An official website of the United States government
SUMMARY Long-period underside SS wave reflections have been widely used to furnish global constraints on the presence and depth of mantle discontinuities and to document evidence for their origins, for example, mineral phase-transformations in the transition zone, compositional changes in the mid-mantle and dehydration-induced melting above and below the transition zone. For higher-resolution imaging, it is necessary to separate the signature of the source wavelet (SS arrival) from that of the distortion caused by the mantle reflectivity (SS precursors). Classical solutions to the general deconvolution problem include frequency-domain or time-domain deconvolution. However, these algorithms do not easily generalize when (1) the reflectivity series is of a much shorter period compared to the source wavelet, (2) the bounce point sampling is sparse or (3) the source wavelet is noisy or hard to estimate. To address these problems, we propose a new technique called SHARP-SS: Sparse High-Resolution Algorithm for Reflection Profiling with SS waves. SHARP-SS is a Bayesian deconvolution algorithm that makes minimal a-priori assumptions on the noise model, source signature and reflectivity structure. We test SHARP-SS using real data examples beneath the NoMelt Pacific Ocean region. We recover a low-velocity discontinuity at a depth of $$\sim 69 \pm 4$$ km which marks the base of the oceanic lithosphere, consistent with previous work derived from surface waves, body wave conversions, and ScS reverberations. We anticipate high-resolution fine mantle stratification imaging using SHARP-SS at locations where seismic stations are sparsely distributed.
more »
« less
Automatic Identification of Mantle Seismic Phases Using a Convolutional Neural Network
Abstract Typical seismic waveform data sets comprise hundreds of thousands to millions of records. Compilation is performed by time‐consuming handpicking of phase arrival times, or signal processing algorithms such as cross‐correlation. The latter generally underperform compared to handpicking. However, differences in picking methods creates variations in models and interpretation of Earth's structure. Here, we exploit the pattern recognition capabilities of Convolutional Neural Networks (CNN). Using a large handpicked data set, we train a CNN model to identify the seismic shear phase SS. This accelerates, automates, and makes consistent data compilation, a task usually completed by visual inspection and influenced by scientists' choices. The CNN model is employed to identify precursors to SS generated by mantle discontinuities. It identifies precursors in stacked and individual seismograms, producing new measurements of the mantle transition zone with quality comparable to handpicked data. This rapid acquisition of high‐quality observations has implications for automation of future seismic tomography studies.
more »
« less
- Award ID(s):
- 1853662
- PAR ID:
- 10447454
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 48
- Issue:
- 18
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
SUMMARY The Earth's mantle transition zone (MTZ) plays a key role in the thermal and compositional interactions between the upper and lower mantle. Seismic anisotropy provides useful information about mantle deformation and dynamics across the MTZ. However, seismic anisotropy in the MTZ is difficult to constrain from surface wave or shear wave splitting measurements. Here, we investigate the sensitivity to anisotropy of a body wave method, SS precursors, through 3-D synthetic modelling and apply it to real data. Our study shows that the SS precursors can distinguish the anisotropy originating from three depths: shallow upper mantle (80–220 km), deep upper mantle above 410 km, and MTZ (410–660 km). Synthetic resolution tests indicate that SS precursors can resolve $$\ge $$3 per cent azimuthal anisotropy where data have an average signal-to-noise ratio (SNR = 7) and sufficient azimuthal coverage. To investigate regional sensitivity, we apply the stacking and inversion methods to two densely sampled areas: the Japan subduction zone and a central Pacific region around the Hawaiian hotspot. We find evidence for significant VS anisotropy (15.3 ± 9.2 per cent) with a trench-perpendicular fast direction (93° ± 5°) in the MTZ near the Japan subduction zone. We attribute the azimuthal anisotropy to the grain-scale shape-preferred orientation of basaltic materials induced by the shear deformation within the subducting slab beneath NE China. In the central Pacific study region, there is a non-detection of MTZ anisotropy, although modelling suggests the data coverage should allow us to resolve at least 3 per cent anisotropy. Therefore, the Hawaiian mantle plume has not produced detectable azimuthal anisotropy in the MTZ.more » « less
-
SUMMARY Despite progress in tomographic imaging of Earth's interior, a number of critical questions regarding the large-scale structure and dynamics of the mantle remain outstanding. One of those questions is the impact of phase-boundary undulations on global imaging of mantle heterogeneity and on geodynamic (i.e. convection-related) observables. To address this issue, we developed a joint seismic-geodynamic-mineral physical tomographic inversion procedure that incorporates lateral variations in the depths of the 410- and 660-km discontinuities. This inversion includes S-wave traveltimes, SS precursors that are sensitive to transition-zone topography, geodynamic observables/data (free-air gravity, dynamic surface topography, horizontal divergence of tectonic plates and excess core-mantle boundary ellipticity) and mineral physical constraints on thermal heterogeneity. Compared to joint tomography models that do not include data sensitivity to