Results 1 to 10 of about 101,769 (259)
Deep-Learning Inversion of Seismic Data [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 We propose a new method to tackle the mapping challenge from time-series data to spatial image in the field of seismic exploration, i.e., reconstructing the velocity model directly from seismic data by deep neural networks (DNNs). The conventional way of addressing this ill-posed inversion problem is through iterative algorithms, which suffer from poor
Shucai Li, Bin Liu, Yuxiao Ren
exaly +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
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
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
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, 2022 Broadband seismic waveform data from the EOS-DMH-MEC network used in the relocation and gCAP inversion of earthquake focal mechanisms.
Wardah Fadil
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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
Characterising Seismic Data [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 When a seismologist analyses a new seismogram it is oftenuseful to have access to a set of similar seismograms.For example if she tries to determine the event, if any,that caused the particular readings on her seismogram.So, the question is: when are two seismograms similar?To dene such a notion of similarity, we rst preprocessthe seismogram by a ...
Bertens, Roel, Siebes, Arno
openaire +2 more sources
Frontiers in Earth Science, 2022 This study proposes a high-resolution processing technique for seismic data based on the improved synchrosqueezing transform (SST). The SST rearranges the complex spectrum of the wavelet transform along the frequency axis.
Chen Yu, Shuyan Wang, Lifang Cheng
doaj +1 more source
Remote Sensing, 2023 The high-resolution Moho depth model is required in various geophysical studies. However, the available models’ resolutions could be improved for this purpose.
Arash Dashtbazi +3 more
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The Seismic Analyzer: Interpreting and Illustrating 2D Seismic Data [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2008 We present a toolbox for quickly interpreting and illustrating 2D slices of seismic volumetric reflection data. Searching for oil and gas involves creating a structural overview of seismic reflection data to identify hydrocarbon reservoirs. We improve the search of seismic structures by precalculating the horizon structures of the seismic data prior to
Patel, Daniel +4 more
openaire +4 more sources