Geophysics
We detect the recent M8.8 mega-earthquake in Eastern Russia, on a 4400km long active telecom cable in the Pacific Ocean. The resolution achieved 100m represents the highest spatial resolution, the largest number of ocean-bottom sensors, and…
The horizontal-to-vertical spectral ratio (HVSR) technique is widely used to determine site fundamental periods from ambient noise recordings, but relating the observed peak to a specific impedance contrast within layered soils remains…
During an earthquake, slip occurs in a localised shear zone that features a heavily granulated fault core that can be characterised as a shear band. We study the formation of this fault core in a granular rock such as sandstone by…
Hourglass is an equal-area pseudocylindrical map projection developed by John P. Snyder in mid 1940s. It was never published in a detailed way by its author, and only a couple of references exist in literature since 1991, both of them…
Seismic velocity inversion is a key task in geophysical exploration, enabling the reconstruction of subsurface structures from seismic wave data. It is critical for high-resolution seismic imaging and interpretation. Traditional…
The propagation of waves through the marginal ice zone (MIZ) and deeper into pack ice is a key phenomenon that influences the breakup and drift of sea ice. When waves in ice propagate through a solid, non-cracked, thick enough sea ice…
The inversion of surface wave dispersion curves poses significant challenges due to the non-uniqueness, nonlinear, & ill-posed nature of the problem. Local search methods get trapped in suboptimal minima, whereas global search methods are…
The success of building a high-resolution velocity model using machine learning is hampered by generalization limitations that often limit the success of the approach on field data. This is especially true when relying on neural operators…
Explainable artificial intelligence (XAI) methods have been applied to interpret deep learning model results. However, applications that integrate XAI with established hydrologic knowledge for process understanding remain limited. Here we…
In this article, we present a novel Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, designed as a real-time Volcano-seismic Signal Recognition (VSR) system for Distributed Acoustic…
Subsurface lithological heterogeneity presents challenges for traditional geophysical methods, particularly in resolving nonlinear electrical resistivity and induced polarization (IP) relationships. This study introduces a data-driven…
Seismic wave generation creates labeled waveform datasets for source parameter inversion, subsurface analysis, and, notably, training artificial intelligence seismology models. Traditionally, seismic wave generation has been time-consuming,…
The Marchenko method is a powerful tool for reconstructing full-wavefield Green's functions using surface-recorded seismic data. These Green's functions can then be utilized to produce subsurface images that are not affected by artifacts…
The Fe-Ni alloy is believed to be the main component of Earth's core. Yet, a comprehensive understanding of phase equilibria near the melting point of this alloy under core conditions is still lacking, leaving the effect of nickel…
To understand the dynamics of partially molten mantle in terrestrial bodies, we carried out a linear perturbation analysis and 2-D numerical simulations of magma-matrix flow in a horizontal layer, where decompression melting generates magma…
The Laser Interferometer Lunar Antenna (LILA), a concept for measuring sub-Hz gravitational waves on the Moon, would use laser strainmeters to obtain extremely sensitive strain measurements from 1 mHz to 1 Hz. With proposed strain…
Full waveform inversion (FWI) iteratively updates the velocity model by minimizing the difference between observed and simulated data. Due to the high computational cost and memory requirements associated with global optimization…
Forecasting earthquake sequences remains a central challenge in seismology, particularly under non-stationary conditions. While deep learning models have shown promise, their ability to generalize across time remains poorly understood. We…
Farmed landscapes provide a natural laboratory to test how management reshapes near-surface hydrodynamics. Combining distributed acoustic sensing with physics-based hydromechanical modeling, we tracked minute-resolution, meter-scale changes…
Efforts to estimate the magma decompression rate from the vesicular texture of volcanic products have progressed through the development of theoretical models and laboratory experiments. The theoretical model is based on nucleation theory,…