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作 者:杜苛 李红谊[1] 李炎臻 黄雅芬 Du Ke;Li Hongyi;Li Yanzhen;Huang Yafen(School of Geophysics and Information Technology,China University of Geosciences(Beijing),Beijing 100083,China)
机构地区:[1]中国地质大学(北京)地球物理与信息技术学院,中国北京100083
出 处:《地震学报》2023年第6期970-984,共15页Acta Seismologica Sinica
基 金:国家自然科学基金项目(U1939203,41874063)资助.
摘 要:首先对四川省地震局提供的1017次地震进行重定位,并将重定位后的578次高信噪比地震作为模板,利用基于图像处理器加速的匹配定位技术(GPU-M&L)对紫坪铺水库地震台网7个台站2005—2008年记录的连续波形数据进行扫描;然后利用基于深度学习算法的去噪技术(DeepDenoiser)设计出的卷积神经网络模型来进一步验证这些新检测到的地震事件;最后利用双差定位法对检测到的地震事件进行精定位。最终识别到的地震事件多达1万6836个,约为四川省地震局目录事件的13倍,地震目录的完备震级由M_(L)1.4降为M_(L)−0.1。定位结果显示,研究区的地震事件呈北东向线性分布,优势震源深度指示区域地壳内的滑脱层位置,结合b值和震源深度分析结果推测,研究区蓄水后的地震主要是构造应力积累导致的天然地震活动,并伴随水库触发地震混杂发生。We relocate the 1017 earthquakes provided by the Sichuan Earthquake Agency and then use the 578 relocated earthquakes with a high signal-to-noise ratio as templates.The continuous waveform data recorded by 7 stations of Zipingpu reservoir seismic network from 2005 to 2008 are scanned by graphics processing unit-based match and locate(GPU-M&L)method.Then,based on the denoising results by applying the deep learning algorithm called Deep-Denoiser,a convolutional neural network model is designed to further verify these newly detected events.Finally,the double-difference location method is used to accurately relocate them.A total of 16836 events are eventually identified,which is about 13 times as many as the events listed in the local catalog of Sichuan Earthquake Agency.The magnitude of completeness is reduced from M_(L)1.4 given by the local catalog to M_(L)−0.1.The relocated results show that the seismic events in the study area are linearly distributed in the northeast direction.The dominant focal depth indicates the location of the detachment layer in the crust of the region.Combined with the analysis results of b value and the focal depth,it is speculated that the earthquakes after impoundment in the study area are mainly natural seismic activities caused by the accumulation of tectonic stress,accompanied by the occurrence of reservoir-triggered seismicity.
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