Imaging before an unimaginable eruption: Volcanic super-eruptions eject thousands of times the volume of the largest documented eruptions over human history. Several “supervolcanoes” capable of this type of unimaginable devastation dot the surface of Earth today. Jaxybulatov et al. use seismic background noise to estimate the size and maturity of one of the world's largest volcanic reservoirs, the Toba caldera in northern Sumatra. Magma storage under the caldera occurs slowly over time, in the form of horizontal layers of magma injected into the crust. These magmatic sills are documented to 20 kilometers below the surface, but more sills could exist even deeper. The characterization of magma storage in large volcanic systems may help us to prepare for future volcanic super-eruptions. Science , this issue p. 617

We used 6 hr of continuous seismic noise records from 2320 four-component sensors of the Valhall ‘Life of Field Seismic’ network to compute cross-correlations (CCs) of ambient seismic noise. A beamforming analysis showed that at low frequencies (below 2 Hz) the seismic noise sources were spatially homogeneously distributed, whereas at higher frequencies (2–30 Hz), the dominant noise source was the oil platform at the centre of the network. Here, we performed an ambient noise surface wave tomography at frequencies below 2 Hz. We used vertical-component geophones CCs to extract and measure the Scholte waves group velocities dispersion curves that were then processed with a set of quality criteria and inverted to build group velocity maps of the Valhall area. Although Scholte wave group velocity depends on S wave, our group velocity maps show features similar to that was previously obtained from P-wave velocity full-waveform inversion of an active seismic data set. Since the dominant noise source at high frequency (above 3 Hz) was the oil platform, we determined a 2-D S-wave velocity model along a profile aligned with the platform by inverting group velocity dispersion curves of Love waves from transverse-component geophones CCs. We found that S-wave velocity down to 20 m was low and varied along the profile, and could be used to estimate S-wave static.

Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth is found to be nearly impossible to achieve. We show that seismic noise generated by vehicle traffic, and especially heavy freight trains, can be turned into a powerful repetitive seismic source to continuously probe the Earth's crust at a few kilometers depth. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train‐generated seismic signals allow daily reconstruction of direct P body waves probing the San Jacinto Fault down to 4‐km depth. This new approach may facilitate monitoring most of the San Andreas Fault system using the railway and highway network of California.

Researchers monitor southwest Greenland’s ice sheet mass changes by measuring seismic velocity variations in Greenland’s crust.

We cross correlate 4 years of seismic noise from the seismic network of Piton de la Fournaise Volcano (La Réunion Island) to measure the group velocity dispersion curves of Rayleigh and Love waves. We average measurements from vertical and radial components to obtain 577 Rayleigh wave dispersion curves. The transverse components provided 395 Love wave dispersion curves. We regionalize the group velocities measurements into 2‐D velocity maps between 0.4 and 8 s. Finally, we locally inverted these maps for a pseudo 3‐D anisotropic shear‐velocity model down to 3 km below the sea level using a Neighborhood Algorithm. The 3‐D isotropic shear‐wave model shows three distinct high‐velocity anomalies surrounded by a low‐velocity ring. The anomaly located below the present “Plaine des Sables” could be related to an old intrusive body at the location of the former volcanic center before it migrated toward its present location. The second high‐velocity body located below the summit of the volcano likely corresponds to the actual preferential dyke intrusion zone as highlighted by the seismicity. The third high‐velocity anomaly located below the “Grandes Pentes” and the “Grand Brûlé” areas and is an imprint of the solidified magma chamber of the dismantled “Les Alizés” Volcano. Radial anisotropy shows two main anomalies: positive anisotropy above sea level highlighting the recent edifice of Piton de la Fournaise with an accumulation of horizontal lava flows and the second one below the sea level with a negative anisotropy corresponding to the ancient edifice of Piton de la Fournaise dominated by intrusions of vertical dykes.

This study presents a depth inversion of Scholte wave group and phase velocity maps obtained from cross-correlation of 6.5 hr of noise data from the Valhall Life of Field Seismic network. More than 2 600 000 vertical–vertical component cross-correlations are computed from the 2320 available sensors, turning each sensor into a virtual source emitting Scholte waves. We used a traditional straight-ray surface wave tomography to compute the group velocity map. The phase velocity maps have been computed using the Eikonal tomography method. The inversion of these maps in depth are done with the Neighbourhood Algorithm. To reduce the number of free parameters to invert, geological a priori information are used to propose a power-law 1-D velocity profile parametrization extended with a gaussian high-velocity layer where needed. These parametrizations allowed us to create a high-resolution 3-D S-wave model of the first 600 m of the Valhall subsurface and to precise the locations of geological structures at depth. These results would have important implication for shear wave statics and monitoring of seafloor subsidence due to oil extraction. The 3-D model could also be a good candidate for a starting model used in full-waveform inversions.