Article(id=1149781959678849703, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403143, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1714233600000, receivedDateStr=2024-04-28, revisedDate=1734624000000, revisedDateStr=2024-12-20, acceptedDate=null, acceptedDateStr=null, onlineDate=1752058981102, onlineDateStr=2025-07-09, pubDate=1743091200000, pubDateStr=2025-03-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752058981102, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752058981102, creator=13701087609, updateTime=1752058981102, updator=13701087609, issue=Issue{id=1149781952959574654, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='9', pageStart='3529', pageEnd='3967', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752058979501, creator=13701087609, updateTime=1776333392421, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1251596220226027613, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1251596220226027614, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3664, endPage=3671, ext={EN=ArticleExt(id=1149781960106668715, articleId=1149781959678849703, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Optimization of Key Parameters for Fracturing Operation in Shallow Tight Oil Reservoirs, columnId=1156262729003422020, journalTitle=Science Technology and Engineering, columnName=Papers·Petroleum and Natural Gas Industry, runingTitle=null, highlight=null, articleAbstract=

The tight oil reservoirs in the eastern Ordos Basin are characterized by shallow burial, low pressure, small principal geostress, and low fracture pressure, which are significantly different from the general mid-deep tight oil reservoirs. Previously, the development of horizontal wells in this area through hydraulic fracturing was mainly based on field experience, and the design of the fracturing construction lacked a theoretical foundation, making the impact pattern of construction parameters unclear and the enhancement of production effect uncertain. Hence, research on the optimization of key parameters in fracturing construction is urgently needed. To maximize production efficiency, an integrated research method involving fracturing simulation and numerical reservoir simulation has been adopted. FrSmart has been used for fracturing simulation, Petrel for building geological reservoir models, and tNavigator for numerical simulation. Through the comprehensive application of various numerical simulation software, optimal cluster spacing, displacement, and single-segment fluid volume suitable for horizontal well fracturing in the reservoir were determined. By adjusting the conventional volume fracturing process parameters of well YCN-1 in the study area to a cluster spacing of 20 m, a displacement of 12 m3/min, and increasing the single-segment fluid volume to 1 000 m3, significant improvements in fracturing and production enhancement effects were achieved. Field test results show that the production of well YCN-1 after optimizing fracturing parameters is 29.98% and 50.27% higher than that of the unoptimized wells N-2 and N-3, respectively. Therefore, a method of critical significance for guiding the fracturing construction of shallow tight oil reservoirs, enhancing fracturing efficiency, and improving production effects has been proposed.

, correspAuthors=Yue-tian LIU, 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=Ping-tian FAN, Yue-tian LIU, Jing-tao DUAN, Mao-zong GAN, Xiao-wen YANG, Xian-kun SONG, Cheng-zhi LIU), CN=ArticleExt(id=1149782004348187620, articleId=1149781959678849703, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=浅层致密油藏压裂施工关键参数优化, columnId=1156262729603207500, journalTitle=科学技术与工程, columnName=论文·石油、天然气工业, runingTitle=null, highlight=null, articleAbstract=

鄂尔多斯盆地东部致密油藏储层浅,压力低,地应力主值小,破裂压力低,明显不同于一般中深层致密油藏。此前该区域油藏水平井压裂开发主要依赖现场经验,压裂施工设计缺少理论依据,施工参数影响规律不清楚,增产效果难以保证,亟须开展压裂施工关键参数优化研究。以产能效益最大化为目标,通过压裂模拟与油藏数值模拟一体化研究方法,使用FrSmart进行压裂模拟、Petrel构建油藏地质模型和tNavigator进行数值模拟,综合运用多种模拟软件对压裂施工关键参数进行优化设计,最终得到了适合该油藏水平井压裂施工的最优簇间距、排量和单段液量。通过调整研究区YCN-1井常规体积压裂工艺参数,簇间距改用20 m,排量12 m3/min,单段液量增至1 000 m3,显著提高了压裂和增产效果。现场试验结果表明,压裂参数优化后的YCN-1井产量比未优化的N-2、N-3井高出29.98%和50.27%。可见该方法对于指导浅层致密油藏压裂施工、提升压裂效率和增产效果具有重要的指导意义。

