Article(id=1322942811196236335, tenantId=1146029695717560320, journalId=1322258508890079423, issueId=1322942002035295141, articleNumber=null, orderNo=null, doi=10.13809/j.cnki.cn32-1825/te.20250113, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1767110400000, receivedDateStr=2025-12-31, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793343745277, onlineDateStr=2026-10-30, pubDate=1790352000000, pubDateStr=2026-09-26, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793343745277, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793343745277, creator=13701087609, updateTime=1793343745277, updator=13701087609, issue=Issue{id=1322942002035295141, tenantId=1146029695717560320, journalId=1322258508890079423, year='2026', volume='16', issue='5', pageStart='949', pageEnd='1136', issueExtLink='null', onlineDate='null', pubDate='1790352000000', pubDateStr='2026-09-26', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793343552359, creator='13701087609', updateTime=1793344212649, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322944771945267389, tenantId=1146029695717560320, journalId=1322258508890079423, issueId=1322942002035295141, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322944771945267390, tenantId=1146029695717560320, journalId=1322258508890079423, issueId=1322942002035295141, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1093, endPage=1102, ext={EN=ArticleExt(id=1322942811435311664, articleId=1322942811196236335, tenantId=1146029695717560320, journalId=1322258508890079423, language=EN, title=Inversion and application of coal rock fracturing parameters based on multistage shut-in pressure decline analysis, columnId=1322941621217657699, journalTitle=Petroleum Reservoir Evaluation and Development, columnName=Engineering Techniques, runingTitle=null, highlight=

To tackle the difficulties in real-time evaluation of coalbed methane (CBM) reservoir fracturing performance and the insufficient consideration of multi-scale fracture network closure in conventional inversion models, this study identified the hierarchical closure processes of cleats, natural fractures, and hydraulic fractures using the inflection points from the shut-in pressure decline curves. Taking multi-stage fracture closure as the core mechanism, the study integrated coupled material balance principles with pressure transient analysis methods. Inversion formulas for fracture surface area, half-length, and complexity index were derived. And a shut-in pressure decline inversion model for coal rock reservoirs was established. Using the granulated coal reservoir in Fukang, Xinjiang, as a validation case, the fracture half-length inverted by the model was 45.4% lower than the microseismic monitoring result, as the model only captured the wet stimulated reservoir volume (SRV) with sustained conductivity and excluded fractures without effective flow contribution, making the results more consistent with engineering reality. The model was further applied to medium-shallow high-rank coal in the Qinshui Basin and deep coal rock in the Ordos Basin. Results revealed significant differences in fracturing performances among the three coal types. For shallow granulated coal, the surface area proportions of main fractures and secondary fractures were 9.18% and 52.17%, respectively. The fracture network was short and complex, with a complexity index of 10.03. For medium-shallow high-rank coal, the main fracture accounted for 14.29%, and secondary fractures accounted for 77.5%. The fracture network extended relatively far along main fractures, with a complexity index of 6.05. For deep coal reservoirs, main and secondary fractures accounted for 22.08% and 77.92%, respectively. No connected cleat system was observed and the network had a complexity index of 3.67. Comparative analysis showed that coal integrity and in-situ stress conditions jointly controlled fracture network development patterns. Granulated coal restricted main fracture extension due to coal structure disruption and heavy fluid loss. Primary-structure coal and deep coals exhibited lower leakoff, allowing stable extension of main fractures. However, high vertical stress in deep coals inhibited fracture branching and limited network complexity. The proposed model overcomes the limitations of conventional approaches by accurately identifying multi-stage fracture closure characteristics, distinguishing fracture development differences caused by coal structures, and improving the technical framework of shut-in pressure decline inversion for evaluating CBM fracturing performance. It provides theoretical support for the optimization and effectiveness evaluation of fracturing designs in CBM reservoirs.

, articleAbstract=null, authors=ZHIHONG ZHAO1, 2, LIXIAO ZHAI1, 2, JIANCHUN GUO1, 2, TAO ZHANG1, 2, JIE ZENG1, 2, TIANBIN LIAO3, HENG ZHANG3, authorsList=ZHIHONG ZHAO, LIXIAO ZHAI, JIANCHUN GUO, TAO ZHANG, JIE ZENG, TIANBIN LIAO, HENG ZHANG, authorCompany=null, correspAuthors=LIXIAO ZHAI, 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, fund=null), CN=ArticleExt(id=1322942815046607427, articleId=1322942811196236335, tenantId=1146029695717560320, journalId=1322258508890079423, language=CN, title=基于多级停泵压降分析的煤岩压裂参数反演与应用, columnId=1322941621964243813, journalTitle=油气藏评价与开发, columnName=工程工艺, runingTitle=null, highlight=

