Article(id=1322917034648019258, tenantId=1146029695717560320, journalId=1281212831689347082, issueId=1322916945741348911, articleNumber=null, orderNo=null, doi=10.14075/j.jgg.2025.12.445, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1766678400000, receivedDateStr=2025-12-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793337599670, onlineDateStr=2026-10-30, pubDate=1789401600000, pubDateStr=2026-09-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793337599670, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793337599670, creator=13701087609, updateTime=1793337599670, updator=13701087609, issue=Issue{id=1322916945741348911, tenantId=1146029695717560320, journalId=1281212831689347082, year='2026', volume='46', issue='9', pageStart='1039', pageEnd='1170', issueExtLink='null', onlineDate='null', pubDate='1789401600000', pubDateStr='2026-09-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793337578473, creator='13701087609', updateTime=1793337578473, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1080, endPage=1087, ext={EN=ArticleExt(id=1322917034811597115, articleId=1322917034648019258, tenantId=1146029695717560320, journalId=1281212831689347082, language=EN, title=Deep Reservoir In-Situ Stress Inversion via Microseismic Monitoring—A Case Study of Carbonate HDR Fracturing in Northern Jiangsu, columnId=null, journalTitle=Journal of Geodesy and Geodynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

This paper proposes a novel in-situ stress inversion method. Combined with Michael's linear stress inversion and Vavryčuk's fault plane identification technology, a complete inversion workflow for in-situ stress parameters is established by adopting multi-constrained moment tensor inversion to determine focal mechanisms. Taking the carbonate hot dry rock (HDR) reservoir in the Subei basin as a case study, 90 high-quality microseismic events are selected for in-situ stress inversion. The relative magnitude of the three principal stresses follows the order of SV>SHmax>SHmin. The orientation of the maximum horizontal principal stress SHmax is approximately NW44°, and the stress shape factor R is 0.74. The inverted results are in good agreement with the in-situ stress data measured by the anelastic strain recovery (ASR) method from core samples of the same well, in terms of stress regime and principal stress orientation. This confirms the reliability and applicability of the microseismic-based stress inversion method in the study area. The proposed method can efficiently calculate in-situ stress parameters during fracturing and quantitatively characterize dynamic stress field evolution, which provides solid technical support for deep reservoir stimulation.

, authors=Xinglong XIE1, Wenhao XU1, Dong CHEN2, Qiuchen LI1, Yongbiao YANG2, Junpeng GUAN2, Xianpeng JIN1, authorsList=Xinglong XIE, Wenhao XU, Dong CHEN, Qiuchen LI, Yongbiao YANG, Junpeng GUAN, Xianpeng JIN, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., 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=1322917038670356816, articleId=1322917034648019258, tenantId=1146029695717560320, journalId=1281212831689347082, language=CN, title=基于微地震监测的深部储层地应力反演研究——以苏北碳酸盐岩型干热岩储层压裂为例, columnId=1281933709121138897, journalTitle=大地测量与地球动力学, columnName=地球动力学, runingTitle=null, highlight=null, articleAbstract=

基于大量微地震监测实践,提出基于水力压裂微地震监测的地应力反演方法,通过多约束矩张量反演震源机制,结合Michael线性应力反演与Vavryčuk断层面识别,构建地应力参数反演流程。以苏北盆地碳酸盐岩干热岩储层为例,使用优选后的90个微地震事件反演得到地应力参数,三向主应力的相对大小为SV>SHmax >SHmin,最大水平主应力SHmax方向约为NW44°,应力形状因子R为0.74。该反演结果与同井滞弹性应变恢复(ASR)法岩心实测地应力数据在应力类型、主应力方位上高度吻合,验证了微地震地应力反演方法的场地适用性。本文提出的地应力反演方法可快速计算压裂期内的地应力参数,量化压裂过程中应力场的变化,为深部储层改造提供有力支撑。

, authors=谢兴隆1, 许文豪1, 陈冬2, 李秋辰1, 杨用彪2, 关俊朋2, 金显鹏1, authorsList=谢兴隆, 许文豪, 陈冬, 李秋辰, 杨用彪, 关俊朋, 金显鹏, authorCompany=null, correspAuthors=null, authorNote=

