郑现, 赵翠萍, 郑斯华. 2019: 利用多种地震数据联合反演剪切波速度结构的可靠性检测. 地震学报, 41(2): 194-206. DOI: 10.11939/jass.20180100
引用本文: 郑现, 赵翠萍, 郑斯华. 2019: 利用多种地震数据联合反演剪切波速度结构的可靠性检测. 地震学报, 41(2): 194-206. DOI: 10.11939/jass.20180100
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

利用多种地震数据联合反演剪切波速度结构的可靠性检测

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

  • 摘要: 本文模拟使用青藏高原东南缘区域台网及国家台网的170个宽频台站基于背景噪声、天然地震面波、P波接收函数反演时的实际数据,对青藏高原东南缘假定的初始模型进行恢复,通过计算初始模型台站下方纯路径频散、提取各台站对间的瑞雷波频散曲线、计算理论接收函数以及反演剪切波速度结构来测试使用不同单项数据与联合使用多种数据反演对初始模型的恢复程度。结果表明,同时使用接收函数、基于噪声经验格林函数的群速度、相速度频散以及基于天然地震面波的相速度频散联合反演的剪切波速度结构,充分利用了几种数据的分辨率优势,清晰地分辨出中下地壳及上地幔顶部的低速层。此外,本文也分析了实际数据处理中出现的计算误差、随机噪声干扰对计算结果稳定性的影响。结果显示:对于面波频散,加入1%的误差后,联合反演的结果仍可很好地反映低速层的形态,但是当误差提升至5%后,对最终结果则产生了一定程度的影响;而在接收函数中加入4%的随机噪声时,虽然地幔低速层的上界面和下界面会略微受到随机噪声的影响,但是低速层的深度范围和速度值均得到了较好的恢复。

     

    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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