针对煤层气储层压裂效果实时评价难、常规反演模型未充分考虑多尺度缝网闭合的问题,基于停泵压降曲线拐点识别割理、天然裂缝、水力裂缝的分级闭合过程,以多级裂缝闭合为核心,结合耦合物质平衡原理与压力瞬态分析方法,推导裂缝表面积、半长及复杂指数的反演公式,构建适用于煤岩的停泵压降反演模型。以新疆阜康碎粒煤储层为验证,模型反演裂缝半长较微震监测值低45.4%,该偏差源于模型仅识别具备持续导流能力的“湿SRV(储层改造体积)”,滤除无导流贡献的裂缝,结果更贴合工程实际。进一步应用于沁水盆地中浅层高阶煤与鄂尔多斯深部煤岩,结果表明三类煤层压裂效果差异显著:浅层碎粒煤主裂缝表面积占比9.18%,次级裂缝52.17%,缝网短而复杂,复杂指数10.03;中浅层高阶煤主裂缝占比14.29%,次级裂缝77.5%,缝网以主裂缝为骨架且延伸较长,复杂指数6.05;深部煤岩压裂主裂缝占比22.08%,次级裂缝77.92%,未见沟通的割理系统,缝网长而简单,复杂指数3.67。对比分析表明:煤体完整性和地应力条件共同主导裂缝网络的发育模式,碎粒煤因煤体破碎、滤失严重,抑制主裂缝延伸;原生结构煤与深部煤滤失较低,主裂缝可稳定扩展,但深部煤受高垂向应力制约,难以形成分支裂缝,限制了缝网复杂化。研究模型突破传统局限,可精准识别裂缝多级闭合特征,区分煤体结构引发的裂缝发育差异,完善煤层气压裂效果停泵压降反演技术体系,为煤层气储层压裂方案优化与效果评价提供理论支撑。

, articleAbstract=null, authors=赵志红1, 2, 翟利晓1, 2, 郭建春1, 2, 张涛1, 2, 曾杰1, 2, 廖天彬3, 张恒3, authorsList=赵志红, 翟利晓, 郭建春, 张涛, 曾杰, 廖天彬, 张恒, authorCompany=null, correspAuthors=翟利晓, authorNote=

赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

, correspAuthorsNote=
翟利晓(2000—),男,在读硕士研究生,主要从事煤层(岩)气压裂参数智能反演相关研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:
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赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

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赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

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Natural Gas Industry, 2024, 44(10): 126-139., articleTitle=Research progress and prospect of deep coalrock fracturing, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322942815289877060, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, xref=1, ext=[AuthorCompanyExt(id=1322942815298265669, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815289877060, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, China), AuthorCompanyExt(id=1322942815306654278, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815289877060, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 西南石油大学油气藏地质及开发工程全国重点实验室,四川   成都 610500)]), AuthorCompany(id=1322942815394734663, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, xref=2, ext=[AuthorCompanyExt(id=1322942815403123272, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815394734663, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Petroleum and Engineering School, Southwest Petroleum University, Chengdu, Sichuan 610500, China), AuthorCompanyExt(id=1322942815411511881, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815394734663, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 西南石油大学石油与天然气工程学院,四川   成都 610500)]), AuthorCompany(id=1322942815482815050, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, xref=3, ext=[AuthorCompanyExt(id=1322942815495397963, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815482815050, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 Xinjiang Yaxin Coalbed Methane Resources Technology Research Co., Ltd., Urumqi, Xinjiang 830063, China), AuthorCompanyExt(id=1322942815507980876, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, companyId=1322942815482815050, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 新疆亚新煤层气资源技术研究有限责任公司,新疆   乌鲁木齐 830063)])], figs=[ArticleFig(id=1322942819920388737, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=EN, label=Fig.1, caption=Shut-in pressure decline inversion methodology framework for multi-stage fracture closure, figureFileSmall=Rsikj2F5UjVFIZw06o1rWg==, figureFileBig=jHRAkxljdYOQmKhyqJGOOg==, tableContent=null), ArticleFig(id=1322942819995886210, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=图1, caption=多级裂缝闭合的停泵压降反演方法框架

注:te为停泵时刻,单位min;t1、t2、tend分别为沟通割理、次级裂缝和水力主裂缝的闭合时刻,单位min;Δp为停泵压降,单位MPa;Δp/ΔG为压降导数。