谢兴隆,高级工程师,主要从事地球物理勘探与方法研究工作,E-mail:

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Directions and normalized eigenvalues of principal stresses

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应力轴 方位/(°) 俯角/(°) 应力特征值 形状因子
SV(σ1) 87.05 50.20 -1 0.74
SHmax(σ2) 315.73 28.82 0.28
SHmin(σ3) 210.93 24.91 0.72
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主应力轴方向与归一化特征值

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应力轴 方位/(°) 俯角/(°) 应力特征值 形状因子
SV(σ1) 87.05 50.20 -1 0.74
SHmax(σ2) 315.73 28.82 0.28
SHmin(σ3) 210.93 24.91 0.72
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In-situ stress measurement results by ASR method

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编号 取样深度/m SHmax/ MPa SHmin/ MPa SV/ MPa SHmax方向
ASR-4 4 700 77.0 75.1 85.4 NW80°
ASR-5 4 702 75.8 71.0 85.4 NW65°
ASR-6 4 703 81.1 80.2 85.4 NW22°
ASR-7 4 704 77.0 72.1 85.4 NW31°
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ASR法地应力测量结果

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编号 取样深度/m SHmax/ MPa SHmin/ MPa SV/ MPa SHmax方向
ASR-4 4 700 77.0 75.1 85.4 NW80°
ASR-5 4 702 75.8 71.0 85.4 NW65°
ASR-6 4 703 81.1 80.2 85.4 NW22°
ASR-7 4 704 77.0 72.1 85.4 NW31°
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基于微地震监测的深部储层地应力反演研究——以苏北碳酸盐岩型干热岩储层压裂为例
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谢兴隆 1 , 许文豪 1 , 陈冬 2 , 李秋辰 1 , 杨用彪 2 , 关俊朋 2 , 金显鹏 1
大地测量与地球动力学 | 地球动力学 2026,46(9): 1080-1087
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大地测量与地球动力学 |地球动力学 2026 , 46 (9) : 1080 -1087
基于微地震监测的深部储层地应力反演研究——以苏北碳酸盐岩型干热岩储层压裂为例
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谢兴隆1 , 许文豪1, 陈冬2, 李秋辰1, 杨用彪2, 关俊朋2, 金显鹏1
作者信息
  • 1 中国地质调查局水文地质环境地质调查中心, 天津, 300309
  • 2 江苏省地质调查研究院, 南京, 210008
作者简介:

谢兴隆,高级工程师,主要从事地球物理勘探与方法研究工作,E-mail:

Deep Reservoir In-Situ Stress Inversion via Microseismic Monitoring—A Case Study of Carbonate HDR Fracturing in Northern Jiangsu
Xinglong XIE1 , Wenhao XU1, Dong CHEN2, Qiuchen LI1, Yongbiao YANG2, Junpeng GUAN2, Xianpeng JIN1
Affiliations
  • 1 Center for Hydrogeology and Environmental Geology Survey, CGS, Tianjin 300309, China
  • 2 Geological Survey of Jiangsu Province, Nanjing 210008, China
出版时间: 2026-09-15 doi: 10.14075/j.jgg.2025.12.445
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基于大量微地震监测实践,提出基于水力压裂微地震监测的地应力反演方法,通过多约束矩张量反演震源机制,结合Michael线性应力反演与Vavryčuk断层面识别,构建地应力参数反演流程。以苏北盆地碳酸盐岩干热岩储层为例,使用优选后的90个微地震事件反演得到地应力参数,三向主应力的相对大小为SV>SHmax >SHmin,最大水平主应力SHmax方向约为NW44°,应力形状因子R为0.74。该反演结果与同井滞弹性应变恢复(ASR)法岩心实测地应力数据在应力类型、主应力方位上高度吻合,验证了微地震地应力反演方法的场地适用性。本文提出的地应力反演方法可快速计算压裂期内的地应力参数,量化压裂过程中应力场的变化,为深部储层改造提供有力支撑。

