scholarly journals The shallow crustal S-velocity structure of the Longmenshan fault zone using ambient noise tomography of a seismic dense array

2019 ◽  
Vol 32 (5-6) ◽  
pp. 197-206
Author(s):  
Dandan Li ◽  
◽  
Gaochun Wang ◽  
Ruihua Lin ◽  
Kai Deng ◽  
...  
2019 ◽  
Vol 110 (1) ◽  
pp. 38-48 ◽  
Author(s):  
Yuting Zhang ◽  
Hongyi Li ◽  
Yafen Huang ◽  
Min Liu ◽  
Yong Guan ◽  
...  

ABSTRACT The Longmen Shan fault zone that was shocked by the 12 May 2008 M 8.0 Wenchuan earthquake acts as the boundary between the western edge of the Sichuan basin and the steep eastern margin of the Songpan-Ganze block. In this study, continuous seismic data recorded by 176 temporary short-period seismic stations between 22 October and 20 November 2017 are used to study the shallow crustal structure of the Longmen Shan fault zone by applying ambient-noise tomography and horizontal-to-vertical spectral ratio (HVSR) analysis. From ambient-noise analysis, fundamental-mode Rayleigh-wave dispersion curves between 0.25 and 1 Hz are extracted. Then, the direct surface-wave tomographic method is used to invert surface-wave dispersion data for the 3D shallow shear-wave velocity structure. Our results show that low shear-wave velocities are mainly distributed around the surface rupture trace of the Wenchuan earthquake at least down to 2 km. From the HVSR method, the sites are sorted into two types according to the pattern of HVSR curves with single peak or double peak. By converting frequency to depth, the results show that the sediments are thicker near the surface rupture. The low-velocity zone based on ambient-noise tomography agrees well with the distribution of sedimentary cover estimated from HVSR, which are generally consistent with geological information. Our results provide high-resolution shallow crustal velocity structure for future detailed studies of the Longmen Shan fault.


2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Haiou Li ◽  
Xiwei Xu ◽  
Wentao Ma ◽  
Ronghua Xie ◽  
Jingli Yuan ◽  
...  

Three-dimensional P wave velocity models under the Zipingpu reservoir in Longmenshan fault zone are obtained with a resolution of 2 km in the horizontal direction and 1 km in depth. We used a total of 8589 P wave arrival times from 1014 local earthquakes recorded by both the Zipingpu reservoir network and temporary stations deployed in the area. The 3-D velocity images at shallow depth show the low-velocity regions have strong correlation with the surface trace of the Zipingpu reservoir. According to the extension of those low-velocity regions, the infiltration depth directly from the Zipingpu reservoir itself is limited to 3.5 km depth, while the infiltration depth downwards along the Beichuan-Yingxiu fault in the study area is about 5.5 km depth. Results show the low-velocity region in the east part of the study area is related to the Proterozoic sedimentary rocks. The Guanxian-Anxian fault is well delineated by obvious velocity contrast and may mark the border between the Tibetan Plateau in the west and the Sichuan basin in the east.


2021 ◽  
Author(s):  
Máté Timkó ◽  
Lars Wiesenberg ◽  
Amr El-Sharkawy ◽  
Zoltán Wéber ◽  
Thomas Meier ◽  
...  

<p>The Pannonian Basin is located in Central-Europe surrounded by the Alpine, Carpathian, and Dinarides mountain ranges. This is a back-arc basin characterized by shallow Moho depth, updoming mantle and high heat flow. In this study, we present the results of the Rayleigh wave based ambient noise tomography to investigate the velocity structure of the Carpathian-Pannonian region. </p><p>For the ambient noise measurements, we collected the continuous waveform data from more than 1280 seismological stations from the broader Central-Eastern European region. This dataset embraces all the permanent and the temporary (AlpArray, PASSEQ, CBP, SCP) stations from the 9-degree radius of the Pannonian Basin which were operating between the time period between 2005 and 2018. All the possible vertical component noise cross-correlation functions were calculated and all phase velocity curves were determined in the 5-80 s period range using an automated measuring algorithm. </p><p>The collected dispersion measurements were then used to create tomographic images that are characterized by similar velocity anomalies in amplitude, pattern and location that are consistent with the well-known tectonic and geologic structure of the research area and are comparable to previous tomographic models published in the literature.</p>


2020 ◽  
Vol 24 (6) ◽  
pp. 1175-1188
Author(s):  
Xiao-Ping Fan ◽  
Yi-Cheng He ◽  
Cong-Jie Yang ◽  
Jun-Fei Wang

AbstractBroadband teleseismic waveform data from 13 earthquakes recorded by 70 digital seismic stations were selected to evaluate the inhomogeneity parameters of the crustal medium in the southern Longmenshan fault zone and its adjacent regions using the teleseismic fluctuation wavefield method. Results show that a strong inhomogeneity exists beneath the study region, which can be divided into three blocks according to its structure and tectonic deformation features. These are known as the Sichuan-Qinghai Block, the Sichuan-Yunnan Block, and the Mid-Sichuan Block. The velocity fluctuation ratios of the three blocks are approximately 5.1%, 3.6%, and 5.1% in the upper crust and 5.1%, 3.8%, and 4.9% in the lower crust. The inhomogeneity correlation lengths of the three blocks are about 10.1 km, 14.0 km, and 10.7 km in the upper crust and 11.8 km, 17.0 km, and 11.8 km in the lower crust. The differences in the crustal medium inhomogeneity beneath the Sichuan-Yunnan Block, the Sichuan-Qinghai Block, and the Mid-Sichuan Block may be related to intensive tectonic movement and material flow in the crust and upper mantle.


2020 ◽  
Vol 307 ◽  
pp. 106557
Author(s):  
Huaizhong Yu ◽  
Jing Zhao ◽  
Xiaoxia Liu ◽  
Chen Yu ◽  
Chong Yue ◽  
...  

2019 ◽  
Vol 177 (1) ◽  
pp. 37-53 ◽  
Author(s):  
Reiken Matsushita ◽  
Kazutoshi Imanishi ◽  
Makiko Ohtani ◽  
Yasuto Kuwahara ◽  
Jiuhui Chen ◽  
...  

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Hongfeng Yang ◽  
Yaohui Duan ◽  
Junhao Song ◽  
Xiaohuan Jiang ◽  
Xiaofeng Tian ◽  
...  

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