• ISSN 2097-1893
  • CN 10-1855/P
方洪健,刘影,姚华建,张海江. 2023. 区域尺度地震体波和面波走时联合成像:进展与展望. 地球与行星物理论评(中英文),54(3):252-269. doi: 10.19975/j.dqyxx.2022-055
引用本文: 方洪健,刘影,姚华建,张海江. 2023. 区域尺度地震体波和面波走时联合成像:进展与展望. 地球与行星物理论评(中英文),54(3):252-269. doi: 10.19975/j.dqyxx.2022-055
Fang H J, Liu Y, Yao H J, Zhang H J. 2023. Regional-scale joint seismic body- and surface-wave travel time tomography. Reviews of Geophysics and Planetary Physics, 54(3): 252-269 (in Chinese). doi: 10.19975/j.dqyxx.2022-055
Citation: Fang H J, Liu Y, Yao H J, Zhang H J. 2023. Regional-scale joint seismic body- and surface-wave travel time tomography. Reviews of Geophysics and Planetary Physics, 54(3): 252-269 (in Chinese). doi: 10.19975/j.dqyxx.2022-055

区域尺度地震体波和面波走时联合成像:进展与展望

Regional-scale joint seismic body- and surface-wave travel time tomography

  • 摘要: 如何利用观测到的地震图上尽可能多的信息来约束地下结构以及地震震源本身一直是地震学研究的前沿课题. 近年来,随着计算机计算能力的提高,使用基于全波形反演的方法已被用于不同尺度结构成像中,并取得了良好的效果. 但如何减小全波形反演对计算资源的巨大需求以及其反演的高度非线性仍是目前急需解决的问题. 此外,对于区域以及全球尺度成像,全波形反演的波形的拟合仅限于相对较低的频率. 目前,基于波形层析成像在区域尺度最高能拟合的频率大约为0.5 Hz,在全球尺度能拟合的频率更低,所以获得的波速模型的分辨率还有一定的改进空间. 地震学体波和面波联合反演是另一种可以综合利用更多信息的成像方法. 该种方法主要利用高频体波的走时信息以及面波的频散信息来约束地下结构. 由于只需要求解高频近似下的波动方程,其效率较全波形反演有较大提高. 相比于体波和面波数据单独反演,联合反演能利用体波和面波对地下结构约束的互补性来获得能同时拟合不同数据的波速结构模型. 此外,体波和面波数据联合反演能获得更为准确的泊松比模型,因此可以更好地约束岩性、孔隙度、熔融程度等. 鉴于目前海量的基于机器学习获得的不同震相的走时数据以及越来越多的密集流动地震观测,联合反演方法将在区域尺度地壳及上地幔结构的成像中发挥重要作用,进而为区域构造演化、地震灾害评估以及依赖波速结构模型的其他研究奠定基础. 本文将回顾区域尺度常用的地震成像方法,介绍联合反演方法的基本原理以及川滇地区的应用,最后探讨一些未来的发展方向.

     

    Abstract: To make full use of seismograms to put tight constraints on the structure of subsurface and earthquake sources has always been the research focus in seismology. With increasing computational power, full waveform based seismic tomography has been applied in some regions with promising results. However, the heavy demand for computational resources and strong nonlinearity still prohibit its wide applications. Additionally, most applications of full waveform tomography at regional or global scales can only fit relatively long-period waveforms; the highest frequency of waveform fitting in full waveform tomography is approximately 0.5 Hz on regional scales and even lower on global scales. An alternative way to take advantage of more information on seismograms is the joint inversion of body and surface waves. Instead of fitting low-frequency waveforms, as in full waveform tomography, the joint inversion method uses high-frequency body-wave arrival times and surface-wave dispersion measurements. The forward problem in joint inversion only involves ray tracing or solving the Eikonal equation numerically. Therefore, it is less demanding in terms of computational resources. Compared to separate inversion using either body or surface wave data, joint inversion can provide a unified VP and VS model, and thus more reasonable VP/VS ratio model, by taking advantage of the complementary strength of both data sets. These models could impose tighter constraints on lithology, porosity, and partial melting. Moreover, machine learning-based techniques to detect earthquakes and pick arrivals have obtained many high-frequency arrival times on regional scales with dense deployments, which could be used in joint inversion to improve regional wavespeed models in the crust and upper mantle. The improved models may benefit other seismological studies and provide better understanding of regional tectonics. In this paper, we review some widely used seismic tomography methods for constructing regional models, introduce the basics of joint inversion and its application in southwest China, and discuss potential improvements.

     

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