微地震监测  /  震源机制  /  地应力  /  水力压裂  /  储层改造  /  干热岩

This paper proposes a novel in-situ stress inversion method. Combined with Michael's linear stress inversion and Vavryčuk's fault plane identification technology, a complete inversion workflow for in-situ stress parameters is established by adopting multi-constrained moment tensor inversion to determine focal mechanisms. Taking the carbonate hot dry rock (HDR) reservoir in the Subei basin as a case study, 90 high-quality microseismic events are selected for in-situ stress inversion. The relative magnitude of the three principal stresses follows the order of SV>SHmax>SHmin. The orientation of the maximum horizontal principal stress SHmax is approximately NW44°, and the stress shape factor R is 0.74. The inverted results are in good agreement with the in-situ stress data measured by the anelastic strain recovery (ASR) method from core samples of the same well, in terms of stress regime and principal stress orientation. This confirms the reliability and applicability of the microseismic-based stress inversion method in the study area. The proposed method can efficiently calculate in-situ stress parameters during fracturing and quantitatively characterize dynamic stress field evolution, which provides solid technical support for deep reservoir stimulation.

microseismic monitoring  /  source mechanism  /  in-situ stress  /  hydraulic fracturing  /  reservoir stimulation  /  hot dry rock (HDR)
谢兴隆, 许文豪, 陈冬, 李秋辰, 杨用彪, 关俊朋, 金显鹏. 基于微地震监测的深部储层地应力反演研究——以苏北碳酸盐岩型干热岩储层压裂为例. 大地测量与地球动力学, 2026 , 46 (9) : 1080 -1087 . DOI: 10.14075/j.jgg.2025.12.445
Xinglong XIE, Wenhao XU, Dong CHEN, Qiuchen LI, Yongbiao YANG, Junpeng GUAN, Xianpeng JIN. Deep Reservoir In-Situ Stress Inversion via Microseismic Monitoring—A Case Study of Carbonate HDR Fracturing in Northern Jiangsu[J]. Journal of Geodesy and Geodynamics, 2026 , 46 (9) : 1080 -1087 . DOI: 10.14075/j.jgg.2025.12.445