, figureFileSmall=Rsikj2F5UjVFIZw06o1rWg==, figureFileBig=jHRAkxljdYOQmKhyqJGOOg==, tableContent=null), ArticleFig(id=1322942820184629891, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=EN, label=Fig.2, caption=Schematic diagram of multi-stage fracture closure characteristics, figureFileSmall=V5T2AaGuRgqAJ8Yy3vJtGg==, figureFileBig=Wwcc5twAQiE0dFxlsxib7A==, tableContent=null), ArticleFig(id=1322942820247544452, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=图2, caption=多级裂缝闭合特征示意图, figureFileSmall=V5T2AaGuRgqAJ8Yy3vJtGg==, figureFileBig=Wwcc5twAQiE0dFxlsxib7A==, tableContent=null), ArticleFig(id=1322942820364984965, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=EN, label=Fig.3, caption=Flowchart for analytical solution calculation, figureFileSmall=0kHL791k0idTZipHcNV5Tw==, figureFileBig=HUiFG6mDoRbDRS65dmc+RA==, tableContent=null), ArticleFig(id=1322942820427899526, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=图3, caption=解析求解流程, figureFileSmall=0kHL791k0idTZipHcNV5Tw==, figureFileBig=HUiFG6mDoRbDRS65dmc+RA==, tableContent=null), ArticleFig(id=1322942820486619783, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=EN, label=Fig.4, caption=Microseismic monitoring and parameter inversion results of stage 3 in Well A, figureFileSmall=MVrj9O8RZLrX2p7G6N3qBA==, figureFileBig=f7lNkCKbfKJQkLa4X0ZslQ==, tableContent=null), ArticleFig(id=1322942820637614728, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=图4, caption=A井第3段微地震监测及参数反演结果, figureFileSmall=MVrj9O8RZLrX2p7G6N3qBA==, figureFileBig=f7lNkCKbfKJQkLa4X0ZslQ==, tableContent=null), ArticleFig(id=1322942820704723593, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=EN, label=Fig.5, caption=Fitting pressure and calculation results of stage 6 in Well A, figureFileSmall=qG03/0A/dMg34bGGGOvhIA==, figureFileBig=FYutZ+CHooUeZvIZWVmEsA==, tableContent=null), ArticleFig(id=1322942820796998282, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=图5, caption=A井第6段拟合压力和计算结果

注:p3*、p2*、p1*分别为沟通割理、天然裂缝、水力裂缝闭合时刻的压降斜率。

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参数参数取值/MPa裂缝半长/m敏感系数
p3*11.460105.980.435
7.64088.530.460
p2*14.988112.420.765
9.99281.800.805
p1*19.494120.411.175
12.99673.321.240
), ArticleFig(id=1322942823183557268, tenantId=1146029695717560320, journalId=1322258508890079423, articleId=1322942811196236335, language=CN, label=表1, caption=

参数敏感性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
参数参数取值/MPa裂缝半长/m敏感系数
p3*11.460105.980.435
7.64088.530.460
p2*14.988112.420.765
9.99281.800.805
p1*19.494120.411.175
12.99673.321.240
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基于多级停泵压降分析的煤岩压裂参数反演与应用
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赵志红 1, 2 , 翟利晓 1, 2 , 郭建春 1, 2 , 张涛 1, 2 , 曾杰 1, 2 , 廖天彬 3 , 张恒 3
油气藏评价与开发 | 工程工艺 2026,16(5): 1093-1102
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油气藏评价与开发 |工程工艺 2026 , 16 (5) : 1093 -1102
基于多级停泵压降分析的煤岩压裂参数反演与应用
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赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

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赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

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赵志红1, 2 , 翟利晓1, 2, 郭建春1, 2, 张涛1, 2, 曾杰1, 2, 廖天彬3, 张恒3
作者信息
  • 1 西南石油大学油气藏地质及开发工程全国重点实验室,四川   成都 610500
  • 2 西南石油大学石油与天然气工程学院,四川   成都 610500
  • 3 新疆亚新煤层气资源技术研究有限责任公司,新疆   乌鲁木齐 830063
通讯作者:
翟利晓(2000—),男,在读硕士研究生,主要从事煤层(岩)气压裂参数智能反演相关研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:
作者简介:

赵志红(1981—),男,博士,副教授,主要从事油气藏储层改造及采油气理论与技术研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:

