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denoising

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Journal Article
Published: 08 April 2024
Bulletin of the Seismological Society of America (2024)
...Louis Quinones; Rigobert Tibi ABSTRACT Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted...
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Journal Article
Journal: Geophysics
Published: 22 March 2024
Geophysics (2024) E73–E85.
... geoelectrical structures decreases when the data collected in mining areas are of poor quality and contain complex anthropogenic noise, leading to distorted apparent resistivity-phase curves and posing significant challenges for mineral exploration. To effectively denoise AMT data, we develop a new denoising...
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Journal Article
Journal: Geophysics
Published: 26 February 2024
Geophysics (2024) V209–V217.
...Lihua Liu; Tianyao Hao; Yonggang Guo; Chuanchuan Lü; Sujing Wang ABSTRACT Denoising is a critical step in signal processing. We develop a method for random noise reduction in active source seismic data using spectrum reconstruction. Two methods are developed for modifying the observed data’s...
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Journal Article
Published: 17 October 2023
Seismological Research Letters (2024) 95 (1): 378–396.
... networks have been used for automatically picking dispersions. Dispersion curves are picked based on deep learning mainly for denoising these spectrograms. In several studies, the neural network was solely trained, and its performance was verified for the denoising. However, they all learn single‐source...
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Journal Article
Journal: Geophysics
Published: 13 October 2023
Geophysics (2023) 88 (6): WC145–WC162.
... applied to seismic data denoising as well as reconstruction and achieved good performance compared with traditional methods. However, relatively few CNN-based studies have been done on the simultaneous denoising and reconstruction of seismic data, especially for the complex DAS seismic data with a low...
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Journal Article
Journal: Geophysics
Published: 11 October 2023
Geophysics (2024) 89 (1): WA39–WA51.
... denoising network into the plug-and-play (PnP) framework. A novel network is introduced whose design extends an existing blind-spot network architecture for partially coherent noise (i.e., correlated in time). The network is then trained directly on the noisy input data at each step of the PnP algorithm...
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Journal Article
Published: 28 September 2023
Seismological Research Letters (2023) 94 (6): 2840–2851.
...Yangkang Chen; Alexandros Savvaidis; Sergey Fomel Abstract Passive seismic denoising is mostly performed using a simple band‐pass filter, which can be problematic when signal and noise share the same frequency band. More advanced passive seismic denoising methods take advantage of fixed‐basis...
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Journal Article
Journal: Geophysics
Published: 05 September 2023
Geophysics (2023) 88 (6): WC69–WC89.
... severe and diverse types of noise with varying amplitudes, resulting in a low signal-to-noise ratio (S/N) and making the extraction of hidden signals a challenging task. Therefore, exploring a high-efficiency and high-generalization denoising method is crucial for improving the S/N of DAS data...
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Journal Article
Journal: Geophysics
Published: 16 June 2023
Geophysics (2023) 88 (4): L53–L63.
... in a low-S/N scenario, we have developed an end-to-end network that jointly performs denoising and classification tasks (JointNet) and applied it to fiber-optic distributed acoustic sensing (DAS) microseismic data. JointNet consists of 2D convolution layers that are suitable for extracting features...
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Journal Article
Journal: Geophysics
Published: 13 June 2023
Geophysics (2023) 88 (4): V317–V332.
... method, where the size of each patch is 48 × 48. To adapt to the proposed network, we stretch the segmented 2D patches into 1D signals input to the network. In this study, one synthetic and three field data sets are used to test the denoising performance of our proposed network. Our proposed...
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Journal Article
Published: 07 March 2023
Seismological Research Letters (2023) 94 (3): 1703–1714.
... passive seismic data, 3D SS‐precursor denoising, 2D receiver function data denoising, and 2D cascaded denoising workflow of DAS data. We will only briefly introduce each example because all the details can be found in the reproducible scripts. * Corresponding author: chenyk2016@gmail.com 21...
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Journal Article
Journal: Geophysics
Published: 16 January 2023
Geophysics (2023) 88 (1): WA345–WA360.
...-consistent loss to replace the commonly used L1 norm or L2 norm to train the network. The obtained hybrid training set containing unpaired synthetic and unpaired field data sets for model pretraining and fine tuning effectively improves the denoising performance of the seismic field data. In summary...
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Journal Article
Journal: Geophysics
Published: 04 January 2023
Geophysics (2023) 88 (1): E13–E28.
..., and the noise in MT data is quite distinct from clean data in morphological features. By performing the signal-noise identification and data prediction, we develop a deep learning method to denoise MT data containing strong noise. First, we use the convolutional neural network (CNN) to learn the feature...
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Journal Article
Journal: Geophysics
Published: 27 December 2022
Geophysics (2023) 88 (1): WA267–WA279.
... various types of random noise interferences, which are subsequently added to the IP signals. Then, a denoising autoencoder deep neural network structure is built and trained by using noisy signals as input samples and pure signals as output samples. The resulting optimum network is capable...
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Journal Article
Published: 23 December 2022
Bulletin of the Seismological Society of America (2023) 113 (2): 548–561.
... by the regional network of the University of Utah Seismograph stations. The denoising methods, consisting of approaches based on nonlinear thresholding of continuous wavelet transforms (CWTs, e.g., Langston and Mousavi, 2019 ), convolutional neural network (CNN) denoising ( Tibi et al. , 2021 ), and frequency...
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