岩体变形与破裂现象本质上是应力作用的结果。实施地应力测量既能服务于各类岩体工程实践,亦可为地球动力学研究、断裂活动性评估及地质灾害预警机制提供理论支撑[1]。现有地应力测试技术体系多样,主要包括套芯应力解除法、水压致裂法、应变恢复法、钻孔崩落法及声发射法等[2]。然而,随着工程建设不断向深部发展,地应力测量及监测正面临着严峻的考验。受深度限制,深部地应力测量可应用的方法有限,成本较高。当前深部地层地应力参数获取主要有两条途径:一是基于岩石力学试验与测井资料反演分析[3];二是对目标层位取岩心开展直接测量[4]。
在深部储层改造领域,水力压裂技术广泛应用于石油、页岩气、干热岩等深部能源开发项目。尤其在干热岩开发中,压裂区应力状态对压裂效果具有决定性影响,需动态评估应力场演化。然而,压裂区裂缝形态复杂交错会导致应力场高度非均质性,传统测量手段在此场景下难以有效实施。相比之下,微地震监测作为当前压裂过程的核心地球物理监测技术[5-6],其监测成果可进一步反演获取压裂目标层的地应力信息。区别于常规地震勘探,微地震监测的核心任务在于解译震源位置、强度、发震时刻、初始振幅、震源机制及介质参数等关键信息[7]。
基于震源机制反演应力场的技术逐步成熟。早期研究多通过天然地震的震源机制解统计法反演区域构造应力场[8-9],该方法虽能揭示宏观应力格局,但精度较低,难以满足深部储层精细刻画需求。近年来,利用水力压裂诱发的微地震震源机制反演储层应力状态取得了显著进展,并在非常规页岩气等场地取得了较好的应用效果[10-13]。但已有工作多针对致密砂岩或页岩气等非常规油气藏,且多侧重于剪切型事件的DC机制反演,对深部碳酸盐岩型干热岩储层、混合破裂机制及与深孔ASR等实测应力的系统对比研究相对不足。
针对这些不足,本文在现有方法的基础上系统构建了适用于深部储层改造的微地震地应力反演技术流程,通过多约束矩张量反演获取震源机制,结合Michael线性应力反演与Vavryčuk断层面不稳定性判据,实现断层面识别与应力张量求解。本文以苏北盆地碳酸盐岩型干热岩储层为研究对象,基于R2井目标段压裂微地震监测数据优选了90次有效微地震事件,依托构建的地应力反演流程求取地应力参数。反演结果置信区间收敛效果良好,整体可信度较高。同时,将反演结果与R2井同段ASR岩心应力实测数据进行对比分析,二者在应力类型、主应力方位上高度吻合,进一步验证了本文反演方法在深部储层研究中的适用性与可靠性。
本文地应力反演流程见图 1,主要包括常规处理、震源机制计算、地应力参数迭代计算3个部分。首先,需要对微地震数据进行常规处理,主要包括速度模型、静校正、噪声压制、微地震识别及定位等内容;然后,在常规处理的基础上开展多约束条件的震源机制计算,得到震源机制矩张量;最后,采用优选的微地震事件集,开展Michael线性应力反演与Vavryčuk断层面识别,输出最优地应力参数。
矩张量反演算法种类较多,天然地震震源机制中常采用gCAP全波形反演法[14-15]。由于水力压裂微地震能量普遍较小,而基于单一约束的微地震震源机制反演所使用的信息有限,理论与实际数据在某些方面拟合程度较差。为获得拟合度较高的震源机制,本文采用混合约束方式。以波形信息约束为基础,将合成地震记录与实际地震记录的L2范数作为目标函数:
$F=\sum\limits_{n=1}^N \sum\limits_{i=1}^{N_c}\left\|\boldsymbol{V}_i^n-\boldsymbol{v}_i^n\right\|_2$
式中,N为地震记录的数量;Nc为反演中使用的波形分量数量;Vin为实际地震记录;vin为合成地震记录。
为更好地利用波形信息,将P波初动极性、振幅比等多约束条件融合,提升解的稳定性[16],建立新的目标函数:
$\begin{gathered}F=\sum\limits_{n=1}^N \sum\limits_{i=1}^{N_c}\left\{\alpha_1\left\|\boldsymbol{V}_i^n-\boldsymbol{v}_i^n\right\|_2-\alpha_2\left(\boldsymbol{V}_i^n \otimes \boldsymbol{v}_i^n\right)_{\max }+\right. \\\left.\alpha_3 f\left[P\left(\boldsymbol{V}_i^n\right), P\left(\boldsymbol{v}_i^n\right)\right]+\alpha_4 h\left[R\left(\boldsymbol{V}_i^n\right), R\left(\boldsymbol{v}_i^n\right)\right]\right\}\end{gathered}$