, correspAuthors=刘月田, authorNote=null, correspAuthorsNote=
* 刘月田(1965—),男,汉族,河北无极人,博士,教授,博士研究生导师。研究方向:油藏渗流力学、数值模拟及开发。E-mail:
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樊平天(1980—),男,汉族,甘肃玉门人,博士研究生,高级工程师。研究方向:油气田开发。E-mail:

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樊平天(1980—),男,汉族,甘肃玉门人,博士研究生,高级工程师。研究方向:油气田开发。E-mail:

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Fracture modeling parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
模型参数 数据
水平最小主应力/MPa 11.9
水平最大主应力/MPa 26.0
垂向应力/MPa 18.2
弹性模量/GPa 20
泊松比 0.25
断裂韧性/(MPa·m-0.5) 1.5
滤失系数/(m·min-0.5) 1.3×10-4
孔眼直径/mm 10
压裂液黏度/(mPa·s) 1.6
支撑剂平均粒径/mm 0.15
支撑剂视密度/(kg·m-3) 2 500
), ArticleFig(id=1251249376409105345, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=CN, label=表1, caption=

裂缝建模参数

, figureFileSmall=null, figureFileBig=null, tableContent=
模型参数 数据
水平最小主应力/MPa 11.9
水平最大主应力/MPa 26.0
垂向应力/MPa 18.2
弹性模量/GPa 20
泊松比 0.25
断裂韧性/(MPa·m-0.5) 1.5
滤失系数/(m·min-0.5) 1.3×10-4
孔眼直径/mm 10
压裂液黏度/(mPa·s) 1.6
支撑剂平均粒径/mm 0.15
支撑剂视密度/(kg·m-3) 2 500
), ArticleFig(id=1251249376539128779, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=EN, label=Table 2, caption=

Oil-water relative permeability

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水相饱
和度Sw
水相相对
渗透率Krw
油相相对
渗透率Kro
水相饱
和度Sw
水相相对
渗透率Krw
油相相对
渗透率Kro
0.379 1 0.000 0 1.000 0 0.633 7 0.197 9 0.081 7
0.519 9 0.010 0 0.389 4 0.640 7 0.215 3 0.068 3
0.539 4 0.014 9 0.322 5 0.647 0 0.235 5 0.058 8
0.565 6 0.047 7 0.251 2 0.673 5 0.325 7 0.016 0
0.587 4 0.090 3 0.190 0 0.682 9 0.363 0 0.005 5
0.602 6 0.119 6 0.155 0 0.690 3 0.404 0 0.001 4
0.625 3 0.173 5 0.098 5 0.693 8 0.441 5 0.000 6
), ArticleFig(id=1251249376643986389, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=CN, label=表2, caption=

油水相渗曲线

, figureFileSmall=null, figureFileBig=null, tableContent=
水相饱
和度Sw
水相相对
渗透率Krw
油相相对
渗透率Kro
水相饱
和度Sw
水相相对
渗透率Krw
油相相对
渗透率Kro
0.379 1 0.000 0 1.000 0 0.633 7 0.197 9 0.081 7
0.519 9 0.010 0 0.389 4 0.640 7 0.215 3 0.068 3
0.539 4 0.014 9 0.322 5 0.647 0 0.235 5 0.058 8
0.565 6 0.047 7 0.251 2 0.673 5 0.325 7 0.016 0
0.587 4 0.090 3 0.190 0 0.682 9 0.363 0 0.005 5
0.602 6 0.119 6 0.155 0 0.690 3 0.404 0 0.001 4
0.625 3 0.173 5 0.098 5 0.693 8 0.441 5 0.000 6
), ArticleFig(id=1251249376744649691, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=EN, label=Table 3, caption=

Fracture parameters under different cluster spacing

, figureFileSmall=null, figureFileBig=null, tableContent=
簇间距/m 平均
半缝长/m
平均
缝高/m
平均
开度/mm
支撑
开度/mm
30 170 16.2 3.11 0.12
20 170 18.5 2.62 0.11
10 150 20.7 2.21 0.11
), ArticleFig(id=1251249376853701601, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=CN, label=表3, caption=

