Geophysics
Quantifying the propagation of landslides is a key step for analyzing gravitational risks. In this context, thin-layer models have met a growing success over the past years to simulate the dynamics of gravitational flows, such as debris…
Big data and large-scale machine learning have had a profound impact on science and engineering, particularly in fields focused on forecasting and prediction. Yet, it is still not clear how we can use the superior pattern matching abilities…
A tsunami hazard assessment was conducted for the communities of Sigatoka and Cuvu, located on the island of Viti Levu, Fiji. The study presents an overview of historical seismic and tsunami impact on the Pacific Island nation of Fiji in…
We perform an adjoint waveform tomography using Rayleigh wave Empirical Green's Functions (EGFs) at 10-50 s periods to improve a prior 3-D velocity model of the crust and uppermost mantle beneath the Iranian Plateau. EGFs were derived from…
Multi-azimuth walkaway vertical seismic profiling (VSP) is an established technique for the estimation of in situ slowness surfaces and inferring anisotropy parameters. Normally, this the technique requires the assumption of lateral…
A crucial step in seismic data processing consists in reconstructing the wavefields at spatial locations where faulty or absent sources and/or receivers result in missing data. Several developments in seismic acquisition and interpolation…
Multiple lines of evidence indicate that the 2023 Mw 7.8 Turkey earthquake started on a splay fault, then branched bilaterally onto the nearby East Anatolian Fault (EAF). This rupture pattern includes one feature deemed implausible, called…
Reliable evaluations of geotechnical hazards like landslides and debris flow require accurate simulation of granular flow dynamics. Traditional numerical methods can simulate the complex behaviors of such flows that involve solid-like to…
The use of the probabilistic approach to solve inverse problems is becoming more popular in the geophysical community, thanks to its ability to address nonlinear forward problems and to provide uncertainty quantification. However, such…
We consider an epidemic-type aftershock model (ETAS($F$)) for a large class of distributions $F$ determining the number of direct aftershocks. This class includes Poisson, Geometric, Negative Binomial distributions and many other. Assuming…
This paper contributes an open source software - SMIwiz, which integrates seismic modelling, reverse time migration (RTM), and full waveform inversion (FWI) into a unified computer implementation. SMIwiz has the machinery to do both 2D and…
Faced with the scarcity of clean label data in real scenarios, seismic denoising methods based on supervised learning (SL) often encounter performance limitations. Specifically, when a model trained on synthetic data is directly applied to…
The thermodynamic model of visco-elastic deformable magnetic materials at finite strains is formulated in a fully Eulerian way in rates with the aim to describe thermoremanent paleomagnetism in crustal rocks. The Landau theory applied to a…
Shear rupture and fault slip in crystalline rocks like granite produce large dilation, impacting the spatiotemporal evolution of fluid pressure in the crust during the seismic cycle. To explore how fluid pressure variations are coupled to…
In this study, we present an artificial neural network (ANN)-based approach for travel-time tomography of a volcanic edifice. We employ ray tracing to simulate the propagation of seismic waves through the heterogeneous medium of a volcanic…
Full Waveform Inversion (FWI) is an advanced geophysical inversion technique. In fields such as oil exploration and geology, FWI is used for providing images of subsurface structures with higher resolution. The conventional algorithm…
Muography is an imaging tool based on the attenuation of cosmic muons to observe the density distribution of large objects, such as underground caves or fractured zones. Tomography based on muography measurements -- that is, three…
Global climate change is one of main concern of modern society. To estimate this change usually one estimates the global mean temperature. Measuring and calculating the Earth's average temperature are multi-steps complex processes which…
We consider the problem of 3D seismic inversion from pre-stack data using a very small number of seismic sources. The proposed solution is based on a combination of compressed-sensing and machine learning frameworks, known as…
There is a surging concern regarding the adverse effects of light pollution on human well-being. This manuscript aims to emphasise the deleterious effects of uncontrolled night-light exposure on the health and mood of individuals residing…