Abstract

The feasibility of using a dense seismic array with an airgun source to study the quality factors of shallow media is verified. Data were obtained from 37 stations in the dense seismic array located in Binchuan, Yunnan Province, China, and the amplitude–distance attenuation method and the coda normalization method were applied to calculate the S-wave quality factors in the area. The amplitude–distance attenuation method yielded Qs-1=0.0260 ± 0.0103, and the frequency-dependent Qs-1 calculated by the coda normalization method can be expressed by the power law Qs-1(f)0.0554f-0.5643. The consistency between the results of these two methods shows that a dense seismic array with an airgun source can be used to study the attenuation characteristics of shallow media. The amplitudes at some points deviate substantially from the fitted curve and thus have a certain influence on the fitting results; hence, we must select high-precision data for the calculation. Given the topography, we speculate that the anomalous stations located on the edge of the Binchuan Basin and in the western hilly area are due to the edge effect of the basin and the weak attenuation of the hilly area and that the anomalous station located in the northern Binchuan depocenter is attributable to local site factors. Compared with the Qs-1 estimated by previous studies, the Qs-1 in the Binchuan area is found to lie between those of the hard soil and sedimentary rock and is similar to the Qs-1 in the North China Basin, corresponding to the shallow velocity structure in this area.

Details

Title
Feasibility study on calculating the Q value of shallow media by using a dense seismic array and a large-volume airgun source
Author
Du, Shen 1 ; Yu YanXiang 1 ; Liang, Xiao 1 

 China Earthquake Administration, Institute of Geophysics, Beijing, China (GRID:grid.450296.c) (ISNI:0000 0000 9558 2971) 
Publication year
2022
Publication date
Dec 2022
Publisher
Springer Nature B.V.
e-ISSN
18805981
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2660493665
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.