不同簇间距下裂缝参数

, figureFileSmall=null, figureFileBig=null, tableContent=
簇间距/m 平均
半缝长/m
平均
缝高/m
平均
开度/mm
支撑
开度/mm
30 170 16.2 3.11 0.12
20 170 18.5 2.62 0.11
10 150 20.7 2.21 0.11
), ArticleFig(id=1251249376950170600, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=EN, label=Table 4, caption=

Fracture parameters under different displacement

, figureFileSmall=null, figureFileBig=null, tableContent=
排量/
(m3·min-1)
平均半
缝长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
8 150 16.2 2.56 0.14
12 160 18.5 2.62 0.11
16 170 18.5 2.65 0.11
), ArticleFig(id=1251249377050833902, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=CN, label=表4, caption=

不同排量下裂缝参数

, figureFileSmall=null, figureFileBig=null, tableContent=
排量/
(m3·min-1)
平均半
缝长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
8 150 16.2 2.56 0.14
12 160 18.5 2.62 0.11
16 170 18.5 2.65 0.11
), ArticleFig(id=1251249377155691508, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=EN, label=Table 5, caption=

Fracture parameters under different fluid volume

, figureFileSmall=null, figureFileBig=null, tableContent=
单段液
量/m3
平均半缝
长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
单段液
量/m3
平均半缝
长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
840 170 18.5 2.62 0.11 1 260 200 20.7 2.52 0.13
1 050 182.5 20.7 2.38 0.12 1 470 210 20.7 2.56 0.14
), ArticleFig(id=1251249377273132029, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149781959678849703, language=CN, label=表5, caption=

不同液量下裂缝参数

, figureFileSmall=null, figureFileBig=null, tableContent=
单段液
量/m3
平均半缝
长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
单段液
量/m3
平均半缝
长/m
平均缝
高/m
平均开
度/mm
支撑开
度/mm
840 170 18.5 2.62 0.11 1 260 200 20.7 2.52 0.13
1 050 182.5 20.7 2.38 0.12 1 470 210 20.7 2.56 0.14
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浅层致密油藏压裂施工关键参数优化
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樊平天 1, 2 , 刘月田 1, * , 段景涛 2 , 甘茂宗 1 , 杨潇文 1 , 宋宪坤 1 , 刘程郅 1
科学技术与工程 | 论文·石油、天然气工业 2025,25(9): 3664-3671
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科学技术与工程 | 论文·石油、天然气工业 2025, 25(9): 3664-3671
浅层致密油藏压裂施工关键参数优化
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樊平天1, 2 , 刘月田1, * , 段景涛2, 甘茂宗1, 杨潇文1, 宋宪坤1, 刘程郅1
作者信息
  • 1 中国石油大学(北京)石油工程学院, 北京 102249
  • 2 延长油田股份有限公司南泥湾采油厂, 延安 716000
  • 樊平天(1980—),男,汉族,甘肃玉门人,博士研究生,高级工程师。研究方向:油气田开发。E-mail:

通讯作者:

* 刘月田(1965—),男,汉族,河北无极人,博士,教授,博士研究生导师。研究方向:油藏渗流力学、数值模拟及开发。E-mail:
Optimization of Key Parameters for Fracturing Operation in Shallow Tight Oil Reservoirs
Ping-tian FAN1, 2 , Yue-tian LIU1, * , Jing-tao DUAN2, Mao-zong GAN1, Xiao-wen YANG1, Xian-kun SONG1, Cheng-zhi LIU1
Affiliations
  • 1 College of Petroleum Engineering, China University of Petroleum, Beijing 102249, China
  • 2 Nanniwan Oil Production Plant, Yanchang Oilfield Co., Ltd., Yan’an 716000, China
出版时间: 2025-03-28 doi: 10.12404/j.issn.1671-1815.2403143
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鄂尔多斯盆地东部致密油藏储层浅,压力低,地应力主值小,破裂压力低,明显不同于一般中深层致密油藏。此前该区域油藏水平井压裂开发主要依赖现场经验,压裂施工设计缺少理论依据,施工参数影响规律不清楚,增产效果难以保证,亟须开展压裂施工关键参数优化研究。以产能效益最大化为目标,通过压裂模拟与油藏数值模拟一体化研究方法,使用FrSmart进行压裂模拟、Petrel构建油藏地质模型和tNavigator进行数值模拟,综合运用多种模拟软件对压裂施工关键参数进行优化设计,最终得到了适合该油藏水平井压裂施工的最优簇间距、排量和单段液量。通过调整研究区YCN-1井常规体积压裂工艺参数,簇间距改用20 m,排量12 m3/min,单段液量增至1 000 m3,显著提高了压裂和增产效果。现场试验结果表明,压裂参数优化后的YCN-1井产量比未优化的N-2、N-3井高出29.98%和50.27%。可见该方法对于指导浅层致密油藏压裂施工、提升压裂效率和增产效果具有重要的指导意义。

致密油藏  /  压裂模拟  /  数值模拟  /  参数优化

The tight oil reservoirs in the eastern Ordos Basin are characterized by shallow burial, low pressure, small principal geostress, and low fracture pressure, which are significantly different from the general mid-deep tight oil reservoirs. Previously, the development of horizontal wells in this area through hydraulic fracturing was mainly based on field experience, and the design of the fracturing construction lacked a theoretical foundation, making the impact pattern of construction parameters unclear and the enhancement of production effect uncertain. Hence, research on the optimization of key parameters in fracturing construction is urgently needed. To maximize production efficiency, an integrated research method involving fracturing simulation and numerical reservoir simulation has been adopted. FrSmart has been used for fracturing simulation, Petrel for building geological reservoir models, and tNavigator for numerical simulation. Through the comprehensive application of various numerical simulation software, optimal cluster spacing, displacement, and single-segment fluid volume suitable for horizontal well fracturing in the reservoir were determined. By adjusting the conventional volume fracturing process parameters of well YCN-1 in the study area to a cluster spacing of 20 m, a displacement of 12 m3/min, and increasing the single-segment fluid volume to 1 000 m3, significant improvements in fracturing and production enhancement effects were achieved. Field test results show that the production of well YCN-1 after optimizing fracturing parameters is 29.98% and 50.27% higher than that of the unoptimized wells N-2 and N-3, respectively. Therefore, a method of critical significance for guiding the fracturing construction of shallow tight oil reservoirs, enhancing fracturing efficiency, and improving production effects has been proposed.