phase-boundary undulations in the transition zone, the inclusion of 410- and 660-km topography strongly influences the inference of volumetric anomalies in a depth interval that encompasses the transition zone and mid-mantle. It is notable that joint tomography inversions, which include constraints on transition-zone discontinuity topography by seismic and geodynamic data, yield more pronounced density anomalies associated with subduction zones and hotspots. We also find that the inclusion of 410- and 660-km topography may improve the fit to the geodynamic observables, depending on the weights applied to seismic and geodynamic data in the inversions. As a consequence, we find that the amplitude of non-thermal density anomalies required to explain the geodynamic data decreases in most of the mantle. These findings underline the sensitivity of the joint inversions to the inclusion of transition-zone complexity (e.g. phase-boundary topography) and the implications for the inferred non-thermal density anomalies in these depth regions. Finally, we underline that our inferences of 410- and 660-km topography avoid a commonly employed approximation that represents the contribution of volumetric heterogeneity to SS-wave precursor data. Our results suggest that this previously employed correction, based on a priori estimates of upper-mantle heterogeneity, might be a significant source of error in estimating the 410- and 660-km topography.more » « less
-
SUMMARY We report finite-frequency imaging of the global 410- and 660-km discontinuities using boundary sensitivity kernels for traveltime measurements made on SS precursors. The application of finite-frequency sensitivity kernels overcomes resolution limits in previous studies associated with large Fresnel zones of SS precursors and their interferences with other seismic phases. In this study, we calculate the finite-frequency sensitivities of SS waves and their precursors based on a single-scattering (Born) approximation in the framework of travelling-wave mode summation. The global discontinuity surface is parametrized using a set of triangular gridpoints with a lateral spacing of about 4°, and we solve the linear finite-frequency inverse problem (2-D tomography) based on singular value decomposition (SVD). The new global models start to show a number of features that were absent (or weak) in ray-theoretical back-projection models at spherical harmonic degree l > 6. The thickness of the mantle transition zone correlates well with wave speed perturbations at a global scale, suggesting dominantly thermal origins for the lateral variations in the mantle transition zone. However, an anticorrelation between the topography of the 410-km discontinuity and wave speed variations is not observed at a global scale. Overall, the mantle transition zone is about 2–3 km thicker beneath the continents than in oceanic regions. The new models of the 410- and 660-km discontinuities show better agreement with the finite-frequency study by Lawrence & Shearer than other global models obtained using SS precursors. However, significant discrepancies between the two models exist in the Pacific Ocean and major subduction zones at spherical harmonic degree >6. This indicates the importance of accounting for wave interactions in the calculations of sensitivity kernels as well as the use of finite-frequency sensitivities in data quality control.more » « less
-
Despite progress in tomographic imaging of Earth’s interior, a number of critical questions regarding the large-scale structure and dynamics of the mantle remain outstanding. One of those questions is the impact of phase-boundary undulations on global imaging of mantle heterogeneity and on geodynamic (i.e. convection-related) observables. To address this issue, we developed a joint seismic-geodynamic-mineral physical tomographic inversion procedure that incorporates lateral variations in the depths of the 410- and 660-km discontinuities. This inversion includes S-wave traveltimes, SS precursors that are sensitive to transition-zone topography, geodynamic observables/data (free-air gravity, dynamic surface topography, horizontal divergence of tectonic plates and excess core-mantle boundary ellipticity) and mineral physical constraints on thermal heterogeneity. Compared to joint tomography models that do not include data sensitivity to phase-boundary undulations in the transition zone, the inclusion of 410- and 660-km topography strongly influences the inference of volumetric anomalies in a depth interval that encompasses the transition zone and mid-mantle. It is notable that joint tomography inversions, which include constraints on transition-zone discontinuity topography by seismic and geodynamic data, yield more pronounced density anomalies associated with subduction zones and hotspots. We also find that the inclusion of 410- and 660-km topography may improve the fit to the geodynamic observables, depending on the weights applied to seismic and geodynamic data in the inversions. As a consequence, we find that the amplitude of non-thermal density anomalies required to explain the geodynamic data decreases in most of the mantle. These findings underline the sensitivity of the joint inversions to the inclusion of transition-zone complexity (e.g. phase-boundary topography) and the implications for the inferred non-thermal density anomalies in these depth regions. Finally, we underline that our inferences of 410- and 660-km topography avoid a commonly employed approximation that represents the contribution of volumetric heterogeneity to SS-wave precursor data. Our results suggest that this previously employed correction, based on a priori estimates of uppermantle heterogeneity, might be a significant source of error in estimating the 410- and 660-km topography.more » « less