Inversion and application of coal rock fracturing parameters based on multistage shut-in pressure decline analysis
ZHIHONG ZHAO1, 2 , LIXIAO ZHAI1, 2, JIANCHUN GUO1, 2, TAO ZHANG1, 2, JIE ZENG1, 2, TIANBIN LIAO3, HENG ZHANG3
Affiliations
  • 1 State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, China
  • 2 Petroleum and Engineering School, Southwest Petroleum University, Chengdu, Sichuan 610500, China
  • 3 Xinjiang Yaxin Coalbed Methane Resources Technology Research Co., Ltd., Urumqi, Xinjiang 830063, China
出版时间: 2026-09-26 doi: 10.13809/j.cnki.cn32-1825/te.20250113
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低阶煤  /  高阶煤  /  深部煤岩  /  水力压裂  /  压裂参数反演  /  多级裂缝闭合
low-rank coal  /  high-rank coal  /  deep coal rock  /  hydraulic fracturing  /  fracturing parameter inversion  /  multi-stage fracture closure
赵志红, 翟利晓, 郭建春, 张涛, 曾杰, 廖天彬, 张恒. 基于多级停泵压降分析的煤岩压裂参数反演与应用. 油气藏评价与开发, 2026 , 16 (5) : 1093 -1102 . DOI: 10.13809/j.cnki.cn32-1825/te.20250113
ZHIHONG ZHAO, LIXIAO ZHAI, JIANCHUN GUO, TAO ZHANG, JIE ZENG, TIANBIN LIAO, HENG ZHANG. Inversion and application of coal rock fracturing parameters based on multistage shut-in pressure decline analysis[J]. Petroleum Reservoir Evaluation and Development, 2026 , 16 (5) : 1093 -1102 . DOI: 10.13809/j.cnki.cn32-1825/te.20250113
中国埋深小于2 000 m的煤层气地质资源量约30.05×1012 m3,可采资源量约12.5×1012 m3[1-3],该类储层普遍低渗,孔隙结构复杂,天然裂缝与割理系统发育[4],对压裂改造效果影响显著。常规压裂设计常忽略天然裂缝与割理的增产核心作用,导致产能提升效果不稳定,亟须建立可靠的地质特征识别与压裂效果评价方法,为现场施工方案优化提供理论依据。
当前煤层气压裂效果评价以产能和缝网改造体积为核心,产能评价依赖长期生产数据,难以实现实时反馈与施工参数优化,而裂缝参数快速反演对现场方案调整具有重要工程价值[5-8]。数值模拟是表征缝网形态的主流方法[9-13],但受网格划分、多场耦合效应等限制,计算效率低、自由度大,无法满足现场实时应用的需求[14-17]。
针对上述问题,间接反演方法成为压裂效果快速评价热点,其中,停泵压降反演技术因经济、高效受广泛关注,相较微地震、分布式光纤传感技术[18-21],该方法可低成本反演裂缝参数,且精准识别流体实际改造的缝网体积,在筛选精度上更具优势。现有研究中,Zeng等[22]、Liu等[23]证实了该技术在非常规油气储层的应用价值,其中,分级闭合现象已得到前沿研究的理论支撑与现场验证[24]。但相关方法在煤层气领域适配性不足,未考虑多尺度缝网的渐进闭合过程,主要局限源于传统模型未能考虑不同尺度裂缝因力学性质差异的非同步闭合行为。
当前煤层气压裂的停泵压降反演研究,尚未见能表征“割理-天然裂缝-水力裂缝”3级渐进闭合的模型,制约了压裂效果的精细评价。因此,研究突破传统单级闭合假设,耦合物质平衡(MB)与压力瞬态分析(PTA)方法,考虑主裂缝、次级裂缝及割理的连续闭合过程,基于停泵压降双对数图版中划分裂缝多级闭合阶段,构建煤岩压裂多级裂缝闭合特征的停泵压降分析模型。同时,引入裂缝复杂指数(FCI)与等效裂缝半长量化评价水力压裂效果,为煤层气藏的高效开发提供理论支持与技术依据。
