• ISSN 2097-1893
  • CN 10-1855/P

区域尺度地震体波和面波走时联合成像:进展与展望

方洪健 刘影 姚华建 张海江

引用本文: 方洪健,刘影,姚华建,张海江. 2022. 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(0):1-18
Fang H J, Liu Y, Yao H J, Zhang H J. 2022. Regional-scale joint seismic body- and surface-wave travel time tomography . Reviews of Geophysics and Planetary Physics, 54(0): 1-18 (in Chinese)

区域尺度地震体波和面波走时联合成像:进展与展望

doi: 10.19975/j.dqyxx.2022-055
基金项目: 国家自然科学基金青年基金资助项目(42104046,42004034);南方海洋科学与工程广东省实验室(珠海)创新团队建设资助项目(311021003)
详细信息
    作者简介:

    方洪健,男,副教授,主要从事天然地震学成像与地震台阵分析等的研究. E-mail:fanghj23@mail.sysu.edu.cn

    通讯作者:

    刘影(1992-),女,副研究员,主要从事地震层析成像与各向异性等的研究. E-mail:liuying7@ustc.edu.cn

  • 中图分类号: P315

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

Funds: Supported by the National Natural Science Foundation of China (Grant Nos. 42104046, 42004034), Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant No.311021003)
  • 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.

     

  • 图  1  以美国南加州为例的区域尺度观测的地震波形及噪声互相关记录. (a)南加州地区宽频带地震台站分布(蓝色三角形). (b)2022年2月6日一个震级为3.1级地震[位置见图(a)红色五角星]在CI.JVM台站垂直分量[位置见图(a)标注的蓝色三角形]不同频段的波形记录. 其中图(b)上波形为1.0 Hz的高通滤波,其次为带通滤波,频率范围为$ 0.05\mathrm{~}0.5 $ Hz. 图(b)下图显示离地震位置较近的台站CI.LMH及CI.JVM台站间互相关记录. 互相关利用了2022年2月到3月一个月的连续记录. 由图可知区域尺度上地震P波和S波较为明显,但面波不发育. 联合反演中的面波数据可由台站间通过对连续记录进行互相关获得. 全波形成像受计算资源限制,通常只拟合低频的地震波形,而区域尺度低频波形常常具有较低的信噪比,故需对用来反演的波形进行严格的质量控制

    Figure  1.  The seismic waveforms and ambient noise cross-correlation function of two stations in Southern California. (a) The blue triangles show the distribution of broadband seismic stations in Southern California. (b) The vertical components of a magnitude 3.1 earthquake (marked as red star in the left panel) at station CI.JVM (marked as blue filled triangle in the left panel) at different frequencies. The right top waveform is high pass filtered at 1 Hz and the right middle waveform is band pass filtered at 0.05~0.5 Hz. The right bottom shows the ambient noise cross-correlation function between station CI.LMH and CI.JVM using one-month continuous records (from February to March 2022). P-wave and S-wave could be easily recognized in the earthquake recording, but surface wave is difficult to identify. For regional-scale joint inversion, the surface wave data can be obtained by ambient noise cross-correlation using continuous records. For full waveform tomography, only low frequencies are used due to the large computational cost. As the signal to noise ratio of low frequency waveform at region scale is relatively low, strict quality control should be applied on the waveforms when doing full waveform tomography

    图  2  体波和面波数据联合反演合成数据测试. (a)输入模型;(b)由联合反演获得的模型;(c)体波数据单独反演的模型;(d)面波数据单独反演的模型. 左列显示VS,右列显示VP. 由图可知联合反演相比于体波数据单独反演在浅部有较大改善,较面波单独反演对VP以及深部模型改善较大,并且异常的整体幅度与输入模型更为接近,可更好地约束VP/VS模型(修改自Fang et al., 2016

    Figure  2.  Synthetic test of joint inversion of body- and surface-wave data. (a) Input model; (b) Recovered model from joint inversion; (c) Separate inversion using body wave only; (d) Separate inversion using surface wave only are shown from the top to bottom. The left and right column show the VS and VP model, respectively. The resolution at shallow depths is improved in the joint inversion compared to separate inversioin using the body wave only. Besides, the joint inversion improves Vp model significantly compared to separate inversion surface wave only. The better resolved anomaly amplitude in the joint inversion leads to more realiable VP/VS model (modified from Fang et al., 2016)

    图  3  川滇公共速度模型(1.0版本)在不同深度(相对于平均海平面)的VPVS分布. 其中,黑色实线为区域主要断层分布,紫色虚线为峨眉山大火成岩省的内、中、外带,红色圆点为4.0级以上地震的重定位结果(修改自Liu et al., 2021

    Figure  3.  The community velocity model (V1.0) of Southwest China at different depths (the depth sea level is 0 km). Solid black lines represent major faults in this region. Purple dashed lines mark the inner, intermediate, and outer boundary of the Emeishan large igneous province. The relocated events with magnitude larger than 4.0 are shown in red circles (modified from Liu et al., 2021)

    图  4  川滇公共速度模型(1.0版本)在不同纵切面的VPVS(a-f),以及Gao等(2017)在相应纵切面的VPVS(g-l). 剖面位置如图3b所示,红色十字为4.0级以上地震的重定位结果. 断层位置以箭头标识:CHF:程海断裂;LZJF:绿汁江断裂;XJF:小江断裂带;RRF:红河断裂带;DLSF:大凉山断裂;LMSF:龙门山断裂带;LXJF:丽江—小金河断裂带

    Figure  4.  Vertical profiles of the community velocity model (V1.0) of southwest China (a-f) and the model from Gao et al. (2017) (g-l). The locations of profiles are shown in Fig. 3b. The plus signs are relocated earthquakes with magnitude larger than 4.0. The faults are marked by arrows and labeled: CHF: Chenghai fault; LZJF: Lvzhijiang fault; XJF: Xiaojiang fault; RRF: Red River fault; DLSF: Daliangshan fault; LMSF: Longmenshan fault; LXJF: Lijiang–Xiaojinhe fault

    图  5  地震学数据联合反演框架

    Figure  5.  The framework of joint inversion with different kinds of seismic data

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  • 收稿日期:  2022-06-30
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