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页岩气储层多期构造应力场反演与裂缝演化

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川南泸州区块五峰组—龙马溪组的页岩气蕴藏量大,构造运动使地应力局部集中,从而引起裂缝和断层的产生,对页岩气的勘探开发有较大影响.为了优选页岩气勘探区,采用地震综合资料、古构造图和岩石力学参数测试等方法,运用神经网络算法和地质力学建模方法,对研究区多期古构造应力场进行反演,并对应力影响下的储层裂缝发育规律进行预测.研究结果表明:采用数值模拟和神经网络算法,可以进行多期构造作用下的地应力场反演.多期构造运动使地应力发生调整变化,地层背斜部位应力较为集中,背斜核部受到强烈构造作用而发生破裂,应力逐步释放;多期构造运动使储层岩石承受的应力逐步变化,易出现破裂带而形成断层,应力逐步减小;原有断层周边裂缝发育较为强烈,易出现应力衰减区域,从而出现多而短的小型裂缝.现今应力场受多期构造运动综合影响,分布较复杂,裂缝发育规律性不强,对页岩气钻井、开发等影响较大.研究成果对深层页岩气的勘探开发具有一定的指导意义.
Inversion of multiphase tectonic stress field and fracture evolution in shale gas reservoirs
The shale gas reserves in the Wufeng Formation-Longmaxi Formation of the Luzhou Block in southern Sichuan are substantial.Tectonic movements alter the ground stress,significantly impacting the exploration and development of shale gas.To optimize exploration areas for deep shale,methods such as seismic comprehensive data,ancient structural maps,and rock mechanics parameter testing have been employed.Additionally,neural network algorithms and geological mechanics modeling analysis have been used to invert the stress field of ancient geological structures across multiple stages within the study area and to predict the development of reservoir fractures influenced by stress.The research indicates that numerical simulation methods and neural network algorithms effectively invert the crustal stress field across multiple stages.Tectonic movements have altered the crustal stress,concentrating it in the stratigraphic anticline.Here,the core of the anticline,affected by strong tectonic activity,is fractured,gradually releasing stress.The ongoing multi-stage tectonic movements have facilitated changes in the stress of the reservoir rock,making the fracture zone conducive to fault formation with decreasing stress over time.Around the original faults,crack development is pronounced,leading to stress attenuation zones prone to numerous,short,small cracks.The current stress field,shaped by multiple tectonic periods,presents a complex distribution and irregular crack development,significantly influencing shale gas drilling and development.These findings offer valuable insights for the exploration and development of deep shale gas.

shale gas reservoirsmultiphase tectonic movementinversion of stress fieldfracture evolutionneural network algorithm

王嘉伟、张伯虎、胡尧、何政毅、胡欣欣、陈伟、罗超

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西南石油大学地球科学与技术学院,四川成都 610500

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

中国石油西南油气田公司页岩气研究院,四川成都 610056

页岩气储层 多期构造运动 应力场反演 裂缝演化 神经网络算法

中国石油天然气集团公司-西南石油大学创新联合体合作项目国家自然科学基金青年科学基金项目

2020CX02010041502150

2024

油气藏评价与开发
中国石油化工集团公司华东石油局

油气藏评价与开发

CSTPCD北大核心
影响因子:0.461
ISSN:2095-1426
年,卷(期):2024.14(4)