Results 21 to 30 of about 24,964,284 (390)
Deep Prior-Based Unsupervised Reconstruction of Irregularly Sampled Seismic Data
IEEE Geoscience and Remote Sensing Letters, 2022 Irregularity and coarse spatial sampling of seismic data strongly affect the performances of processing and imaging algorithms. Therefore, interpolation is a usual preprocessing step in most of the processing workflows. In this work, we propose a seismic
F. Kong +5 more
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Upper mantle structure of Mars 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.
Amir Khan +29 more
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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
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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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2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2015 The focal mechanism of an earthquake and fault plane solutions provide insight into the geology of an area. The objective of this paper is to give a means of better understanding fault movement when an earthquake occurs. In this paper we present an interactive 3D visualisation of possible fault plane solutions, which are usually represented as 2D ...
Ivančić, Matejka +2 more
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Seismic Data Reconstruction Using Deep Bidirectional Long Short-Term Memory With Skip Connections
IEEE Geoscience and Remote Sensing Letters, 2021 Due to environmental and economic constraints on their acquisition, seismic data are always irregularly sampled and include bad or missing traces, which can cause problems for seismic data processing.
D. Yoon, Z. Yeeh, J. Byun
semanticscholar +1 more source
Deep Convolutional Neural Network With Attention Module for Seismic Impedance Inversion
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Seismic inversion is an approach to obtain the physical properties of the Earth layers from the seismic data, which aids in reservoir characterization. In seismic inversion, spatially variable physical parameters, such as impedance ($Z$), wave velocities
Vineela Chandra Dodda +4 more
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The Denoising of Desert Seismic Data Based on Cycle-GAN With Unpaired Data Training
IEEE Geoscience and Remote Sensing Letters, 2021 The seismic data with high quality are the essential foundation of imaging and interpretation. However, the real seismic data are inevitably contaminated by noise, which affects the subsequent processing and interpretation of seismic data.
Yue Li, Hongzhou Wang, Xintong Dong
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Geosciences, 2020 The presented study is devoted to the subsurface Upper Jurassic carbonate buildups and surrounding stratified inter-buildup deposits in the hitherto less recognized area, in comparison with other parts of the northern Tethyan shelf in Poland and Europe ...
Łukasz Słonka, Piotr Krzywiec
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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, R., Siebes, A.P.J.M.
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