Search Results - "Yuan, Sanyi"

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  1. 1

    Seismic Waveform Classification and First-Break Picking Using Convolution Neural Networks by Yuan, Sanyi, Liu, Jiwei, Wang, Shangxu, Wang, Tieyi, Shi, Peidong

    Published in IEEE geoscience and remote sensing letters (01-02-2018)
    “…Regardless of successful applications of the convolutional neural networks (CNNs) in different fields, its application to seismic waveform classification and…”
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  2. 2

    Sparse Bayesian Learning-Based Time-Variant Deconvolution by Yuan, Sanyi, Wang, Shangxu, Ma, Ming, Ji, Yongzhen, Deng, Li

    “…In seismic exploration, the wavelet-filtering effect and Q-filtering (amplitude attenuation and velocity dispersion) effect blur the reflection image of…”
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  3. 3

    Porosity prediction using semi-supervised learning with biased well log data for improving estimation accuracy and reducing prediction uncertainty by Sang, Wenjing, Yuan, Sanyi, Han, Hongwei, Liu, Haojie, Yu, Yue

    Published in Geophysical journal international (12-10-2023)
    “…SUMMARY Porosity characterization is of profound significance for seismic inversion and hydrocarbon prediction. Although semi-supervised learning (SSL) based…”
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  4. 4

    Spectral sparse Bayesian learning reflectivity inversion by Yuan, Sanyi, Wang, Shangxu

    Published in Geophysical Prospecting (01-07-2013)
    “…ABSTRACT A spectral sparse Bayesian learning reflectivity inversion method, combining spectral reflectivity inversion with sparse Bayesian learning, is…”
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  5. 5

    Automatic velocity analysis using interpretable multimode neural networks by Zhang, Haifeng, Yuan, Sanyi, Zeng, Huahui, Yuan, Huan, Gao, Yang, Wang, Shangxu

    Published in Geophysical journal international (01-10-2023)
    “…SUMMARY Seismic velocity analysis is the basis for seismic imaging and understanding complex subsurface geological structures. Although the performance of…”
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  6. 6

    Intelligent velocity picking and uncertainty analysis based on the Gaussian mixture model by Wang, Xiaowei, Gao, Yang, Chen, Chang, Yuan, Huan, Yuan, Sanyi

    Published in Acta geophysica (01-12-2022)
    “…The stacking velocity is often obtained manually. However, manually picking is inefficient and is easily affected by subjective factors such as the priori…”
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  7. 7

    Prestack simultaneous inversion of P-wave impedance and gas saturation using multi-task residual networks by Sang, Wenjing, Ding, Zhiqiang, Li, Mingxuan, Liu, Xiwu, Liu, Qian, Yuan, Sanyi

    Published in Acta geophysica (01-04-2024)
    “…It is challenging to realize the gas saturation (GS) estimation via the integration of seismic data and more complementary data (e.g., elastic attributes) in a…”
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  8. 8

    Gas Reservoir Characterization Using Lp-Norm Constrained High-Resolution Seismic Spectral Attributes by Wang, Tieyi, Yuan, Sanyi, Wang, Rui, Yang, Shan, Wang, Shangxu

    Published in Pure and applied geophysics (01-11-2020)
    “…Reservoir prediction is often a primary objective in seismic exploration, especially for deep hydrocarbon detection with its potential for assessing oil and…”
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  9. 9

    Traveltime-based reflection full-waveform inversion for elastic medium by Wang, Guanchao, Wang, Shangxu, Du, Qizhen, Yuan, Sanyi

    Published in Journal of applied geophysics (01-06-2017)
    “…The main difficulty of full waveform inversion (FWI) based on local optimization methods is that it tends to trap in local minima or cycle-skipping associated…”
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  10. 10

    Inversion-based non-stationary normal moveout correction along with prestack high-resolution processing by Wang, Di, Yuan, Sanyi, Liu, Tao, Li, Shengjun, Wang, Shangxu

    Published in Journal of applied geophysics (01-08-2021)
    “…Seismic wave propagated in viscoelastic media always suffers from amplitude attenuation and velocity dispersion. It not only reduces seismic resolution, but…”
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  11. 11

    Sparse Bayesian Learning-Based Seismic Denoise by Using Physical Wavelet as Basis Functions by Deng, Li, Yuan, Sanyi, Wang, Shangxu

    Published in IEEE geoscience and remote sensing letters (01-11-2017)
    “…Attenuating random noise is a fundamental yet necessary step for subsequent seismic image processing and interpretation. We introduce a sparse Bayesian…”
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  12. 12

    Surface-wave dispersion curves extraction method from ambient noise based on U-net++ and density clustering algorithm by Hu, Wei, Zhang, Hao, Sang, Wenjing, Anna, Sowiżdżał, Yuan, Shichuan, Yuan, Sanyi

    Published in Journal of applied geophysics (01-06-2023)
    “…It is crucial to accurately and rapidly extract dispersion curves of surface waves from ambient noise recordings for inverting the subsurface shear (S) wave…”
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  13. 13

    Edge-preserving noise reduction based on Bayesian inversion with directional difference constraints by Yuan, Sanyi, Wang, Shangxu

    Published in Journal of geophysics and engineering (01-04-2013)
    “…Attenuating random noise while preserving edges and structures of seismic signals is of great significance for seismic interpretation and inversion. An…”
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  14. 14

    Multi-trace stochastic sparse-spike inversion for reflectivity by Ji, Yongzhen, Yuan, Sanyi, Wang, Shangxu

    Published in Journal of applied geophysics (01-02-2019)
    “…Sparse-spike reflectivity inversion can be generally regarded as the combination of a non-linear problem of finding the locations and a linear problem of…”
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  15. 15

    Enhancing low-wavenumber components of full-waveform inversion using an improved wavefield decomposition method in the time-space domain by Lian, Shijie, Yuan, Sanyi, Wang, Guanchao, Liu, Tian, Liu, Ying, Wang, Shangxu

    Published in Journal of applied geophysics (01-10-2018)
    “…Full-waveform inversion (FWI) is a successful technique that attempts to build high-resolution velocity models by minimizing the residuals between observed and…”
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  16. 16

    Multichannel sparse spike deconvolution based on dynamic time warping by Zhao, Xiaowei, Wang, Shangxu, Yuan, Sanyi, Cheng, Liang, Cai, Youjun

    Published in Acta geophysica (01-06-2021)
    “…Seismic sparse spike deconvolution is commonly used to invert for subsurface reflectivity series and is usually implemented as an inversion scheme…”
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  17. 17

    Frequency-domain sparse Bayesian learning inversion of AVA data for elastic parameters reflectivities by Ji, Yongzhen, Yuan, Sanyi, Wang, Shangxu, Deng, Li

    Published in Journal of applied geophysics (01-10-2016)
    “…The prestack amplitude variation with angle (AVA) inversion method utilising angle information to obtain the elastic parameters estimation of subsurface rock…”
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  18. 18

    Building a good initial model for full-waveform inversion using frequency shift filter by Wang, