfdf2f(Knf)32+(1wsf)D0τμtpf
根据质量守恒定律,mt+(kμρgp)=Qs,基质/裂隙系统中气体流动控制方程可分别表示为
t(mm)+(kmaμρgmpm)=Qs
t(mf)+(kfaμρgfpf)=Qs
式中:Qs为基质与裂隙的质量交换量(kg/(m3·s));,mmmf分别为基质和裂隙系统中游离气和吸附气的质量总量:
mm=ρgϕm+ρgaρsmnexm
mf=ρgϕf+ρgaρsfnexf
式中:ρga为标准工况条件下气体密度(kg/m3),ρsmρsf分别为基质系统和裂隙系统的质量密度,ϕmϕf分别为基质系统和裂隙系统的孔隙率,nexmnexf分别为基质系统和裂隙系统的过剩吸附量。
考虑非线性流体效应和气体压差驱动,基质–裂隙系统间的气体质量交换为
Qs=τρgakmaμ(pmpf)
式中:τ为多孔介质的传递形状因子,在REV尺度上模拟流体质量交换,取值为1 m-2[37]
压差作用下具有不同力学性质的基质、裂隙,通过局部作用力交叉耦合产生的局部应变ΔεmdΔεfd分别为
Δεmd=pfpmKmΔεfd=pmpfKf}
当基质和裂隙达到压力平衡,即pm=pf,局部应变将消失,此时Δεmd=Δεfd=0。忽略气体吸附,基质和裂隙各自体积应变的变化量ΔεmvΔεfv可分别表示为
Δεmv=1Km(σ¯αpm)
Δεfv=1Kf(σ¯βpf)
式中:σ¯为岩体承受的3个主应力方向上压缩载荷σkk的平均值,σ¯=σkk/3
吸附应变增量Δεis是气压pi时膨胀应变与参考压力pi0时的膨胀应变差,利用Langmuir型应变函数,基质和裂隙系统的吸附应变增量ΔεmsΔεfs分别为
Δεms={εL1m(pmpm+pL1pm0pm0+pL1)   (pmpc)εL2m(pmpm+pL2pm0pm0+pL2)   (pcpm)
Δεfs=εLf(pfpf+pLfpf0pf0+pLf)
应用伪一级动力学方程,考虑应变滞后效应的机械应变εiv和吸附应变εis可分别表示[38]
εiv=εiv[1exp(t/tm)]
εis=εis[1exp(t/ts)]
式中:εivεis分别为极限机械应变和极限吸附应变,tmts分别为对应达到极限应变平衡所需时间。
基质系统的有效体积应变通过机械应变与裂隙–基质的局部应变之和,再减去吸附应变得到:
Δεme=Δεmv[1exp(ttm)]Δεms[1exp(tts)]+Δεmd=αpmσ¯Km[1exp(ttm)]Δεms[1exp(tts)]pfpmKm
式中:1exp(ttm)为机械应变;pfpmKm为基质局部应变;Δεms为气体吸附诱发应变,计算式为
Δεms={εL1m(pm)εL1m(pm0)  (pmpc)εL2m(pm)εL2m(pm0)  (pcpm)
与基质系统类似,裂隙系统的有效体积应变为
Δεfe=Δεfv[1exp(ttm)]Δεfs[1exp(tts)]+Δεfd=βpfσ¯Kf[1exp(ttm)][εLf(pf)εLf(pf0)][1exp(tts)]pmpfKf
式(31)中,等号右边第1项为机械应变,第2项为气体吸附诱发应变,第3项为裂隙局部应变。
多孔介质弹性体的孔隙度演化本质上随有效应变变化,满足如下表达式[39]
ϕiϕi0=1+abiotϕi0Δεie
式中:abiot为弹性体比奥系数,Δεie为有效应变,ϕiϕi0分别为动态孔隙率、初始孔隙率。
根据孔隙度–渗透率指数关系:ki/ki0=(ϕi/ϕi0)MM为受岩石孔隙连通性、颗粒大小分布和微观结构等因素影响的孔隙度敏感指数,当用REV结构的几何参数定义孔隙度比值表征渗透率比值时,通常M = 3[40],但真实页岩心试验结果表明,M取值为25~35范围,某些情况下高达50[41]。将式(30),(31)分别代入式(32),可得到基质和裂隙系统的渗透率比值km/km0kf/kf0分别为