tight oil reservoir  /  fracture simulation  /  numerical simulation  /  parameter optimization
樊平天, 刘月田, 段景涛, 甘茂宗, 杨潇文, 宋宪坤, 刘程郅. 浅层致密油藏压裂施工关键参数优化. 科学技术与工程, 2025 , 25 (9) : 3664 -3671 . DOI: 10.12404/j.issn.1671-1815.2403143
Ping-tian FAN, Yue-tian LIU, Jing-tao DUAN, Mao-zong GAN, Xiao-wen YANG, Xian-kun SONG, Cheng-zhi LIU. Optimization of Key Parameters for Fracturing Operation in Shallow Tight Oil Reservoirs[J]. Science Technology and Engineering, 2025 , 25 (9) : 3664 -3671 . DOI: 10.12404/j.issn.1671-1815.2403143
致密油气作为非常规油气资源的重要组成部分,可采资源储量巨大、开发技术也日益成熟,正成为全球非常规油气开发的又一重点领域[1-2]。浅层致密油藏储层原始地层压力低,非均质性强,单井产量低,基本无自然工业产能,需要压裂才能有效开发[3-4]。合理的压裂施工参数可以提高压裂效果,增加产能,降低成本,延长井寿命,开展浅层致密油藏压裂施工参数优化研究意义重大。
在鄂尔多斯盆地东部某浅层致密油藏的水平井早期开发阶段,采用瓜胶为主体连续加砂方式压裂,压裂参数设计主要依赖现场经验,段簇间距过大、排量和液量偏小[5]。压裂施工设计缺少理论依据,施工参数影响规律未明确,导致段与段之间压裂改造不充分,不能有效连通,增产改造效果不理想。为实现致密油藏的高效开发,亟须开展以生产效益为目标的压裂施工关键参数优化。
国内外不同学者针对压裂施工参数优化研究主要包括解析法、统计算法、数值模拟和机器学习等方法[6-7]。Heger等[8]结合产能图表和解析公式揭示了有效井眼半径与裂缝之间的关系,对水平井压裂参数优化进行了有效指导。肖阳等[9]通过建立三维地质力学模型,研究排量、液量、砂比、射孔层位厚度等参数对裂缝纵向和平面延伸规律的影响,优化压裂设计。姚锋盛等[10]利用压裂软件对施工液量、排量、加砂量等参数进行模拟分析,从而优化二次加砂压裂施工参数。郭大立等[11]通过使用灰色关联分析法对施工参数进行排序,然后利用粒子群算法构建日产气量最优化模型,反演出最优压裂施工参数。Min等[12]利用机器学习模型预测水力压裂后煤层气井产量,捕捉因子与输出之间潜在的非线性关系,对压裂方案进行优化,并通过数值模拟验证其有效性。
众多参数与压裂效果之间并非简单的函数关系,解析法很难用单一表达式揭示各因素之间的复杂联系。非常规裂缝模拟软件常以压裂改造体积最大化为目标,未考虑后续生产过程,难以准确评价压裂施工参数对产能的影响。研究区最近才开始改用低黏滑溜水[13]压裂液体系进行水力压裂,现场数据有限,所以基于数据驱动机器学习方法目前不太适用。致密油藏压裂施工参数优化是一个复杂的问题,需要综合考虑多种因素。不同的研究方法和技术在不同的致密油藏类型和开发条件下都有其适用性和局限性[14]
现以产能最大化为目标,采用裂缝模拟与数值模拟相结合的油藏动态评价方法,将压裂施工参数与后期生产模拟时采用的裂缝参数建立直接的联系,进行浅层致密油藏的压裂参数优化研究和现场实施评价。首先,使用中国石油勘探开发研究院自研的FrSmart[15]软件模拟得到不同施工参数条件下浅层致密油藏水平井分段多簇压裂形成的裂缝形态;在Petrel[16]软件中建立地质模型,按照所得裂缝拓展参数对水平井进行相应射孔和压裂操作,并进行局部网格加密;随后将构建好的裂缝模型导入tNavigator[17]进行数值模拟,分析不同因素对压裂水平井产量的影响,对簇间距、排量和液量这3个关键参数进行优化研究;最后通过现场实施和效果跟踪分析,验证优化参数的有效性和实用性,为其他区域致密油藏高效开发提供技术借鉴。
首先收集研究区226口水平井的产量、地质概况以及压裂施工参数等数据,进行整理和标准化。然后以产量为目标函数,地质与工程等参数为自变量,使用皮尔逊相关系数分析各因素间的相关性,结果如图1所示。
图1可知,与水平井的产量相关性较大(相关系数绝对值大于0.5)的施工参数有压裂簇间距、单段液量和施工排量,地质因素有基质孔隙度与渗透率。主要考虑施工参数压裂簇间距、单段液量和施工排量对水平井产能的影响,且这三者之间的相关性较低(相关系数绝对值小于0.1),因此采用单因素分析法进行模拟研究。
