Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning. [PDF]
Nat Commun, 2020 The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion.
Seydoux L +5 more
europepmc +2 more sources
Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction [PDF]
SensorsSeismic data acquired in the presence of mechanical vibrations or power facilities may be contaminated by strong interferences, significantly decreasing the data signal-to-noise ratio (S/N).
Zhichao Yu, Yuyang Tan, Yiran Lv
doaj +2 more sources
seismic-py: Reading seismic data with Python [PDF]
, 2008 The field of seismic exploration of the Earth has changed dramatically over the last half a century. The Society of Exploration Geophysicists (SEG) has worked to create standards to store the vast amounts of seismic data in a way that will be portable across computer architectures.
Schwehr, Kurt
openaire +3 more sources
The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania [PDF]
Solid Earth, 2021 After the World Health Organization declared COVID-19 a pandemic in March 2020, Romania followed the example of many other countries and imposed a series of restrictive measures, including restricting people's mobility and closing social, cultural, and ...
B. Grecu +7 more
doaj +1 more source
A Seismic Data Acquisition System Based on Wireless Network Transmission. [PDF]
Sensors (Basel), 2021 Huang Y +6 more
europepmc +3 more sources
The potential of self-supervised networks for random noise suppression in seismic data [PDF]
Artificial Intelligence in Geosciences, 2021 Noise suppression is an essential step in any seismic processing workflow. A portion of this noise, particularly in land datasets, presents itself as random noise.
C. Birnie +3 more
semanticscholar +1 more source
Deep-Learning-Based Low-Frequency Reconstruction in Full-Waveform Inversion
Remote Sensing, 2023 Low frequencies are vital for full-waveform inversion (FWI) to retrieve long-scale features and reliable subsurface properties from seismic data. Unfortunately, low frequencies are missing because of limitations in seismic acquisition steps. Furthermore,
Zhiyuan Gu, Xintao Chai, Taihui Yang
doaj +1 more source
Thickness and structure of the martian crust from InSight seismic data
Science, 2021 Single seismometer structure Because of the lack of direct seismic observations, the interior structure of Mars has been a mystery. Khan et al., Knapmeyer-Endrun et al., and Stähler et al.
B. Knapmeyer‐Endrun +38 more
semanticscholar +1 more source
A Natural Images Pre-Trained Deep Learning Method for Seismic Random Noise Attenuation
Remote Sensing, 2022 Seismic field data are usually contaminated by random or complex noise, which seriously affect the quality of seismic data contaminating seismic imaging and seismic interpretation. Improving the signal-to-noise ratio (SNR) of seismic data has always been
Haixia Zhao, Tingting Bai, Zhiqiang Wang
doaj +1 more source
Energies, 2022 We compare sediment vertical methane flux off the Mahia Peninsula, on the Hikurangi Margin, east of New Zealand’s North Island, with a combination of geochemical, multichannel seismic and sub-bottom profiler data.
Richard B. Coffin +5 more
doaj +1 more source