kmkm0={1α(σ¯αpm)[1exp(ttm)]+pfpmKmϕm0+αΔεms[1exp(tts)]ϕm0}M
kfkf0={1β(σ¯βpf)[1exp(ttm)]+pmpfKfϕf0+β[εLf(pf)εLf(pf0)][1exp(tts)]ϕf0}M
L. F. Fenton[42]研究表明,整体渗透率可被定义为孔隙状和裂隙状渗透率的统计集合。假设基质和裂隙服从对数正态概率分布,且不存在控制渗流的主导流动路径,H. Singh等[43]提出基质组分、裂隙组分和总体渗透率(kbulk)遵循如下数学关系:
ln(kbulk)=Aln(km)+(1A)ln(kf)
式中:A为基质渗透率在整体渗透率中的贡献权重,取值0~1。从岩石的体积组成来看,A可解释为给定单位体积内基质的体积比例系数。将式(35)简化得到:
kbulk=kmAkf1A
将式(33)和(34)代入式(36),得到页岩整体渗透率演化模型为
kbulkkbulk  0=kmAkf1Akm0Akf01A=(kmkm0)A(kfkf0)1A
D. Davudov和R. G. Moghanloo[41]研究表明有效应力作用下孔隙连通性与页岩动态渗透率存在指数关系。将考虑连通性的修正项引入渗透率演化模型,得到如下表达式:
kbulkkbulk  0=(kmkm0)A(kfkf0)1AeLσ¯
式中:L为连通性损失系数,在岩体弹性损伤范围内应用修正项eLσ¯可提升模型的预测精度。当基质成分完全填充页岩时,A = 1,表示页岩渗透率比等同于基质系统渗透率比。事实上,很难分别量化基质和裂隙对整体渗透率的贡献,基于组分空间体积比例的方法,是一种折中方案。
图4展示了全压条件下CO2注入页岩的流–固耦合数值求解框架:以COMSOL自定义求解模块为核心,基于REFPROP精确提取不同相态CO2关键物性参数;通过MATLAB构建数据交互接口,实现CO2密度、黏度等物性参数与多物理场的协同耦合求解。其中,COMSOL平台主导完成2项关键计算:(1)基质–裂隙双系统流–固耦合,实现CO2物性参数更新和固体变形的动态交互机制;(2) 更新受载岩体力学参数变化,对模型进行动态求解。
为确保模型具备较好收敛性,定义注气目标压力pin为随时间变化的函数,即
pin=(pinpa)+pin[1exp(t/td)]
式中:pa为参考压力(大气压),td为控制气体注入速率的特征时间。如图5所示,注气速率越快,基质–裂隙之间的压差增长速率越快,压差极值Δpmax越大。
在气态CO2注入条件下,吸附诱导的页岩膨胀应变和吸附量描述均遵循Langmuir型公式:
εis=εLipi/(pi+pL)nis=nLipi/(pi+pL)}
对于CO2长时化学作用导致的应变滞后效应暂不做考虑,令
exp(t/tm)=0exp(t/ts)=0}
式(41)表示数值模拟过程中,对吸附应变过程不做额外的应变平衡时间干预。由于CO2与N2注入过程中基质–裂隙系统的惯性效应及裂缝变形机制具有相似性,基于N2注入页岩试验的渗透率动态响应数据[44],也可用于模型验证,模型相关参数取值如表3所示。
在实验室动态监测过程中应明确:当注气达到目标压力点时,不同时刻测得渗透率值可能呈现离散性。为建立试验数据与模拟结果的匹配对应关系,笔者采用颜色编码策略,将相同目标压力、不同模拟时间所得渗透率模拟值使用投影垂直条构建动态变化区间;将同等条件试验数据绘制于投影区间内,通过瞬时时间匹配关系预测试验所测时间点。
在实验室动态监测过程中应明确:当注气达到目标压力点时,不同时刻测得渗透率值可能呈现离散性。为建立试验数据与模拟结果的匹配对应关系,笔者采用颜色编码策略,将相同目标压力、不同模拟时间所得渗透率模拟值使用投影垂直条构建动态变化区间;将同等条件试验数据绘制于投影区间内,通过瞬时时间匹配关系预测试验所测时间点。
图6中数值模拟结果可以看到:无论N2还是气态CO2,在注气压力增大到目标值过程中,尽管变化幅度不同,但页岩整体渗透率随时间始终呈现出类“U型”演化;将渗透率–时间演化数据转化为渗透率–目标压力投影面,发现试验数据恰好落在模型预测的范围内。将不同注入目标压力达成后的平衡渗透率模拟值与试验数据对比,发现除了图6(a)中N2组高于6.8 MPa注入目标压力的渗透率出现明显回弹外,其余低压条件下,模拟与试验数据结果基本一致——都呈现逐渐下降趋势。不过,图6(b)中CO2组试验数据的下降并没模拟结果显著,这说明岩心内部未达到对CO2气体的吸附平衡,试验所测渗透率值并不代表最终实际平衡值。
对于渗透率演化趋势分析,笔者与H. H. Liu和J. L. Zhang[45]的观点一致,即因低渗页岩在低压阶段由非线性流动效应主导,导致渗透率快速衰减;随后机械变形效应占据主导,促使渗透率出现回升现象。笔者更深入一步的研究表明,机械变形效应的强弱还受到气体吸附效应的影响,对CO2吸附量–膨胀变形能力都更强的页岩显然回弹所需压力更大,如图6(b)所示。例如,同样4 MPa的目标注气压力,相比初始渗透率,N2组的页岩动态渗透率最大损失25%,明显弱于CO2组的最大损失55%。
图7(a)所示,超临界CO2注入过程中页岩渗透率阶段变化比气态注入更明显,呈现出典型的“W”型演化模式;随着注入目标压力的增大,这种阶段性演化愈发明显。在更高目标压力(>10 MPa)条件下,非平衡阶段渗透率出现的回弹趋势更明显,这与L. Hou和D. Elsworth[8]的3组试样试验结果相同;但渗透率平衡值呈现的却是缓慢下降趋势,这与图7(b)中L. Hou和D. Elsworth[8]将气态和超临界态CO2各自独立注入多组试样所测渗透率演化结果的平均值一致(L. Hou和D. Elsworth[8]将渗透率演化划分为气态区“U型”变化,相态转换区“V型”变化,超临界区“U型”变化)。图7(b)中散点数据由L. Hou和D. Elsworth[8]针对1~3号页岩样品,在气态、相变区和超临界态3个阶段分别进行独立CO2注入试验后,测得的渗透率平均值构成。
将不同时刻数值模拟渗透率演化趋势与全压注入过程的页岩试样数据进行匹配,发现1号页岩注入压力低于6 MPa时,渗透率数据在200 s左右匹配,7 MPa时在150 s匹配,8 MPa时在1 000~1 300 s范围匹配;2和3号页岩的渗透率演化趋势与模拟时间105 s时结果相似,但各自达到注气目标压力的时间存在显著差异;2和3号页岩所测部分数据大致在200和1 500 s时得到匹配,这表明不同目标压力注入过程中实测渗透率数据非岩心完全达到平衡后的稳定值,而是处于非平衡状态下的瞬态值。同时,可以看到105 s模拟所得渗透率“W型”演化曲线与L. Hou和D. Elsworth[8]试验所测“双U+V型”相似。但必须谨慎说明,模型与试验数据匹配的时间点(以s为单位)受多参数影响,其精确性不能完全等同于实际试验,仅可作为时间尺度上的预测值。
常围压条件下,CO2由气态到超临界态注入页岩过程中,结合多种应变机制演化情况,页岩的渗透率演化规律和驱动因素可描述为:
阶段I:外部气体由低压逐渐注入致密低渗岩体中,低气压气体滑脱效应占主导,视渗透率增大,导致渗透率比值呈现下降趋势;但同时气体迅速进入渗透性更强的裂隙系统,软性裂隙率先做出开度增大响应,其渗透率增加;而硬性基质受裂隙挤压影响,其渗透率暂时降低。前期注气过程中,基质–裂隙的力学变形对页岩整体渗透率影响十分有限,因此受气体滑脱效应影响,页岩整体渗透率比值呈现显著降低趋势。
阶段II:两孔隙介质系统内孔隙压力逐渐上升,由于基质具有发达的微/纳米孔和强大的吸附能力,其显著的体积膨胀将挤压裂隙使其收缩闭合,基质组分渗透率显著增加,而裂隙组分渗透率下降;考虑到基质组分体积占比优势,以及体积膨胀对孔隙连通性的连通强化,从而导致整体渗透率表现出与基质组分相似的阶段性增大。
阶段III:随注入压力持续上升,基质组分吸附逐渐达到饱和,但基质和裂隙之间压差诱发的局部应变显著增大,导致基质、裂隙各自的有效应变降低,从而使整体的有效应变降低,最终导致整体渗透率出现一定程度的降低。
阶段IV:虽然压差导致局部应变逐渐消失,但CO2与页岩矿物组分的持续化学反应,导致基质微孔变化并出现了短暂的二次吸附现象;在整体力学性质显著劣化情况下,二次吸附膨胀应变在抵消了一部分机械压缩应变后保持稳定,最终平衡渗透率虽有所增加,但未能恢复到初始值大小。
压差传递相关的特征时间td影响基质/裂隙局部应变竞争程度,平衡时间ts影响膨胀和机械应变之间的相互作用,对渗透率演化都有影响。因此,针对基质初始杨氏模量和泊松比(这里用E0νs0代指Em0νm0),压差传递特征时间td和应变平衡时间ts分别开展模型参数敏感性分析。基于表1所列实测参数劣化范围,模拟杨氏模量20%,30%和40%劣化损失,泊松比20%,40%和60%劣化增大,进行力学参数劣化量化分析,其余输入参数如表4中所列。
图8(a),(b)所示,基质力学参数劣化的加剧明显促进了阶段III整体渗透率的下降,并抑制了阶段IV渗透率的反弹;基质组分和裂隙组分各自渗透率比值的变化范围表明,力学参数经过劣化作用后,相同有效应力下软性裂隙对力学响应更为敏感。图8(c)中,td越小意味着越大的气体注入速率,高注气速率明显放大了阶段I~III的渗透率变化范围;图8(d)中,ts越大表明吸附应变耗时越长,tm不变情况下应变平衡时间的延长明显扩大了阶段II到III的渗透率变化范围。
图5可知,注入压力达到临界压力大约需要1 000 s,以这一节点为分界线,观察图8中的子图,发现超临界CO2区域渗透率表现出持续时间更长、更显著的下降趋势。显然,超临界CO2–页岩相互作用显著强化了渗透率应力敏感性,这与J. P. Zhou等[19]相关试验研究结论是完全一致的。
为何实验室高压CO2被注入岩心试验过程中,有些试验所测渗透率演化后期会出现回弹增大和减小2种情况呢?笔者认为,需要对注入岩心的CO2相态和流–固耦合作用机制进行区分。如图9(a)所示,在弹性变形假设前提下,外部应力和注气补能所诱发的裂隙–基质竞争变形具有可逆性,当高压气态CO2被注入时,在有效应力降低和基质显著膨胀变形作用下,达到气体平衡的页岩渗透率值会显著增大。当超临界态CO2被长期注入,一方面,矿化反应和气体吸附作用会引起页岩力学性质劣化、产生不可逆的塑性变形以及孔裂隙等微结构损伤,受孔裂隙连通性变化渗透率可能出现明显突增现象,甚至出现类似于压裂的渗透率阶跃行为,导致渗透率平衡值出现显著增大;另一方面,矿化反应也会引发缓慢矿物溶蚀沉淀并堵塞流体运移通道,再加上塑性劣化岩体渐进式的软化压实,也可能导致渗透率平衡值降低,但这一过程可能相当漫长。
图9(b)所示,模块化定义相异组分材料的重叠连续非均质岩石,渗透率数学模型通常为连续函数,通过参数设定确保流–固耦合求解结果稳定,其多物理场耦合求解表示了基质与裂隙之间的竞争性变形关系,自洽适应性使整个岩体在内部组分差异变形情况下也处于相对稳定状态。
然而,对于离散型介质,其多物理场耦合求解过程具有连接性和扩展性,当应变能积累至临界阈值时,岩体中预先存在的弱相(如裂隙)作为应力集中区首先发生局部破裂,这些局部破裂扩展通过应力场的动态调整形成级联效应。当释放的应变能量传递路径与岩体结构网络中的“高连通性区域”相遇时,就会触发指数级裂隙扩展,导致整体宏观破裂和结构失稳。为确保求解的稳定,渗透率数学模型通常定义为分段函数,从而能够更灵活地反映渗透率演化的阶段性变化,如:注气阶段渐进性蠕变分数阶损伤渗透率模型[46],或结构破坏失效突变渗透率模型[47]等。
对比来看,双连续介质方法在隐式处理裂缝–基质相互作用方面,比当前离散型裂缝网络(discrete fracture network,DFN)和离散裂缝矩阵(discrete fracture matrix,DFM)方法更为便捷,但在裂缝作为目标区域主要流动通道的情况下,无法显式捕捉裂缝几何形态及变化[48]。因此,耦合地质力学与多相流问题仍是数学模型、数值模型及离散化方案领域的难点,要准确捕捉裂缝–基质相互作用下的流体动力学行为,需要根据研究对象建立合适的理论模型并选用恰当的求解方案。表5为笔者参考相关文献总结的几类流–固耦合渗透率数学模型,其模型特征直观体现了渗透率建模的基本思路。
节4中,结合基质力学参数劣化、二次吸附及应变滞后效应构建的模型,与试验数据吻合良好。为了研究单一因素对渗透率演化的影响,笔者进行了3种情况解耦计算:(1)没有力学参数劣化的情况;(2) 没有二次吸附及分阶段应变的情况;(3) 没有应变滞后效应的情况。
图10(a)所示,不考虑基质力学性质劣化,整体渗透率仍呈现出四阶段演化规律。但是解耦基质力学参数劣化的渗透率比值,其变化范围(1~0.8)比图8(b)中耦合情况下的变化范围(1~0.98)更大,这表明基质的力学劣化并未放大渗透率的波动范围,反而对其起到了缓冲作用;图10(c)中的位移梯度云图则表明,基质与裂隙之间仍然存在显著的竞争应变作用。
(1)Langmuir型吸附模型应用
图11(a),(b)所示,当利用Langmuir吸附模型来描述吸附能力时,页岩整体渗透率虽经历了四阶段演化,但基质和裂隙的有效应变均呈现出“U形”变化趋势。图11(c)中位移梯度云图与图10(c)对比可以明显看出:由Langmuir吸附函数描述涵盖低压到高压注入场景过程中的真实吸附量,将低估CO2对基质微孔、中孔大小的改性作用,使得高压条件下被Langmuir模型简化的基质吸附膨胀作用被弱化,从而导致基质–裂隙系统间因吸附–变形机制差异导致的应变竞争效应显著削弱。
(2)解耦两阶段吸附膨胀变形
图12(a)所示,页岩整体渗透率仍然呈现出四阶段演化趋势,最明显的变化是渗透率终值对基质pLm十分敏感。如图12(b)所示,单一阶段Langmuir吸附应变过程,pLm的值决定了气体注入后最终渗透率是否会大于初始渗透率。试验所测pLm总是倾向于小于6 MPa[53],这意味着气体注入达到平衡后,页岩渗透率终值会大于初始值。显然,这与试验所测结果相反,表明单Langmuir型方程描述吸附应变不符合实际情况。
相比之下,使用两阶段应变函数可以更准确地预测渗透率演化的整个过程,这也反映出CO2相变对于吸附应变的确存在显著影响。此外,图12(c)中位移梯度随时间变化并不显著,表明两阶段吸附应变对基质–裂隙系统间的竞争应变影响显著。
图13(a)所示,当忽略应变滞后效应时,渗透率呈现多阶段演化特征。于阶段IV缓慢增大之后,又出现下降–稳定的过程,这可能是因为吸附应变已达极限后,力学性质劣化的页岩仍在经历缓慢的压缩应变累积,这一情况通过图13(b)中长时间显著的位移梯度变化得到佐证。同时,由于吸附变形比机械应变响应更早,因此基质、裂隙以及页岩整体的渗透率均存在短期上升现象。相比于图9(b)全耦合,无应变滞后效应的基质–裂隙竞争应变在注气较短时间内表现的更为显著(见图13(c))。
针对当前渗透率模型难以准确描述CO2由低压气态到超临界态全压注入页岩过程中的渗透率演化过程,运用理论建模与数值模拟方法开展CO2全压注入页岩渗透率演化过程研究,并揭示控制其阶段演化的基本机制,得出如下主要结论:
(1)受基质渗透率和裂隙渗透率演化之间复杂相互作用影响,页岩整体渗透率是一个耦合参数。在双孔隙均质材料模型中预测的渗透率演化反映的是组分渗透率,而在双弹性介质材料并行耦合框架内,页岩渗透率可表征为各组分渗透率加权后的耦合渗透率。基于组分渗透率加权确定的整体渗透率演化模型,能够有效刻画CO2注入过程中渗透率基本演化模式。
(2)在弹性力学与连续介质理论框架下,基于力–化耦合作用机制构建的渗透率演化模型,系统阐明了CO2相变诱发的渗透率四阶段演化过程,各阶段的渗透率演化规律及主控因素为:阶段I,渗透率比值下降,主要由气体滑脱效应占据主导,基质–裂隙的力学变形影响有限;阶段II,渗透率增加,主要由吸附膨胀控制;阶段III,渗透率下降,主要由竞争性局部应变驱动;阶段IV,渗透率恢复增加,主要归因于二次吸附膨胀以及基质力学性能劣化。
(3)裂隙与基质的力学差异显著扩大了渗透率演化范围。杨氏模量降低会减弱渗透率变化幅度,延缓演化过程,而泊松比的增加则与之相反;机械应变和吸附应变同步响应影响渗透率的演化模式和渗透率平衡终值,应变滞后效应仅延长了各阶段演化持续时间,使渗透率呈现出更为直观的多阶段演化特征;应用Langmuir吸附模型对渗透率演化趋势分析影响不大,但会低估平衡后渗透率终值;双Langmuir型吸附应变函数应用,显著提高了超临界CO2区域渗透率演化预测的准确性。
当前,通过弹塑性损伤本构模型定义页岩力学损伤过程仍存在局限性,未来需考虑连续–非连续介质的耦合求解,以期更精准表征页岩复杂破坏机制。此外,笔者正构建基于原位CT可视化的多物理场耦合试验平台,致力于解构渗透率动态演化各阶段对应的微观结构变形规律,从而揭示页岩多尺度力学响应对渗透性演化的控制机制。
  • 国家自然科学基金面上项目(52574238; 52274191)
  • 河南理工大学河南省瓦斯地质与瓦斯治理重点实验室开放课题(WS2024B10)
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2026年第45卷第2期
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doi: 10.3724/1000-6915.jrme.2025.0505
  • 接收时间:2025-07-17
  • 首发时间:2026-06-18
  • 出版时间:2026-02-01
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  • 收稿日期:2025-07-17
  • 修回日期:2025-10-13
基金
National Natural Science Foundation of China(52574238; 52274191)
国家自然科学基金面上项目(52574238; 52274191)
Open Project of Henan Key Laboratory for Gas Geology and Gas Control, Henan Polytechnic University(WS2024B10)
河南理工大学河南省瓦斯地质与瓦斯治理重点实验室开放课题(WS2024B10)
作者信息
    1.河南理工大学 安全科学工程学院,河南 焦作 454000
    2.河南理工大学 河南省瓦斯地质与瓦斯治理重点实验室–省部共建国家重点实验室培育基地,河南 焦作 454000
    3.河南理工大学 煤矿瓦斯灾害防治应急管理部重点实验室,河南 焦作 454000

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* 王登科(1980–),现任教授,主要从事安全科学与工程方面的研究工作。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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