Passive surface-wave waveform inversion for source-velocity joint imaging

Reliable dispersion measurement between two seismic stations is an essential basis of surface wave imaging. Noise source directivity has become an inescapable obstacle and a main concern for passive seismic survey: it basically breaks the principle of Green’s function retrieval in travel-time tomography; moreover, the azimuthal effect of heterogeneous ambient noise sources will inherently cause different levels of early arrival on cross-correlation functions, the apparent velocity of surface waves can be overestimated by either multichannel slant stackings or interstation frequency-time analysis.

Based on the theoretical framework of full waveform ambient noise inversion, Zhou et al. (2022) proposed a method to jointly invert noise source distributions and the corresponding unbiased surface wave velocities. The coupled dependencies of source distributions and path velocities in waveform misfit function show necessity of source-structure joint inversion. The decoupling strategy of partial derivatives is approved by the synthetic tests. Field experiments in Hangzhou urban area further reveal the practicability of the theory. The inverted noise source models are comparable with the in-situ noise distributions in urban environment, and the delineated surface wave velocities have been verified by local borehole datasets. The developed waveform joint imaging algorithm is named ModAS, and it can well relieve the dilemma of source induced velocity uncertainties (Figure 1) for the community.

Figure 1. Source-velocity joint inversion results and comparisons. (a) Waveform comparisons between the inverted and the observed cross-correlation functions; Tomographic slices based on (b) prior path velocities, (c) observed path velocities and (d) inverted path velocities; (e) inverted source distributions, the seismic stations are represented by the black dots, the working drilling machine is denoted by the red star.

This work has been done by Prof. Jianghai Xia’s group and published in Surveys in Geophysics (One of the best journals in geophysics). The first author Changjiang Zhou is a PhD candidate. This study is supported by the National Natural Science Foundation of China (grant no. 41830103), and the China Geological Survey (grant no. DD20190281)

For more details:

Zhou, C., Xia, J., Cheng, F., Pang, J., Chen, X., Xing, H., & Chang, X., 2022. Passive

surface-wave waveform inversion for source-velocity joint imaging. Surveys in

Geophysics, 1-29. https://doi.org/10.1007/s10712-022-09691-7