4.7 Article

Surface Wave Tomography of Northeastern Tibetan Plateau Using Beamforming of Seismic Noise at a Dense Array

期刊

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2019JB018416

关键词

Beamforming; Ambient noise; Dense array; Surface wave tomography; Northeastern Tibet

资金

  1. National Key RAMP
  2. D Program of China [2017YFC1500200]
  3. National Natural Science Foundation of China [41674062, U1839209, 41174041]
  4. China National Special Fund for Earthquake Scientific Research of Public Interest [201308011]
  5. Research Council of Norway through its centers of Excellence funding scheme [223272]

向作者/读者索取更多资源

In traditional surface wave tomography based on seismic noise, 2D phase or group velocity distribution is obtained by performing pure-path inversion after extracting interstation velocities based on the noise cross-correlation function. In this paper, we show that 2D surface wave phase velocity maps of adequate quality can be obtained directly, without interferometry, by beamforming the ambient noise recorded at array of stations. This method does not require a good azimuthal distribution of the noise sources. The 2D surface wave phase velocity map is obtained by moving the subarrays within a larger dense network of stations. The method is illustrated with seismic noise recorded by over 600 stations of the ChinArray (Phase II). We obtain 2D Rayleigh wave phase velocity maps between 7 and 35 s in Northeastern (NE) Tibetan Plateau and adjacent regions that compare well with results obtained with other methods. The shear wave velocity model is then derived by inverting the phase velocity with depth. The model correlates well with geology and tectonics in NE Tibet. Two clear mid-to-low crustal low-velocity zones are observed at 15- to 35-km depth beneath the Songpan-Ganzi terrane and Northwestern Qilian Orogen, possibly facilitating lower crustal flow in this key region for the tectonic evolution of NE Tibet.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据