煤岩水力压裂中,高压流体注入储层诱导主裂缝形成并扩展,在地应力各向异性与煤岩体非均质性共同作用下,主裂缝衍生分支裂缝并沟通、激活割理系统,3类裂缝连通形成具备良好导流能力的多级裂缝网络和稳定的压力分布场,为煤层气高效渗流提供运移通道(图1)。
压裂停泵后,对压降数据进行双对数诊断图版分析可有效识别裂缝多级闭合特征:停泵压降曲线及其导数曲线呈多段线性特征,拐点为不同尺度裂缝依次闭合的物理响应。停泵初期各类裂缝均张开,滤失面积最大、压力陡降,对应图中斜率最陡线段;随压力下降,裂缝按力学性质分级闭合,t1时刻刚度最小的割理发生集体闭合,滤失系数降低,导数曲线出现拐点,压力降落速率减缓;t2时刻天然裂缝网络闭合,滤失系数再降,形成第2个拐点,滤失由水力裂缝主导,直至tend时刻水力裂缝完全闭合。压力响应据此分为3阶段,该过程遵循物质平衡原理,特征拐点界定阶段边界,为裂缝参数反演提供物理基础。
为精准表征裂缝多级闭合过程的停泵压降响应特征(图2),有以下基本假设:
1) 停泵后水力裂缝、次级裂缝与沟通割理相互贯通,形成统一压力系统,忽略裂缝储集效应;
2) 停泵后地层流体滤失符合卡特滤失模型,各闭合阶段内滤失系数保持恒定;
3) 忽略流动诱导的裂缝尖端延伸效应与流动摩擦效应;
4) 停泵至裂缝完全闭合阶段,裂缝柔度与闭合压力保持恒定;
5) 裂缝闭合阶段历时较短,压力瞬变响应近似为线性流主导流态。
停泵时段内,裂缝体积变化量表达式为:
V1(Δt)=w(te+t0)Ae
式中:V1为停泵t0时间内裂缝体积变化量,单位m3;Δt为停泵后计算裂缝体积变化的时间间隔,单位min;w为裂缝缝宽,单位m;te为停泵时刻,单位min;t0为停泵后用于计算裂缝体积变化的时间间隔,单位min;Αe为停泵时单翼裂缝滤失面积,单位m2。
基于裂缝柔度与缝内净压力定义,缝宽与净压力的关系为:
cf=w(te+t0)pt-pc
式中:cf为裂缝平均柔度,单位m/MPa;pt为裂缝内压力,单位MPa;pc为裂缝闭合压力,单位MPa。
联立公式(1)、公式(2)并微分,得裂缝闭合阶段压力—体积变化关系:
dV1dt=Aecfdpnetdt
式中:pnet为裂缝内净压力,单位MPa;t为停泵后所经历的停泵时间,单位min。
对公式(3)在t0时间内进行积分,得到停泵时刻裂缝体积表达式:
V1=cfAe(pt-pc)
由公式(4)可求解停泵后(te+t0)时段内的裂缝体积变化量,结合煤层气裂缝多级闭合特征,按不同阶段计算裂缝体积变化V1:
V1=CmfAmf+Csf1Asf1+Csf2Asf2pISIP-pc,sf2te≤t≤t1CmfAmf+Csf1Asf1pISIP-pc,sf1t1≤t≤t2CmfAmfpISIP-pc,sft2≤t≤tend
式中:Cmf、Csf1、Csf2分别为水力裂缝、次级裂缝和沟通割理的裂缝柔度,单位m/MPa;Amf、Asf1、Asf2分别为水力裂缝、次级裂缝和沟通割理的单侧表面积,单位m2;pc,sf、pc,sf1、pc,sf2分别为水力裂缝、次级裂缝和沟通割理闭合时的闭合压力,单位MPa;pISIP为剔除摩阻的瞬时停泵压力,单位MPa;tend、t2和t1分别为停泵后水力裂缝、次级裂缝和沟通割理完全闭合的时间,单位min。
采用卡特滤失模型,推导时间t内面积为dA(裂缝单元的微小滤失面积)的裂缝单元压裂液滤失量微分方程:
dV2=2dACLrp(t-te)1-θdtte≤t≤t1dV2=2dACL1rp(t-te)1-θdtt1≤t≤t2dV2=2dACL2rp(t-te)1-θdtt2≤t≤tend
式中:dV2是该微小面积dA上,在时间dt内产生的压裂液滤失体积微元;CL、CL1和CL2分别为水力裂缝、次级裂缝和沟通割理的滤失系数,单位m/min0.5;V2为时间t后的滤失体积,单位m3;θ为压裂液滤失指数;rp为滤失高度与裂缝高度的比值,近似可取值1。
按裂缝闭合阶段对公式(6)进行时间与面积双重积分,可得停泵后各阶段流体滤失量V2,表达式如下:
V2=2rpCL∫0Amf∫tet11t-te1-θdAdt+2rpCL1∫0Asf1∫tet11t-te1-θdAdt+2rpCL2∫0Asf2∫tet11t-te1-θdAdtte≤t≤t12rpCL∫0Amf∫t1t21t-te1-θdAdt+2rpCL1∫0Asf1∫t1t21t-te1-θdAdtt1≤t≤t22rpCL∫0Amf∫t2tend1t-te1-θdAdtt2≤t≤tend
式中:V2为停泵后各阶段流体滤失量,单位m3;CL、CL1、CL2分别为水力裂缝、次级裂缝和沟通割理的滤失系数,单位m/min0.5。
将各阶段滤失系数简化为恒定值是模型实现解析求解、大幅降低计算复杂度的关键。但实际停泵过程中缝内压力与裂缝形态持续变化,因此,后续将引入滤失系数随缝内压力的动态变化机制,提升复杂煤层滤失行为的刻画精度。
