South Ilan Plain High-Resolution 3-D S-Wave Velocity from Ambient Noise Tomography

Summary Determining a detailed 3-D velocity model with high resolution for the sedimentary layer in the Sichuan Basin is potentially beneficial both to the industrial oil/gas exploration and earthquake hazards mitigation. In this study, we apply the ambient noise tomography method to construct a 3-D S-wave velocity model. This model focuses on the sedimentary layer of the Sichuan Basin, with a 0.3° × 0.3° grid precision. Dispersion curves of both group and phase velocities of Rayleigh wave at 4 to 40 s periods are utilized, which are extracted from 87 broadband stations in the Sichuan Basin and the surrounding areas. The 3-D model reveals a thick sedimentary layer of the Sichuan Basin with S-wave velocity ranging from ∼2.0 km/s to 3.4 km/s. The sediment thickness in the margins of the Sichuan Basin is generally greater than the typical values of 6–10 km in the central areas due to surrounding orogenic activities, with a maximum depth of ∼13 km in the northwestern margin. Moreover, a prominent low S-wave velocity anomaly in the margins may be caused by the sediment accumulations from large-scale landslides and pronounced denudation of the surrounding orogenic belts. Major geologic units in the sedimentary layer are delineated in this study. The S-wave velocity values within each geologic unit and their bottom interfaces are obtained. Based on our model, we calculate synthetic ground motions for the 2013 Lushan earthquake and obtain the distribution of the peak ground acceleration from the earthquake epicenter to the western Sichuan Basin. The result clearly illustrates the basin amplification effect on the seismic waves.

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Three-dimensional S-wave velocity model of the Bohemian Massif from Bayesian ambient noise tomography

Tectonophysics ◽

10.1016/j.tecto.2017.08.033 ◽

2017 ◽

Vol 717 ◽

pp. 484-498 ◽

Cited By ~ 2

Author(s):

Lubica Valentová ◽

František Gallovič ◽

Petra Maierová

Keyword(s):

Wave Velocity ◽

Bohemian Massif ◽

Ambient Noise ◽

Three Dimensional ◽

Velocity Model ◽

S Wave ◽

Ambient Noise Tomography

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Imaging of Subsurface Velocity Structure on Volcanic Area of South East Java: An Application of Passive Seismic Ambient Noise Tomography for Sub-Volcanic Hydrocarbon Exploration

10.29118/ipa21-g-294 ◽

2021 ◽

Author(s):

P. Wardaya

Keyword(s):

Velocity Profile ◽

Wave Velocity ◽

Ambient Noise ◽

Velocity Structure ◽

Petroleum Exploration ◽

Volcanic Area ◽

S Wave ◽

Ambient Noise Tomography ◽

Volcanic Formation ◽

Passive Seismic

Petroleum exploration in sub-volcanic area always poses an inevitable challenge. Active seismic exploration method fails to obtain reliable imaging of the sediment beneath volcanic formation due to massive attenuation. This issue has been a long-standing problem in onshore seismic activity in Indonesia, especially in areas where volcanic formations present above the sedimentary formation of interest. To address this issue, we propose an alternative method utilizing a passive seismic approach to obtain reliable subsurface information. This paper discusses our experience in employing ambient noise tomography to evaluate the sedimentary structure beneath the volcanic area in Southern Malang, East Java. The passive seismic network deploying 70 seismometers were installed in a relatively regular grid. With the maximum offset between two furthest stations was 44.5km, we can capture the maximum wavelength of 15 km which is associated with the minimum frequency as low as 0.08 Hz to be used in the inversion. In principle, the seismometers record the coherent seismic noise coming from the atmospheric activity, sea wave, or industrial activity in the surface. Cross correlation between signal received in each station and their continuous stacking yields useful signals to reveal the dispersion curve which can produce the subsurface velocity profile through an inversion technique. From the inversion result we obtain the subsurface s-wave velocity structure down to a depth of 6 km. Higher s-wave velocity structure on the shallow depth in the northern area of the survey confirms the presence of the thick volcanic sediment situated near volcanic mountain. Towards the southern area we observe a slower s-wave velocity profile that indicates the thinning of volcanic formation. Although the method has successfully delivered a reliable s-wave structure over an entire survey area, its resolution is limited due to large spacing between stations. We suggest deploying denser stations to improve the velocity resolution.

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S-wave velocity of the crust around Tianshan Mountains inverted from seismic ambient noise tomography

Chinese Science Bulletin ◽

10.1007/s11434-010-4017-3 ◽

2010 ◽

Vol 55 (31) ◽

pp. 3590-3598 ◽

Cited By ~ 5

Author(s):

Zhi Guo ◽

Xing Gao ◽

WeiMin Wang ◽

GuiLin Li ◽

ZongQi Duan ◽

...

Keyword(s):

Wave Velocity ◽

Ambient Noise ◽

Tianshan Mountains ◽

S Wave ◽

Ambient Noise Tomography ◽

Seismic Ambient Noise

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Ambient-Noise Tomography of the Baiyun Gold Deposit in Liaoning, China

Seismological Research Letters ◽

10.1785/0220190393 ◽

2020 ◽

Vol 91 (5) ◽

pp. 2791-2802 ◽

Cited By ~ 1

Author(s):

Xuantao Li ◽

Jinli Huang ◽

Zhikun Liu

Keyword(s):

Gold Deposit ◽

Wave Velocity ◽

Ambient Noise ◽

Velocity Structure ◽

S Wave ◽

Ambient Noise Tomography ◽

Surface Wave Dispersion ◽

Wave Velocities ◽

Metal Mine ◽

Single Station

Abstract Ambient-noise tomography (ANT) has become an effective method for determining the fine velocity structure of the shallow crust. However, studies on metal mines using this method are rarely reported. To investigate the tectonic background and prospecting of the deep mine in the Baiyun gold deposit (BYGD) of eastern Liaoning Province, China, we use ANT to determine a 3D S-wave velocity structure model of the BYGD. A total of 21 broadband seismic stations were installed in an area of 15×14 km, centered at the BYGD. Continuous observations for approximately three months were made. After single-station preprocessing, cross correlation of ambient noise, and phase-weighted stacking, the empirical Green’s function for the Rayleigh waves between stations was recovered. Next, group-velocity dispersion with 0.8–3 s periods was measured. A direct inversion method of surface-wave dispersion based on raytracing was then adopted to determine a 3D S-wave velocity structure of the BYGD from the ground surface to a depth of 1.8 km. The results show that the distribution of S-wave velocities in the study area well reflected the geological characteristics of the surface. The velocities were significantly low within the “ore field” and the regional ore-controlling Jianshanzi fault. Combining this with the fact that a large number of magmatic veins were visible inside both structures, it was deduced that both structures had experienced large-scale magmatic intrusion activities, thus confirming that BYGD was a magmatic hydrothermal deposit. The significantly low S-wave velocities beneath the gold deposit extended to a depth of 1.8 km. This might imply the occurrence of blind ore bodies at that depth. The fine velocity structure of the BYGD reconstructed by this study provided a direction for subsequent prospecting of deep regions and demonstrated that ANT has good potential in metal mine exploration.

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