Jun Xie

Blind fault mapping requires dense observations over large areas, and distributed acoustic sensing (DAS) provides a viable solution using dark fibers. Seismic attenuation is sensitive to fault‐related structure but relies on reliable amplitude measurements. In DAS data, amplitudes are distorted by non‐attenuation effects, including non‐uniform coupling and small‐scale heterogeneity, limiting their direct use for attenuation imaging. Here, we propose an attenuation imaging method based on ambient noise cross‐correlation functions, in which double virtual shot gathers are used to separate attenuation‐related and non‐attenuation‐related amplitude contributions. Using 6 hr of noise data, we obtain an attenuation coefficient profile along a 7.2‐km DAS array with sub‐kilometer resolution. The image reveals three strong‐attenuation zones, two of which are likely associated with fault‐related structures characterized by strong scattered waves, while the third is more likely associated with a low‐velocity structure. These results highlight the potential of DAS‐based ambient‐noise attenuation imaging for large‐scale, high‐resolution fault exploration.

Some earthquakes in stable continental regions are very shallow, and their seismogenesis mechanism remains unresolved. Here, we focus on the extremely shallow 2020 Mw 5.1 Sparta earthquake sequence in North Carolina. Joint analysis of short-period surface waves from shallow earthquakes and ambient noise-derived empirical Green’s functions reveals a low-velocity zone with strong velocity gradient in the top 3 km of the Sparta-1D velocity model. Furthermore, we validate focal depths in the aftershock catalog with the Rayleigh-wave amplitude spectra method, confirming ∼90% of aftershocks occurred within the shallow low-velocity zone, with event rates decreasing at depths at which shear velocity increases. Geological field studies imply that this feature originates from a shallow weak layer containing intersecting fracture network. The velocity structure, aftershock distribution, and mapped near-surface structures in the Sparta region suggest that fault intersections within a shallow weak layer may provide mechanically favorable conditions for extremely shallow earthquakes.

The Ebao Basin, which locates along the northwest segment of the Qilian‐Haiyuan fault, has experienced several destructive earthquakes in past decades. A 10 km long distributed acoustic sensing (DAS) array was deployed with an existing telecom fiber‐optic cable after the 2022 Mw6.6 Menyuan earthquake, which destroyed high‐speed railways and highways in this region. The DAS array continuously recorded ambient noise and earthquake signals during the 5‐day deployment period. Noise cross‐correlation functions (NCFs) were calculated, and the Rayleigh wave signal clearly emerged on the NCFs. The phase velocities of the fundamental mode between 2.5 and 17 Hz were measured with the modified Frequency‐Bessel transform method. The S‐wave velocity structure along the cable, extending to a depth of 200 m, was constructed using the surface wave tomography method. It consists of three blocks, with velocity variations of up to 12%. P‐wave delay times of regional earthquakes support the lateral variation among the three blocks. Both Vs30 and site amplification predicted with our S‐wave velocity model correlate well with the ground motion induced by local earthquakes. Precursor and coda waves on the NCFs reveal four possible faults, and fault zone scattered waves are also observed on the record of local earthquakes.

In the nearshore area, ocean current display intricate complexities due to interactions among tide, river, and coastline, which makes accurate current modeling challenging. Continuous in situ observation with high spatial and temporal resolution helps to better understand the dynamics of these currents. In this study, we used a 10‐km long submarine fiber‐optic cable with distributed acoustic sensing technology to record seismic signals associated with ocean waves. The current velocity and water depth were obtained from the velocity dispersion using frequency‐wave number analysis matched against theoretical ocean wave propagation equations. The results show remarkable agreement with observation of a nearby current meter, confirming the dominance of tidal currents as well as a small‐scale residual current. The temporal variation of water depth is consistent with observation by a nearby tidal gauge. This study demonstrates the potential of using submarine fiber‐optic cable for long‐term, high‐resolution, near real‐time nearshore current monitoring.

Studying seismic sources and wave propagation in ice plates can provide valuable insights into understanding various processes, such as ice structure dynamics, migration, fracture mechanics and mass balance. However, the harsh environment makes it difficult to conduct in situ dense seismic observations. Consequently, our understanding of the dynamic changes within the ice sheet remains insufficient. We conducted a seismic experiment using a distributed acoustic sensing (DAS) array on a frozen lake, exciting water vibrations through underwater airgun shots. By employing an artificial intelligence method, we were able to detect seismic events that include both high-frequency icequakes and low-frequency events. The icequakes clustered along ice fractures and their activity correlated with local temperature variations. The waveforms of low-frequency events exhibit characteristics of flexural-gravity waves, which offers insights into the properties of the ice plate. Our study demonstrates the effectiveness of an DAS array as an in situ dense seismic network for investigating the internal failure process and dynamic deformation of ice plates such as the ice shelf, which may contribute to an enhanced comprehension and prediction of ice shelf disintegration.

The study of seismic sources and wave propagation in ice plate is helpful to understand the structure, migration, fracture mechanics, mass balance and other processes. However, due to extreme environment, in-situ dense seismic observations are rare and the dynamic changes of the ice plate remain poorly understood. We conduct a seismic experiment with distributed acoustic sensing array on a frozen lake. We excite water vibrations by under-water airgun shots. With an artificial intelligence method, we detected seismic signals including high frequency icequakes and low frequency events. Icequakes cluster along the fractures and correlate with the local temperature variation. The flexural-gravity wave reveals the property of the ice plate. Our study demonstrates the utility of DAS array as an in-situ dense seismic network in illuminating the internal failure process and dynamic deformation of ice plate such as ice shelf, which contributes to understanding and prediction of disintegrations of ice shelves.

In this study, we built a high‐resolution 3D S‐wave velocity model of the South China Sea (SCS) and adjacent areas by the joint inversion of surface wave dispersions retrieved from ambient noise and earthquake data. We first measured Rayleigh wave phase velocity dispersions from the waveforms recorded by 94 broadband seismic stations. Subsequently, we used a generalized least squares inversion scheme with spatially varying resolution to perform 2D tomographic inversion at different periods. Lastly, we performed 1D inversion at different grid points and obtained the 3D S‐wave velocity model in the depth range of 15–250 km. Our model reveals a prominent high velocity (high‐V) anomaly beneath the SCS basin and shows that the lithosphere beneath the SCS basin is about 70–80 km thick. We observe a prominent low velocity (low‐V) anomaly in the asthenosphere beneath the SCS basin, and we interpret this as evidence for the ongoing partial melting of the asthenosphere. An obvious high‐V anomaly is also revealed beneath the Khorat Plateau (KP) in the depth range of 80–150 km, suggesting that the KP has a cold and thick lithosphere and has suffered limited destruction in the Cenozoic era. In the northern part of Kalimantan Island (KI), a prominent low‐V anomaly is shown in the upper 60 km of the lithosphere revealing the upwelling of the asthenosphere. Our findings shed lights on the tectonic evolution of the SCS and adjacent areas.