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Fundamental mode surface wave data have often been used to construct global shear velocity models of the upper mantle under the so-called ‘path average approximation’, an efficient approach from the computational point of view. With the advent of full-waveform inversion and numerical wavefield computations, such as afforded by the spectral element method, accounting for the effects of the crust accurately becomes challenging. Here, we assess the merits of accounting for crustal and uppermost mantle effects on surface and body waveforms using fundamental mode dispersion data and a smooth representation of the shallow structure. For this we take as reference a model obtained by full-waveform inversion and wavefield computations using the spectral element method, model SEMUCB-WM1 and compare the waveform fits of synthetics to different parts of three component observed teleseismic records, in the period band 32–300 s for body waves and 40–300 s for surface waves and their overtones for three different models. The latter are: a dispersion-only based model (model Disp_20s_iter5), and two models modified from SEMUCB-WM1 by successively replacing the top 200 km (model Merged _200 km) and top 80 km (model Merged _80 km), respectively, by a model constrained solely by fundamental mode surface wave dispersion data between periods of 20 and 150 s. The crustal part of these three models (resp. SEMUCB-WM1) is constrained from dispersion data in the period range 20–60 s (resp. 25–60 s), using the concept of homogenization which is tailored to simplify complex geological features, enhancing the computational efficiency of our seismic modelling. We evaluate the fits to observed waveforms provided by these three models compared to those of SEMUCB-WM1 by computing three component synthetics using the spectral element method for five globally distributed events recorded at 200+stations, using several measures of misfit. While fits to waveforms for model 3 are similar to those for SEMUCB-WM1, the other two models provide increasingly poorer fits as the distance travelled by the corresponding seismic wave increases and/or as it samples deeper in the mantle. In particular, models 1 and 2 are biased towards fast shear velocities, on average. Our results suggest that, given a comparable frequency band, models constructed using fundamental mode surface wave data alone and the path average approximation, fail to provide acceptable fits to the corresponding waveforms. However, the shallow part of such a 3-D radially anisotropic model can be a good starting model for further full waveform inversion using numerical wavefield computations. Moreover, the shallow part of such a model, including its smooth crustal model, and down to a maximum depth that depends on the frequency band considered, can be fixed in full-waveform inversion iterations for deeper structure. This can save significant computational time when higher resolution is sought in the deeper mantle. In the future, additional constraints for the construction of the homogenized model of the crust can be implemented from independent short period studies, either globally or regionally.

 

The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform ‘data’ for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ, and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for.

 

Abstract Distributed acoustic sensing (DAS) is being explored in a variety of environments as a promising technology for the recording of seismic signals in dense array configurations. There is a particular interest for deploying DAS arrays on the ocean floor, presenting formidable challenges for conventional seismology. Taking advantage of the availability of a dark fiber on the Monterey Bay Accelerated Research System (MARS) 52 km offshore cable at Monterey Bay, California, in July 2022, we installed a DAS interrogator at the shore end of the cable with the intention of acquiring continuous data for a period of one year. Here, we describe the experiment and present examples of observations over the first six months of the deployment. 

SUMMARY The presence of seismic anisotropy at the base of the Earth's mantle is well established, but there is no consensus on the deformation mechanisms in lower mantle minerals that could explain it. Strong anisotropy in magnesium post-perovskite (pPv) has been invoked, but different studies disagree on the dominant slip systems at play. Here, we aim to further constrain this by implementing the most recent results from atomistic models and high-pressure deformation experiments, coupled with a realistic composition and a 3-D geodynamic model, to compare the resulting deformation-induced anisotropy with seismic observations of the lowermost mantle. We account for forward and reverse phase transitions from bridgmanite (Pv) to pPv. We find that pPv with either dominant (001) or (010) slip can both explain the seismically observed anisotropy in colder regions where downwellings turn to horizontal flow, but only a model with dominant (001) slip matches seismic observations at the root of hotter large-scale upwellings. Allowing for partial melt does not change these conclusions, while it significantly increases the strength of anisotropy and reduces shear and compressional velocities at the base of upwellings. 

Accurate synthetic seismic wavefields can now be computed in 3-D earth models using the spectral element method (SEM), which helps improve resolution in full waveform global tomography. However, computational costs are still a challenge. These costs can be reduced by implementing a source stacking method, in which multiple earthquake sources are simultaneously triggered in only one teleseismic SEM simulation. One drawback of this approach is the perceived loss of resolution at depth, in particular because high-amplitude fundamental mode surface waves dominate the summed waveforms, without the possibility of windowing and weighting as in conventional waveform tomography.

This can be addressed by redefining the cost-function and computing the cross-correlation wavefield between pairs of stations before each inversion iteration. While the Green’s function between the two stations is not reconstructed as well as in the case of ambient noise tomography, where sources are distributed more uniformly around the globe, this is not a drawback, since the same processing is applied to the 3-D synthetics and to the data, and the source parameters are known to a good approximation. By doing so, we can separate time windows with large energy arrivals corresponding to fundamental mode surface waves. This opens the possibility of designing a weighting scheme to bring out the contribution of overtones and body waves. It also makes it possible to balance the contributions of frequently sampled paths versus rarely sampled ones, as in more conventional tomography.

Here we present the results of proof of concept testing of such an approach for a synthetic 3-component long period waveform data set (periods longer than 60 s), computed for 273 globally distributed events in a simple toy 3-D radially anisotropic upper mantle model which contains shear wave anomalies at different scales. We compare the results of inversion of 10 000 s long stacked time-series, starting from a 1-D model, using source stacked waveforms and station-pair cross-correlations of these stacked waveforms in the definition of the cost function. We compute the gradient and the Hessian using normal mode perturbation theory, which avoids the problem of cross-talk encountered when forming the gradient using an adjoint approach. We perform inversions with and without realistic noise added and show that the model can be recovered equally well using one or the other cost function.

The proposed approach is computationally very efficient. While application to more realistic synthetic data sets is beyond the scope of this paper, as well as to real data, since that requires additional steps to account for such issues as missing data, we illustrate how this methodology can help inform first order questions such as model resolution in the presence of noise, and trade-offs between different physical parameters (anisotropy, attenuation, crustal structure, etc.) that would be computationally very costly to address adequately, when using conventional full waveform tomography based on single-event wavefield computations.