式中,P、R分别表示求取P波初动极性、P/S波振幅比;f[P(Vin), P(vin)]、h[R(Vin), R(vin)]分别表示实际和理论地震记录P波初动极性的拟合差、P/S波振幅比的拟合差;$ \otimes$表示互相关运算;α1~α4表示对应项的权值系数。根据新的目标函数,采用全局优化算法进行迭代反演,最终获得矩张量及其相关的断层面解。因拟合差的大小与微地震数据质量存在明显相关性,为获得较好的拟合效果,需对微地震事件进行优选。
随机选择一组震源机制开展Michael线性反演[17]。该方法假设断层面剪应力方向与滑动矢量一致,即断层面的剪切应力与滑动方向差值最小,用矩阵形式表达为:
$\boldsymbol{G T}=\boldsymbol{s}$
式中,G为根据每个震源机制断层面法向向量构成的系数矩阵;T为待求应力张量;s为由K个震源滑动方向分量构成的单位向量。
$\begin{gathered}\mathbf{G}= \\{\left[\begin{array}{ccc}n_1-n_1^3+n_1 n_3^2 & -n_2 n_1^2+n_2 n_3^2 & -n_3 n_1^2-n_3+n_3^3 \\n_2-2 n_2 n_1^2 & n_1-2 n_1 n_2^2 & -2 n_1 n_2 n_3 \\n_3-2 n_3 n_1^2 & -2 n_1 n_2 n_3 & n_1-2 n_1 n_3^2 \\-n_1 n_2^2+n_1 n_3^2 & n_2-n_2^3+n_2 n_3^2 & -n_3 n_2^2-n_3+n_3^3 \\-2 n_1 n_2 n_3 & n_3-2 n_3 n_2^2 & n_2-2 n_2 n_3^2\end{array}\right]}\end{gathered}$
式中,n1、n2、n3可由震源机制解的走向、倾角和滑动角求得。
$\boldsymbol{s}=\left[\begin{array}{lllllll}s_{11} & s_{12} & s_{13} & \cdots & s_{K 1} & s_{K 2} & s_{K 3}\end{array}\right]^{\mathrm{T}}$
各向同性介质应力状态可由对称二阶张量表征,应力张量T表达为:
$\boldsymbol{T}=\left[\begin{array}{lll}\sigma_{11} & \sigma_{12} & \sigma_{13} \\\sigma_{21} & \sigma_{22} & \sigma_{23} \\\sigma_{31} & \sigma_{32} & \sigma_{33}\end{array}\right]$
引入3个互相垂直的主应力σ1、σ2、σ3(特征值),其中σ1对应最大主应力,σ2对应中间主应力,σ3对应最小主应力,简化应力场的表述为:
$\boldsymbol{T}^{\prime}=\left[\begin{array}{ccc}\sigma_1 & 0 & 0 \\0 & \sigma_2 & 0 \\0 & 0 & \sigma_3\end{array}\right]$
Gephart等[18]定义了形状因子。形状因子可以明确地表示出三轴主应力的相对大小:
$R=\frac{\sigma_1-\sigma_2}{\sigma_1-\sigma_3}$
形状因子R的变化范围为0~1,控制了应力椭球的形状。如果σ2和σ3相等,R接近1,对应单轴压缩;如果σ2和σ1近似相等,那么R接近0,对应双轴压缩[19]。
因滑动方向不约束应力张量各向同性分量,限定迹为0:
$\operatorname{Tr}(\boldsymbol{T})=\sigma_1+\sigma_2+\sigma_3=0$
由于Michael线性反演仅能确定偏应力张量,本文对应力特征值进行无量纲处理,并采用式(9)的迹约束,使所得应力张量表示的是相对应力状态而非绝对应力幅值。最后,基于式(3)采用L2范数广义线性反演方法求取T。
震源机制有2个节面,为获得真实断层面,采用Vavryčuk[20]提出的参数I量化断层的不稳定性,具体公式为:
$I=\frac{\tau-\mu\left(\sigma-\sigma_1\right)}{\tau_c-\mu\left(\sigma_c-\sigma_1\right)}$
式中,μ为摩擦系数;τc和σc分别为最优断层面剪切应力与有效正应力;τ和σ为待分析断面相应值。
因式(9)与绝对应力值无关,故为相对值。选取I值较大的作为真实断层面,返回震源机制参数继续Michael线性反演,使用式(3)和式(10)迭代反演,直至结果不再变化,停止迭代。这时获得较为稳定的断层面,得到应力张量T,输出最优应力模型参数。