压裂液是牛顿流体(滤失指数θ=0.5),可对公式(7)进行简化的表达式如下:
V2=4t1-teCLrpAmf+CL1rpAsf1+CL2rpAsf2te≤t≤t14t2-t1t2-te-t1-teCLrpAmf+CL1rpAsf1t1≤t≤t24tend-t2tend-te-t2-teCLrpAmft2≤t≤tend
根据Nolte理论,滤失阶段裂缝面积呈幂律增长,泵入裂缝总流体体积比例按不同阶段的滤失时间比例划分,据此得到单簇泵入体积表达式如下:
V3=VPt1-teNtend-tete≤t≤t1VPt2-t1Ntend-tet1≤t≤t2VPtend-t2Ntend-tet2≤t≤tend
式中:V3为单簇泵入体积,单位m³;Vp为注入裂缝的体积,单位m³;N是射孔簇的数量。
结合煤岩压裂存在部分射孔簇无效的实际情况和经验[25-26],将射孔簇数取为设计簇数的70%。裂缝闭合各阶段泵入裂缝的流体体积等于裂缝体积变化量与流体滤失量之和,表达式为:
VPt1-teNtend-te=4rpt1-teCLAmf+CL1Asf1+CL2Asf2+CmfAmf+Csf1Asf1+Csf2Asf2pISIP-pc,sf2                                                                                          te≤t≤t1VPt2-t1Ntend-te=4t2-t1rpt2-te-t1-teCLAmf+CL1Asf1+CmfAmf+Csf1Asf1pISIP-pc,sf1                                                                                          t1≤t≤t2VPtend-t2Ntend-te=4tend-t2tend-te-t2-teCLrpAmf+CmfAmfpISIP-pc,mf                       t2≤t≤tend
停泵后任意时间间隔t0内的流体滤失量,为该时段始末滤失量的差值,结合滤失量计算方法得该时段滤失量为:
ΔVL=2AeteθCLrpgΔt,α,θ-g0α,θ
式中:teθ为停泵时刻的时间幂次基准项,单位minθ;gΔt,α,θ为Nolte无因次滤失时间函数;g0α,θ为初始基准无因次时间常数。
对公式(3)积分,得停泵后裂缝体积收缩量为:
ΔVf=AeCfΔpnet
式中:∆Vf为停泵后裂缝体积收缩量,单位m3。
据物质平衡原理,停泵后流体滤失量等于裂缝体积收缩量,联立公式(11)、公式(12),即得停泵压降模型:
Δpnet=πCLrpteθ2Cf4πgt0,α,θ-g0α,θ=πCLrpteθ2CfGt0,α,θ
引入Nolte提出的无因次G函数,描述停泵至裂缝完全闭合过程的无因次时间差为:
G(t0,α,θ)=4πgt0,α,θ-gα,θ
由净压力定义,不同时段的停泵压降模型如下:
pwt-pc,sf2=πrpte(CL+CL1+CL2)2(Cmf+Csf1+Csf2)Gt1,α,θ-GtD,α,θte≤t≤t1pwt-pc,sf1=πrpte(CL+CL1)2(Cmf+Csf1)Gt2,α,θ-GtD,α,θt1≤t≤t2pwt-pc,mf=πrpteCL2CmfGtend,α,θ-GtD,α,θt2≤t≤tend
对公式(15)关于时间t求导,引入拟合压力p*:
p3*=πrpte(CL+CL1+CL2)2(Cmf+Csf1+Csf2)te≤t≤t1p2*=πrpte(CL+CL1)2(Cmf+Csf1)t1≤t≤t2p1*=πrpteCL2Cmft2≤t≤tend
式中:p3*、p2*和p1*分别为沟通割理、天然裂缝、水力裂缝闭合时刻的压降斜率。
对公式(15)两侧关于G求微分,可得拟合压力等于dp/dG。结合公式(16),拟合压力与滤失系数呈线性关系,但实际应用中该曲线斜率较小,水平段难以识别。为此,采用Barree等[27]提出的叠加导数曲线Gdp/dG增强识别效果,过原点作曲线切线,切线斜率为拟合压力,曲线首次明显偏离线性趋势的点为裂缝闭合点,对应裂缝闭合时间和压力。
基于裂缝多级闭合压降模型与G函数求解方法,推导得到裂缝参数反演公式,结合公式(10)和公式(16)为模型求解的核心方程组,构建解析求解流程(图3)。该方程组无需复杂数值迭代,通过识别压降导数曲线拐点,将多裂缝系统反演分解为沟通割理、次级裂缝及主裂缝闭合3个顺序发生的独立阶段,各阶段方程组均得以简化,从而联立求解对应裂缝参数。
为实现各阶段解析求解,需引入简化条件,忽略裂缝储集效应,联立公式求解,可反演多级裂缝闭合过程的裂缝表面积及对应滤失系数。该简化将各阶段闭合压力与裂缝柔度设为恒定值,显著降低了计算复杂度。为表征水力压裂效果,定义复杂指数为次级裂缝与沟通割理的表面积之和与水力主裂缝表面积的比值。复杂指数越大,表明压裂沟通的割理及次级裂缝越多、缝网面积越大,压裂效果越优,其表达式为:
