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作 者:丁文秀[1] 申学林[1] 廖武林[1] 周闻云 李媛[1] 魏贵春[1] 曹正琦 DING Wenxiu1, SHEN Xuelin1, LIAO Wulin1, ZHOU Wenyun2 , LI Yuan1, WEI Guichun1, CAO Zhengqi3(1 Key Laboratory of Earthquake Geodesy, Institute of Seismology, CEA, 40 Hongshance Road, Wuhan 430071, China; 2 Army Engineering University, 1038 Luoyu Road, Wuhan 430074, China; 3 Hubei Geological Survey, 9 Fifth-Gutian Road, Wuhan 430034, Chin)
机构地区:[1]中国地震局地震研究所(地震大地测量重点实验室),武汉市洪山侧路40号430071 [2]陆军工程大学军械士官学校,武汉市珞喻路1038号430074 [3]湖北省地质调查院,武汉市古田五路9号430034
出 处:《大地测量与地球动力学》2018年第4期351-355,共5页Journal of Geodesy and Geodynamics
基 金:中国地震局"三结合"课题(CEA-JC/3JH-161705);中国地震局地震研究所所长基金(IS201426143;IS201556232);国家自然科学基金(41572354)~~
摘 要:在秦岭-大别造山带及邻区背景噪声相速度成像的基础上,用近邻算法反演得到深度6~38km范围内的S波速度分布图像。依据S波速度结构建立湖北分区速度模型,并将该模型应用到2017-02-23秭归3.8级地震和06-16秭归4.3级地震定位中。结果显示,分区模型得到的总体平均误差比一维模型的更小,与三峡台网定位结果相比分区模型得到的定位结果偏差也更小。Ambient noise tomography is a powerful method to image the structure of the crust and upper mantle with better resolution. We use the nearest neighbor algorithm to map S wave velocity based on the ambient noise phase speed tomography of the Qingling-Dabie orogenic belt. With depths of 6~38 km S wave velocity, we build the partition velocity model, and apply it to the seismic localization of the June 16,2017 Zigui M4.3 and the February 23,2017 Zigui M3.8 earthquakes. The results show that the average error of the partition model issmaller, and the seismic localization results of the partition model is closer to the results from the Three Gorges digital seismological network. So, the partition velocity model is more reasonable than the one-dimensional velocity model in seismic localization.
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