根据相关性分析结果,采用FrSmart软件模拟浅层致密油藏水平井分段多簇压裂形成的裂缝系统,得到不同簇间距、压裂液量、排量等施工参数影响下的水力裂缝起裂和扩展的详细参数。模拟目标油藏的储层埋深为1 000 m,水平井段长度为1 200 m。裂缝建模参数的选取主要借鉴了现场实际施工的数据和参考以往的研究成果[18],并进行了适当的修改和调整,如表1所示,模拟所得的裂缝扩展形态如图2所示。
油藏模型的建立参数选取同样借鉴了油藏实际地质概况和以往的研究成果。油藏数值模型的网格单元划分为400×21×11,共92 400个网格。网格步长设置为x方向5 m,y方向50 m,z方向2 m,油藏顶深1 000 m。岩石密度2.4 g/cm3,原始地层压力为5.50 MPa。
流体参数如下:地面原油密度为0.842 g/cm3,黏度为4.17 mPa·s;地层水密度为1.015 g/cm3,黏度为0.356 5 mPa·s,初始含水饱和度为40%,参考压力为55.6×105 Pa,体积系数为1,压缩系数为4.1×10-5 MPa-1。模拟所用油水相渗曲线数据如表2所示。
基质系统参数如下: 孔隙度10%,X方向渗透率0.1 mD,Y方向渗透率0.1 mD,Z方向渗透率0.05 mD。
裂缝系统参数如下:裂缝网格加密(LGR)数量为65,加密后总网格数增加至339 548。按照裂缝导流能力换算,加密裂缝中心网格渗透率600 mD,周围网格渗透率50 mD,裂缝孔隙度1%。
在Petrel软件中建立上述地质模型,采用FrSmart软件所得裂缝拓展参数对水平井进行射孔和压裂等操作,如图3所示。随后对水力裂缝进行局部网格加密,并修改裂缝区域渗透率,如图4所示。接下来将在Petrel中构建好的水平井裂缝模型导入tNavigator进行数值模拟。工作制度采用注入滑溜水压裂液后先焖井一个月,随后开井定井底流压3 MPa生产1年。
簇间距是水平井压裂的重要参数,FrSmart软件压裂模拟所得不同簇间距下的裂缝缝长、开度和缝高等数据,如表3所示。根据所依次建立簇间距为10、20、30 m的裂缝油藏数值模型,其在模拟最后时间步的压力属性的裂缝网格形态如图5所示。
FrSmart软件压裂模拟所得不同排量下的裂缝缝长、开度和缝高等数据,如表4所示。根据所依次建立排量为8、12、16 m3/min的数值模型。其在模拟最后时间步的压力属性的裂缝网格形态如图6所示。
FrSmart软件压裂模拟所得不同液量下的裂缝缝长、开度和缝高等数据,如表5所示。根据所建立单段液量为840、1 050、1 260、1 470 m3的裂缝油藏数值模型,其在模拟最后时间步的压力属性的裂缝网格形态如图7所示。
对簇间距为10、20、30 m的裂缝数值模型进行计算,整理得到的油井产量数据,结果如图8所示。
对比簇间距分别为10、20、30 m的产量结果,可知裂缝簇间距与产量间存在拐点,当裂缝簇间距为20 m时,最终产量为5 657.69 m3,大于簇间距为10 m的产量(5 155.7 m3)和30 m的产量(4 842.19 m3)。
簇间距对压裂改造效果及生产效果都有明显的影响。簇间距过小,会导致主裂缝之间的改造效果重合,降低压裂改造效率;簇间距过大,压裂裂缝间互不连通,会导致改造不彻底,造成油藏资源浪费。合理控制簇间距有利于形成复杂裂缝,从而提高产量,该油藏建议簇间距为20 m。
对排量为8、12、16 m3/min的裂缝数值模型进行计算,得到的油井产量数据如图9所示。
对比排量分别为8、12、16 m3/min的产量结果,可知施工排量与产量间也存在拐点,当施工排量为12 m3/min时,最终产量为5 058.74 m3,大于排量为16 m3/min的产量(4 759.81 m3)和8 m3/min的产量(4 558.46 m3)。
压裂液施工排量越大,压裂缝缝长、缝高、开度均增加,在一定范围内可以较大地提升油井的产量;但同时支撑裂缝开度随排量增加反而减小,过高的排量不利于支撑剂在裂缝中的运移与铺置,该油藏建议排量为12 m3/min。
对单段液量为840、1 050、1 260、1 470 m3的裂缝数值模型进行计算,对得到的油井产量数据进行整理,结果如图10所示。
对比单段液量分别为840、1 050、1 260、1 470 m3的产量结果,当液量为1 470 m3时,最终产量为7 143.93 m3,大于液量为1 260、1 050、840 m3的产量(6 386.2 、5 464.71、3 966.17 m3)。