经过大量实践,为获得良好的地应力反演结果,需要注意以下事项:
1) 微地震事件需选择同一压裂层段或相近压裂层段事件,确保地应力没有明显差异。
2) 水力压裂微地震能量较弱,为获得良好效果,需对参与计算的微地震事件的初至进行精准手动拾取,为保证反演质量,对于P波初动极性不明显的波形不再拾取初至。
3) 事件优选分为2次,第1次根据微地震事件波形的信噪比选择合适的矩震级,只有大于该矩震级的微地震事件参与计算;第2次根据震源机制的整体反演效果,确定可精准拾取初至的最低台站数量,只有初至数量大于最低值的微地震事件可参与后期计算。
4) 优选后的微地震事件数量对反演结果的可靠性有着直接影响,通常参与反演的事件数量越多,解的置信区间越小,结果越收敛,可靠性越高。当优选事件较少时,应观察主应力轴置信图,置信区间发散或不聚焦时则不具备反演条件。
本文以我国东部苏北盆地碳酸盐岩型干热岩储层为例进行分析。R2井位于江苏兴化干热岩实验场,构造上位于东台坳陷中段柘垛低凸起北东部。该井以奥陶-寒武纪碳酸盐岩干热岩段为目的层,井型为定向井。
在大尺度区域应力场的研究进程中,震源机制解资料的应用是一种兼具普适性与有效性的核心研究手段。徐鸣洁等[21]使用P波初动法计算了1980—1991年江苏及邻区天然地震的震源机制解,分析结果显示,江苏及邻区现代应力场主压应力方向为NEE向。宋尚武等[22]利用2001年以来郯庐断裂带南段及邻区数千次2~3级中小地震的震源机制解,通过阻尼张量、HASH等反演方法,明确了区域应力场空间分布规律。苏北断陷区与苏南隆起区构造属性不同,应力场特征差异显著。
由图 2可知,实验场所处的区域应力场较为复杂,地应力方向以NEE向或近E向为主,但也有一些指标指示地应力方向为NW向。隶属于扬子板块的苏北盆地经历了多次构造活动,地质条件错综复杂,内部主要发育NE、NEE、NW向断裂。因此,明确干热岩开发储层的地应力特点及参数对于实验工程极为重要。
微地震监测采用地面放射性观测系统,在井场中心5 km范围内布设46个监测台站,观测系统见图 3。本文选择R2井某一段水力压裂过程中的微地震事件作为示例进行计算,压裂目标层位深度为4 695~4 800 m,压裂液量4 340方。
在进行地应力反演前,首先需进行常规微地震资料处理,常规处理的关键步骤为速度模型的建立、微地震定位。本文速度模型见图 4,速度模型根据声波测井曲线进行分层,并通过已知信号进行校正,4 000 m以深的碳酸盐岩速度基本在6 000 m/s左右。微地震定位采用能量叠加法,微震事件定位目标函数等值线切片见图 5,水平方向、垂直方向均具有较好的聚焦性,因采用地面监测方式,水平方向上的能量聚焦性较强。
水力压裂微地震能量较弱,为获得良好的效果,需对微地震事件进行优选。本文首先根据微地震事件信噪比进行筛选,微地震事件信噪比整体上与矩震级呈正相关。通过对比,本文仅对矩震级大于-0.5的地震事件进行后续计算。不同震级的微地震波形见图 6,矩震级为-0.8的地震事件可观察到波形特征,但信噪比较差。
地应力反演的效果是建立在震源机制解的基础上的,为获得质量较高的震源机制解,微地震波形的初动极性非常关键,因此,本文对可精准拾取初至(起跳点)的数量进行限制。如图 7所示,26、27、30、31号台站可精准拾取起跳点,28、29号台站无法精准拾取起跳点。为达到较好的反演效果,将本次可精准拾取初至的最低台站数量设置为12。
最终优选压裂期间的90次微地震事件进行地应力反演,微地震的空间分布见图 8,整体上呈北西-南东分布。
基于90次微地震事件,经过6次迭代,最终地应力反演结果见图 9,地应力反演的主要参数见表 1。由图 9可知,反演结果置信区间收敛效果良好,整体可信度较高。由图 9(b)可知,σ1、σ2、σ3分别对应垂向应力、最大水平主应力和最小水平主应力,为便于后续对比说明,分别使用SV、SHmax、SHmin代表。反演结果表明,储层应力相对大小关系为SV>SHmax>SHmin,应力形状因子为0.74,最大水平主应力(压应力)SHmax方向为NW44.27°。根据地应力反演结果可知,水力裂缝破裂机制以正断层和走滑断层为主,储层改造缝网容易在NW向扩展,同时也有可能在垂向上进行扩展。
岩心滞弹性应变恢复(anelastic strain recovery,ASR)法是近年来发展起来的基于定向岩心的深孔地应力测量方法,只要能够取得完整岩心,即可采用ASR法进行地应力测量获得可靠的数据[23]。R2井完井后,采用岩心ASR法进行地应力测试。
