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Zheng Xian, Zhao Cuiping, Zheng Sihua. 2019: Reliability tests of shear wave velocity structure from joint inversion of multiple types of seismic data. Acta Seismologica Sinica, 41(2): 194-206. DOI: 10.11939/jass.20180100
Citation: Zheng Xian, Zhao Cuiping, Zheng Sihua. 2019: Reliability tests of shear wave velocity structure from joint inversion of multiple types of seismic data. Acta Seismologica Sinica, 41(2): 194-206. DOI: 10.11939/jass.20180100
shu

Reliability tests of shear wave velocity structure from joint inversion of multiple types of seismic data

  • 1.

    Institute of Earthquake Forecasting，China Earthquake Administration，Beijing 100036，China

  • 2.

    Key Laboratory of Earthquake Prediction，China Earthquake Administration，Beijing 100036，China

More Information
  • Received Date: July 17, 2018
  • Revised Date: September 19, 2018
  • Available Online: March 17, 2019
  • Published Date: February 28, 2019
    Graphical Abstract
    • Abstract
  • Based on the real data from joint inversion of ambient noise, surface wave data, and P wave receiver functions of 170 broad-band seismic stations of national and regional networks of the southeastern margin of Tibetan Plateau and its adjacent areas, we preformed the recovering tests to the presumed initial model of southeastern margin of Tibetan Plateau. We calculated pure path dispersion curves on the basis of the initial model, then retrieved the Rayleigh wave dispersion curves between station pairs and receiver functions beneath each station. Finally, the recovering tests were taken to measure the recovery ability to the initial model based on different seismic data alone and joint inversion of multiple types of seismic data. Our result reveals that joint inversion of receiver function, dispersion cures based on empirical Green’s functions （EGFs） of ambient noise and on teleseismic surface wave data can take full advantage of the resolution of each seismic data, and can resolve the crustal and upper mantle LVZs perfectly. Additionally, we analyzed the resulting reliability on the condition of adding calculation error or random noise. From these tests, surface wave dispersions with 1% error in joint inversion can resolve the low velocity zone （LVZ） commendably, while with 5% error can cause some differences from the initial model. Though receiver functions with 4% random noise in joint inversion can reduce the resolution of the upper and lower boundaries of the mantle LVZ, they can commendably recover the LVZs in terms of occurrence depth and velocities.
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