可以发现使用的液量和最终产量成正相关,但增加幅度逐渐减小。增加单段液量可以提高压裂液在地层中的覆盖面积和深度,对地层能量有一定补充,从而增加有效压裂面积和压裂效果,进而增加产量。但液量增加过大会导致压裂液分布不均,有可能形成“油水分层”,降低产量增速。在实际生产时需要同时考虑经济效益与环境问题,选取经济高效且环境友好的液量范围,该油藏建议单段液量为1 050~1 260 m3
YCN-1井目标油层为延长组长6致密储层,天然裂缝较为发育,原油密度为0.84 g/cm3,50℃时黏度为4.5 mPa·s,孔隙度峰值位于8%~11%,渗透率峰值位于0.09~0.52 mD;水平井段长度为735 m,目的层厚度17 m,地层压力3.5 MPa,这些地层条件与上文模拟参数基本一致。按照优化后参数进行8段压裂施工,排量以12 m3/min,每段射孔5簇,簇间距20 m,段间距也是20 m,单段液量1 016 m3。在YCN-1井压裂施工过程中同步进行了微地震监测,监测结果如图11所示。
YCN-1井共压裂8段,监测7段316个事件点,由于埋深较浅,压力系数较低,岩石破裂能量较低,震级较小,集中在-3.56~-2.66。整体来看压裂裂缝东西两翼扩展长度基本相等,裂缝网络内微地震事件密度较大,改造较为充分。各段微地震事件紧密相连但又没有重复改造现象,段间距簇间距设计较为合理。
压裂施工参数优化后的YCN-1井与未优化的N-2、N-3井累产量对比如图12所示。
YCN-1井投产560 d,累计生产原油3 100 m3,高于其他未进行压裂施工参数优化的井如N-2井与N-3井,累产油量为2 385 m3和2 063 m3,增加幅度29.98%和50.27%。YCN-1井累产液量7 294 m3,高于N-2和N-3井的4 379 m3和4 160 m3,增加幅度66.56%和75.34%。YCN-1井含水率57.4%,略高于N-2井和N-3井的45.5%和50.4%。更大的施工液量意味着更大的产液量,同时也有着更大的产油量。
以生产效益最大化为目标,结合压裂模拟与数值模拟,对某浅层致密油藏进行压裂施工关键参数优化,主要结论如下。
(1) 随着簇间距的减小,受缝间干扰影响,裂缝长度、开度均减小,但缝高逐渐增大;当簇间距过大时,改造体积增速减缓,易导致改造不彻底。从产量角度来看,簇间距20 m时压裂缝渗流控制范围最大,水平井产能最高。
(2) 压裂液排量越大,压裂缝缝长和缝高均增加,但支撑裂缝开度反而减小,表明排量过高不利于支撑剂的运移与铺置,该区域建议压裂施工排量为12 m3/min。
(3) 随施工液量增加,压裂缝缝长、缝高、开度均增加,缝长增加最为显著;但当压裂液量持续增加时,裂缝缝长与导流能力增加明显减缓,考虑生产成本与环境问题,建议单段液量1 050~1 260 m3
  • 国家自然科学基金(52274048)
  • 北京市自然科学基金(3222037)
  • 陕西省技术创新引导专项计划(2023-YD-CGZH-02)
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2025年第25卷第9期
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doi: 10.12404/j.issn.1671-1815.2403143
  • 接收时间:2024-04-28
  • 首发时间:2025-07-09
  • 出版时间:2025-03-28
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  • 收稿日期:2024-04-28
  • 修回日期:2024-12-20
基金
国家自然科学基金(52274048)
北京市自然科学基金(3222037)
陕西省技术创新引导专项计划(2023-YD-CGZH-02)
作者信息
    1 中国石油大学(北京)石油工程学院, 北京 102249
    2 延长油田股份有限公司南泥湾采油厂, 延安 716000

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* 刘月田(1965—),男,汉族,河北无极人,博士,教授,博士研究生导师。研究方向:油藏渗流力学、数值模拟及开发。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
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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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