English
Related papers

Related papers: Probing slow earthquakes with deep learning

200 papers

We present and evaluate the capacity of a deep neural network to learn robust features from EEG to automatically detect seizures. This is a challenging problem because seizure manifestations on EEG are extremely variable both inter- and…

Machine Learning · Computer Science 2016-08-02 Pierre Thodoroff , Joelle Pineau , Andrew Lim

Post-disaster inspections are critical to emergency management after earthquakes. The availability of data on the condition of civil infrastructure immediately after an earthquake is of great importance for emergency management.…

Signal Processing · Electrical Eng. & Systems 2020-09-25 Xiao Liang , Seyed Omid Sajedi

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…

Geophysics · Physics 2023-11-02 Maayan Gelboim , Amir Adler , Yen Sun , Mauricio Araya-Polo

The final size of an earthquake typically cannot be predicted from its ongoing seismic radiation. Expanding observations reveal distinct exceptions, such as slow earthquakes, injection-induced seismicity, and earthquake swarms, in which…

Geophysics · Physics 2026-05-19 Dye SK Sato , Keisuke Yoshida

Low-frequency earthquakes (LFEs) are small magnitude earthquakes, with typical magnitude less than 2, and reduced amplitudes at frequencies greater than 10 Hz relative to ordinary small earthquakes. Their occurrence is often associated with…

Geophysics · Physics 2023-01-02 Ariane Ducellier , Kenneth C. Creager

Deep learning techniques for processing large and complex datasets have unlocked new opportunities for fast and reliable earthquake analysis using Global Navigation Satellite System (GNSS) data. This work presents a deep learning model,…

Seismic data often contain gaps due to various obstacles in the investigated area and recording instrument failures. Deep learning techniques offer promising solutions for reconstructing missing data parts by leveraging existing…

Geophysics · Physics 2024-04-04 Mohammad Mahdi Abedi , David Pardo , Tariq Alkhalifah

Earthquake science and seismology rely on the ability to associate seismic waves with their originating earthquakes. Earthquake detection algorithms based on deep learning have progressed rapidly and now routinely detect microearthquakes…

Geophysics · Physics 2024-12-13 Cheng Shi , Giulio Poggiali , Chris Marone , Maarten V. de Hoop , Ivan Dokmanić

Simulating dynamic rupture propagation is challenging due to the uncertainties involved in the underlying physics of fault slip, stress conditions, and frictional properties of the fault. A trial and error approach is often used to…

Geophysics · Physics 2019-06-17 Sabber Ahamed , Eric G. Daub

Subduction megathrusts release stress not only seismically through earthquakes, but also through creep and transient slow deformation, called slow slip events (SSEs). Understanding the interplay between fast and slow slip is essential for…

The exact mechanisms leading to an earthquake are not fully understood and the space-time structural features are non-trivial. Previous studies suggest the seismicity of very low intensity earthquakes, known as micro-earthquakes, may…

Applications · Statistics 2017-05-12 Arash Andalib , Raheleh Baharloo , Jose C. Principe

A fundamental mystery in earthquake physics is ``how can an earthquake be triggered by distant seismic sources?'' Here, we use discrete element method simulations of a granular layer, during stick-slip, that is subject to transient…

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the…

Geophysics · Physics 2017-03-07 G. F. Panza , A. Peresan , F. Sansò , M. Crespi , A. Mazzoni , A. Nascetti

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to…

Fast and accurate magnitude prediction is the key to the success of earthquake early warning. We have proposed a new approach based on deep learning for P-wave magnitude prediction (EEWNet), which takes time series data as input instead of…

Geophysics · Physics 2020-07-07 Yanwei Wang , Zifa Wang , Zhenzhong Cao , Jingyan Lan

We developed a new strategy for Disaster Risk Reduction for gravitational slope failure: We propose a simple method for real-time early warning of gravity-driven failures that considers and exploits both the heterogeneity of natural media…

Geophysics · Physics 2018-12-14 Jerome Faillettaz , Martin Funk , Jan Beutel , Andreas Vieli

Forest fire models may be interpreted as a simple model for earthquake occurrence by translating trees and fire into stressed segments of a fault and their rupture, respectively. Here we adopt a twodimensional forest-fire model in…

Geophysics · Physics 2015-12-17 Tetsuya Mitsudo , Takahiro Hatano , Naoyuki Kato

A model for fault dynamics consisting of two rough and rigid brownian profiles that slide one over the other is introduced. An earthquake occurs when there is an intersection between the two profiles. The energy release is proportional to…

Condensed Matter · Physics 2019-08-17 V. De Rubeis , R. Hallgass , V. Loreto , G. Paladin , L. Pietronero , P. Tosi

Determining earthquake hypocenters and focal mechanisms requires precisely measured P-wave arrival times and first-motion polarities. Automated algorithms for estimating these quantities have been less accurate than estimates by human…

Geophysics · Physics 2018-08-15 Zachary E. Ross , Men-Andrin Meier , Egill Hauksson

Earth structural heterogeneities have a remarkable role in the petroleum economy for both exploration and production projects. Automatic detection of detailed structural heterogeneities is challenging when considering modern machine…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Luiz Schirmer , Guilherme Schardong , Vinícius da Silva , Rogério Santos , Hélio Lopes