本次测试共从4 000~4 900 m段取得岩心9个,其中岩样4~7均在4 700 m附近,与压裂段岩性一致,也处于压裂时微地震发育深度段内,本次ASR测试系统见图 10。为保证测量精度,岩心样本经过细致挑选以确保完整性;测试时采用恒温控制系统,以保证岩心样品处于恒温和密封状态。
最终地应力测量结果见表 2,因采集样本有限,地应力测量方向具有一定的波动性,但大致方向相同,均为NW向。通过ASR法地应力测试获得深部钻孔的地应力类型及方向,结果表明,最大水平主应力方向为NW22°~80°,储层应力的相对大小为SV>SHmax>SHmin,与基于微地震地应力反演的结果具有较好的一致性。这也充分证明,基于微地震监测的地应力反演方法具有良好的可靠性。
由§2.1可知,R2井实验场区域地应力场特征复杂,试采储层地应力参数的精准获取,对后续干热岩开发工程的顺利实施具有关键意义。偶极子声波测井资料表明,储层地层各向异性显著,不同层位地层的地应力状态存在明显差异。压裂目的层段的最大主应力方向与微地震地应力反演、ASR地应力测量2种方法所得结果基本吻合。
基于微地震监测的地应力反演结果是归一化后的偏应力张量,仅能反映地应力的相对大小,无法像ASR法直接获得绝对应力值,但该反演结果仍可用于对地应力状态的定性及半定量分析。如本文实例所示,基于微地震监测的地应力反演可以有效判定主应力关系,确定最大水平主应力方向。另外,本文实例的形状因子显示,垂向应力与水平应力差异较大,而2个水平主应力差异较小,这也与ASR法测试结果一致。
需要指出的是,ASR法地应力测量、偶极子声波测井等常规地应力获取手段仅适用于压裂施工前的储层静态地应力分析,且难以刻画压裂过程中地应力场的动态变化特征与演化趋势。相比之下,基于微地震监测的地应力反演技术具备显著优势:该技术可灵活选取任意压裂阶段作为分析时段,并快速计算得到对应时段的地应力参数,不仅能为不同压裂阶段、不同压裂层段的地应力场变化规律提供量化表征依据,更可以为后续储层改造与开发方案的优化提供重要技术支撑。
与此同时,该微地震地应力反演方法存在一定局限性,其应用效果高度依赖微地震监测数据的质量。当压裂施工期间微地震事件释放能量较弱时,满足地应力反演条件的有效事件数量不足,将直接导致地应力反演工作难以开展。
本文系统研究了基于水力压裂微地震监测的地应力反演方法,并通过实际案例验证了其可靠性,主要结论如下:
1) 基于大量微地震监测实践,本文提出了基于水力压裂微地震监测的地应力反演技术流程,通过多约束矩张量反演震源机制,结合Michael线性应力反演与Vavryčuk断层面识别,实现了深部复杂储层应力场的量化表征。
2) 为保障矩张量反演收敛性及应力反演稳定性,应选取同一压裂层段或邻近层段的微地震事件,同时严格筛选信噪比高、P波初动清晰的有效事件。
3) 以苏北盆地碳酸盐岩干热岩储层为例,基于微地震的地应力反演结果表明,SV>SHmax>SHmin,最大水平主应力方向为NW44.27°,形状因子为0.74,与ASR岩心测试结果(SHmax方向NW22°~80°,应力关系一致)高度吻合,验证了本文方法的可靠性。
4) 本文方法可动态获取压裂全过程地应力参数,揭示应力场时空演化特征,为深部储层改造设计与开发方案优化提供关键力学依据。
  • 江苏省碳达峰碳中和科技创新专项资金(重大科技示范BE2022859)
  • 中国地质调查局项目(DD202305009)
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doi: 10.14075/j.jgg.2025.12.445
  • 接收时间:2025-12-26
  • 首发时间:2026-10-30
  • 出版时间:2026-09-15
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  • 收稿日期:2025-12-26
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江苏省碳达峰碳中和科技创新专项资金(重大科技示范BE2022859)
中国地质调查局项目(DD202305009)
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    1 中国地质调查局水文地质环境地质调查中心, 天津, 300309
    2 江苏省地质调查研究院, 南京, 210008
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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
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