IFC=Asf1+Asf2/Amf
式中:IFC为复杂指数。
基于二维裂缝扩展模型的定裂缝缝高假定,结合水力压裂裂缝的迂曲性特征,水力压裂裂缝半长表达式如下:
Xf=Amf2hfτhτl
式中:Xf为裂缝半长,单位m;hf为裂缝缝高,单位m;τh、τl分别为裂缝在缝高、缝长方向上的迂曲度。
迂曲度的取值主要由煤体结构决定。在岩石力学和物性相似的储层中,迂曲度可视为定值;不同储层中则需根据相关参数调整,反演时保持取值恒定即可。
以新疆阜康区块碎粒煤水平井A井为验证对象,该井目的层41号煤层为碎粒结构,属中渗低孔储层,内生裂隙发育且无充填。结合储层缝网迂曲度高的特征,迂曲度取值1.8~2.0以表征其复杂缝网形态。以微地震监测裂缝长度为基准,选取第3段和第6段,分别开展参数反演、拟合压力精度分析及敏感性分析。
A井第3段反演结果如图4所示,微地震监测裂缝长度284 m,研究模型的计算相对误差为11.3%,低于文献[22]模型的25.1%。通过考虑裂缝多级闭合过程,模型显著提高了反演精度,使结果更接近监测值,这与页岩气多技术对比研究的结论一致[28]。微地震监测表征包含所有力学响应区域的“干SRV(储层改造体积)”,而研究模型仅识别具备持续导流能力的“湿SRV”,滤除无导流贡献的裂缝,反演结果更贴合工程实际。
基于G函数结合公式(10)和公式(16),对A井第6段开展拟合压力精度与敏感性分析(图5):叠加导数曲线呈现多重驼峰形态,随着裂缝按闭合压力由低到高依次闭合,驼峰切线斜率呈阶梯式递减,其变化规律可直接表征滤失系数的动态演化。因此,驼峰个数可作为识别裂缝级数的直接判据。将拟合压力方法与数值模拟结果对比,显示拟合精度均超过80%,表明该模型在压力拟合中具有较好的可靠性。
采用控制变量法开展参数敏感性分析,固定两个拟合压力参数,将第三个参数在±20%范围内以5%为步长变动,计算裂缝半长的相对变化率并定义敏感性系数为:
S=ΔXf/X0Δp*/p0*
式中:S为裂缝半长对拟合压力的敏感性系数;X0为裂缝半长的初始值,单位m;ΔXf为裂缝半长相对于初始值的变化量,单位m;p0*为拟合压力的初始值,单位MPa;Δp*为拟合压力相对于初始值的变化量,单位MPa。
进行参数敏感性分析发现(表1):3个拟合压力参数对裂缝半长均表现为正敏感性,其中水力裂缝对应的参数敏感性最高,该差异源于水力裂缝作为缝网核心,其闭合阶段的压力响应直接控制有效缝网规模。拟合压力精度与敏感性的分析结果和微地震验证结果相互补充,表明研究所建模型可准确识别多级裂缝闭合行为,参数体系具备明确的物理意义与良好的数值稳定性。
为探讨停泵压降模型的适用性,现将停泵压降模型应用于浅层碎粒煤、中浅层高阶煤、深部煤岩3类典型煤层气储层,反演压裂参数结合各储层的地质条件与对应的停泵压降数据,分析缝网发育特征,揭示不同的缝网形态及其成因,并提出针对性压裂工艺对策。
基于新疆阜康区块浅层碎粒煤储层压裂施工数据,采用模型反演得到裂缝平均半长101.5 m,平均复杂指数10.03,主裂缝表面积占比9.18%,次级裂缝占比52.17%,表明碎粒煤储层压裂难以形成单一主裂缝,缝网以短而复杂的形态为主体,次级裂缝为缝网构成核心。从图7可见,停泵压降曲线可清晰识别3级裂缝在停泵阶段依次主导闭合的3个阶段,该类储层煤体破碎度高、强度低,压裂时易发育短而复杂的缝网,大量缝网界面会加剧滤失,进一步限制主裂缝延伸,最终呈现裂缝半长短、复杂指数高的特征。针对该类储层,应采用前置高黏度降滤失,后续中低黏度促缝网复杂的压裂工艺配合小粒径支撑剂超前暂堵[29-31],实现“控近扩远”,构建足够大的泄气面积,该压裂对策的关键在于“主动控滤、立体支撑、均衡改造”。
选取沁水盆地长治地区B水平井为研究对象,采用研究模型反演压裂后裂缝参数。该井目的层下二叠统山西组3号煤层以原生-碎裂结构为主,局部含粒状、鳞片状软煤分层,内生裂隙密度6~15条/5 cm,外生裂隙密度1~3条/5 cm,该区块煤体结构较完整、裂隙系统规则,裂缝扩展迂曲度中等,故将迂曲度参数设为1.7~1.8。
由图6反演结果可知:模型反演得到该储层压裂平均裂缝半长134.9 m,平均复杂指数6.05,主裂缝表面积占比14.29%,次级裂缝占比77.5%,表明压裂改造以单一主裂缝为骨架,伴生大量次级裂缝,构成长而简单的缝网形态。图8的停泵压降曲线进一步印证,该储层缝网以水力主裂缝为核心,次级裂缝为主体,沟通割理较少,其缝网发育特征的主控因素为压裂液滤失,较少的裂缝界面使滤失量低,支撑主裂缝稳定延伸,且停泵阶段裂缝闭合过程无显著非均质性。
