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物探与化探  2023, Vol. 47 Issue (4): 1048-1055    DOI: 10.11720/wtyht.2023.1139
  方法研究信息处理仪器研制 本期目录 | 过刊浏览 | 高级检索 |
基于微地震连续裂缝网络模型的SRV研究
李秋辰1(), 陈冬2, 许文豪1(), 易善鑫2, 谢兴隆1, 关俊朋2, 崔芳姿1
1.中国地质调查局 水文地质环境地质调查中心,河北 保定 071051
2.江苏省地质调查研究院,江苏 南京 210008
Determining stimulated reservoir volume based on the microseismic continuous fracture network model
LI Qiu-Chen1(), CHEN Dong2, XU Wen-Hao1(), YI Shan-Xin2, XIE Xing-Long1, GUAN Jun-Peng2, CUI Fang-Zi1
1. Hydrogeological and Environmental Geological Survey,China Geological Survey,Baoding 071051,China
2. Nanjing Institute of Geology and Paleontology,Chinese Academy of Sciences,Nanjing 210008,China
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摘要 

在干热岩的开发和改造阶段,需要对储层进行水力压裂改造,储层改造体积(stimulated reservoir volume,SRV)是评价压裂效果的主要标准。微地震监测作为水力压裂的技术环节之一,可以对储层改造体积进行有效估算。本文探讨了基于微地震连续裂缝网络模型的SRV计算方法,以指导干热岩的水力压裂工作。首先,基于微震事件时空分布特征与多项震源参数进行连续裂缝网络建模;其次,提取裂缝网格长度,并选取适当的裂缝高度与裂缝宽度以计算储层改造体积;最后,选取某双井型干热岩微地震监测数据对该方法进行实际应用。实例应用结果表明,该方法可有效估算储层改造体积,为干热岩后续开发与改造提供依据。

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李秋辰
陈冬
许文豪
易善鑫
谢兴隆
关俊朋
崔芳姿
关键词 干热岩微地震监测连续裂缝网络储层改造体积    
Abstract

Hydraulic fracturing is required during the exploitation and stimulation of hot dry rock (HDR) reservoirs.The stimulated reservoir volume (SRV) is the main criterion for evaluating the hydraulic fracturing performance.As a technical link of hydraulic fracturing,Microseismic monitoring can be used to effectively estimate the SRV.This study explored the calculational method of SRV based on the microseismic continuous fracture network model with the purpose of guiding the hydraulic fracturing of HDRs.First,the continuous fracture network was modeled based on the temporal and spatial distribution and multiple source parameters of microseismic events.Second,the fracture grid length was extracted and the appropriate fracture height and width were selected to calculate the SRV.Last,the method proposed in this study was applied to the dual-well HDR microseismic monitoring data.The application results show that this method can effectively estimate the SRV,thus providing a basis for the subsequent exploitation and stimulation of HDRs.

Key wordsdry hot rock    microseismic monitoring    continuous fracture network    stimulated reservoir volume
收稿日期: 2022-06-11      修回日期: 2023-04-07      出版日期: 2023-08-20
ZTFLH:  P631.4  
基金资助:江苏省碳达峰碳中和科技创新专项资金(重大科技示范)(BE2022859)
通讯作者: 许文豪(1993-),男,硕士学位,工程师。Email:941734230@qq.com
作者简介: 李秋辰(1988-),男,硕士学位,工程师。Email:874033010@qq.com
引用本文:   
李秋辰, 陈冬, 许文豪, 易善鑫, 谢兴隆, 关俊朋, 崔芳姿. 基于微地震连续裂缝网络模型的SRV研究[J]. 物探与化探, 2023, 47(4): 1048-1055.
LI Qiu-Chen, CHEN Dong, XU Wen-Hao, YI Shan-Xin, XIE Xing-Long, GUAN Jun-Peng, CUI Fang-Zi. Determining stimulated reservoir volume based on the microseismic continuous fracture network model. Geophysical and Geochemical Exploration, 2023, 47(4): 1048-1055.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2023.1139      或      https://www.wutanyuhuatan.com/CN/Y2023/V47/I4/1048
Fig.1  “事件点—网络”连接准则
Fig.2  基于连续裂缝网络模型的SRV算法流程
Fig.3  射孔校正速度模型
Fig.4  微震事件时间—空间分布
a—xy向平面;b—xz向剖面
Fig.5  定位目标函数等值线
a—单井定位目标函数等值线;b—双井定位目标函数等值线
Fig.6  微震事件震源参数反演结果
a—震源机制解玫瑰图;b—应力主轴置信区间图;c—矩震级统计直方图
Fig.7  连续裂缝网络(CFN)模型
Fig.8  储层改造体积(SRV)示意
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