Assessing the vertical localization of seismic variations retrieved by passive surface wave interferometry

Passive seismic interferometry based on noise correlations has become an efficient way to detect tiny temporal changes of properties of Earth’s subsurface and crust. In particular, this method has successfully been used for environmental seismology issues, in a view of investigating the response of shallow subsurface to environmental changes, in particular thermal and hydrogeological forcings ⁽¹⁾. An accurate spatial localization of elastic variations is thus a key objective to understand the processes involved in the whole volume probed.

Nevertheless, estimating the spatial distribution of these changes using coda waves is not a straightforward problem, regarding the complexity of scattered waves. Several assumptions are often used to simplify the coda waves and to estimate their sensitivity kernels to elastic changes ⁽²⁾. Here, our work focuses on the vertical localization of seismic variations observed by coda wave interferometry, reducing the problem to an estimation of the depth of shear stiffness variations over time in a 1D layered medium.

A time-lapse coda wave inversion scheme is commonly used, solving a linear least-square inverse problem ^{(3) (4)}. Several other methods can also be tested, from Marko Chain Monte-Carlo Bayesian inversion to gradient descent algorithms. The choice of regularization parameters and checkerboard tests are discussed here, and help to discriminate the relevant method regarding the accuracy of the results and the vertical resolution obtained. Additionally, we applied these time-lapse inversion procedures to real seismic noise datasets recorded on slope instabilities such as rock glaciers and landslides.

This work illustrates how estimating the depth of seismic velocity changes contributes to characterizing the shallow subsurface and monitoring its sensitivity to various forcings.

 

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