对比图7和图8可知:与A井相比,B井裂缝半长更长、复杂指数更低,差异主要源于煤体结构和滤失效应的不同:A井煤体破碎、强度低,压裂易形成短而复杂的缝网,大量裂缝界面加剧滤失,限制主裂缝延伸;B井煤体完整、强度高,滤失量小,主裂缝可稳定扩展。A、B井的停泵压降曲线响应与模型反演结果吻合,验证了模型的准确性。针对该类储层,应优先采用中高黏度的压裂液体系,并适当提高排量和砂比[32],确保支撑剂能够被有效携带至裂缝远端,形成长而导流能力强的支撑裂缝。压裂策略应侧重于“撑好主缝、适度复杂”,利用其良好地质条件构建以高导流主裂缝为核心的高效缝网系统是进一步提高产能的核心。
选取鄂尔多斯盆地C井本溪组8号深部煤层为研究对象,煤层以光亮煤、半亮煤为主,内生裂隙发育,割理密度7~8条/5 cm,为模型反演提供可靠的地质条件。该深部煤层在高闭合应力作用下裂缝扩展路径相对规则,将迂曲度取值设定为1.5~1.7。该煤层采用分段多簇体积压裂,注入压裂液20 220.5 m3、支撑剂3 600 m3。
模型反演得到该储层压裂裂缝平均半长178.21 m,平均复杂指数3.67,主裂缝表面积占比22.08%,次级裂缝占比77.92%,且无沟通割理的表面积,表明深部煤岩压裂改造以单一主裂缝为主,伴随大量次级裂缝生成,形成长而简单的缝网形态。该储层埋深大导致垂向应力高,裂缝难以沟通割理,主要沿最小主应力方向扩展,仅能形成次级裂缝,因此,复杂指数更低。
对比图8和图9可知:由于滤失效应的差异,B井煤体破碎度高、强度低,压裂易发育短而复杂的缝网,大量裂缝界面加剧滤失,限制主裂缝延伸;C井则因裂缝界面较少,滤失量低,支撑主裂缝稳定延伸,停泵阶段裂缝闭合过程无显著非均质性。因此,C井的停泵压降曲线因滤失非均质性呈现显著的多级裂缝闭合拐点,而B井曲线无明显驼峰。针对该类储层,应采用大排量、段塞式的泵注程序[33-34],利用流体动能强制撑开更多裂隙,并结合暂堵剂,实现缝网内的多次转向,最大化增加裂缝复杂度,压裂策略需转向“主动造复杂、沟通天然缝”为主导。
1) 针对煤层气压裂过程中多尺度缝网闭合评价难题,耦合物质平衡原理与压力瞬态分析方法,基于裂缝多级闭合机制建立了停泵压降解析模型。通过推导裂缝体积、滤失量与G函数之间的定量关系,构建了可反演裂缝表面积、等效半长及复杂指数的解析模型,实现了对压裂后裂缝网络几何形态与闭合特征的定量表征;
2) 浅层碎粒煤压裂形成短而复杂的缝网(半长101.5 m,复杂指数10.03),以次级裂缝为主(占比52.17%)。煤岩破碎导致高滤失,严重制约主裂缝延伸,压降曲线呈多级闭合拐点,利用前置高黏控制滤失,实现“控近扩远”是关键;
3) 中浅层高阶煤压裂形成长而简单的缝网(半长134.9 m,复杂指数6.05),主裂缝骨架清晰(占比14.29%)。煤体完整、滤失低,保障主裂缝稳定延伸,压降曲线平滑。构建以高导流主裂缝为核心的高效缝网系统是核心;
4) 深部煤岩压裂形成较长但极简单的主缝(半长178.21 m,复杂指数3.67),主裂缝主导(占比22.08%)。高地应力抑制缝网复杂化,沟通天然裂缝(割理)能力差。结合缝内暂堵剂,实现缝网内的多次转向,最大化增加裂缝复杂度是必然;
5) 煤体完整性和地应力条件共同主导裂缝网络的发育模式:碎粒煤因破碎、滤失严重抑制主裂缝延伸;原生结构煤和深部煤滤失程度较低,主裂缝可稳定扩展,但深部煤受高应力环境制约,分支裂缝难以生成,限制了缝网向复杂化方向发展。

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2026年第16卷第5期
18
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doi: 10.13809/j.cnki.cn32-1825/te.20250113
  • 接收时间:2025-12-31
  • 首发时间:2026-10-30
  • 出版时间:2026-09-26
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  • 收稿日期:2025-12-31
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    1 西南石油大学油气藏地质及开发工程全国重点实验室,四川   成都 610500
    2 西南石油大学石油与天然气工程学院,四川   成都 610500
    3 新疆亚新煤层气资源技术研究有限责任公司,新疆   乌鲁木齐 830063

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翟利晓(2000—),男,在读硕士研究生,主要从事煤层(岩)气压裂参数智能反演相关研究。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
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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