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作 者:黄雅芬 李红谊[1,2] 李炎臻 葛慧颖 张盛中 Huang Yafen;Li Hongyi;Li Yanzhen;Ge Huiying;Zhang Shengzhong(Key Laboratory of Intraplate Volcanoes and Earthquakes(China University of Geosciences,Beijing),Ministry of Education,Beijing 100083,China;School of Geophysics and Information Technology,China University of Geosciences(Beijing),Beijing 100083,China;Information Network Center,China University of Geosciences(Beijing),Beijing 100083,China)
机构地区:[1]陆内火山与地震教育部重点实验室(中国地质大学(北京)),北京100083 [2]中国地质大学(北京)地球物理与信息技术学院,北京100083 [3]中国地质大学(北京)信息网络与数据中心,北京100083
出 处:《地球与行星物理论评(中英文)》2025年第1期94-101,共8页Reviews of Geophysics and Planetary Physics
基 金:国家自然科学基金资助项目(U1939203)。
摘 要:重复地震是指不同时期发生在断层同一位置的一组地震,表现为波形和震源机制上的高度相似.重复地震可用来探测断层深部形变、刻画断层行为、评估地震灾害.然而,重复地震的识别条件阈值设置尚没有统一的标准,常用的识别参数存在较大的主观性,会导致识别重复地震存在误差.为解决上述问题,本研究利用基于机器学习中的层次聚类算法构建了一个自动高效的重复地震识别方法.首先采用波形并行互相关技术计算地震波形之间的互相关系数,结合S-P到时差方法估算地震震源之间的距离,再利用层次聚类方法将地震聚类,获得重复地震.本文将该方法应用至甘孜—玉树断裂带和东昆仑断裂带地区的地震活动,识别重复地震并估算断层滑动速率.在甘孜—玉树断裂带附近共识别出6组重复地震组,它们均沿甘孜—玉树断裂带走向布展,平均断层滑动速率为7.4 mm/a.东昆仑断裂带附近共识别出3组重复地震组,平均断层滑动速率为6.9 mm/a.沿东昆仑断裂东段,断层滑动速率呈现出速率向东逐渐降低的趋势,显示该区域复杂的动力作用过程.这些结果与野外地质观测和GPS大地测量结果较为一致.基于实际数据测试和验证,结果表明本文发展的基于聚类的识别重复地震方法具有自动、高效、便捷的特性,为准确识别重复地震提供了重要的基础资料,为分析断层活动性提供了重要约束.Events with highly similar waveforms and rupturing of the same fault patch are interpreted as repeating earthquakes,which can be applied in detecting deep fault deformation,characterizing fault behavior,and assess seismic hazards.In this study,we develop a clustering-based repeating earthquakes identification method by using the hierarchical clustering algorithm in machine learning.First,the parallel waveform cross-correlation method is adopted to calculate the cross-correlation coefficient(CC).Then,the S-P differential time is used to measure the inter distance of events.Finally,the hierarchical clustering is applied to obtain repeating clusters.We utilize this method to investigate the seismicity around the Ganzi-Yushu fault(GYF)and the eastern Kunlun fault(EKLF).We identify 6 repeating clusters along the GYF,with an average fault slip rate of 7.4 mm/a.Around the EKLF,we identify 3 repeating clusters,with an average fault slip rate of 6.9 mm/a.Along the EKLF,the fault slip rates gradually decreases from the west to the east along the strike,indicating a complex dynamic process.Our results agree with geology observation and GPS data.Based on real data testing,our results show that the method to identify repeating earthquakes is automatic,efficient and convenient and provides basic information for accurate identification of repeating earthquakes and places constraints on fault activity.
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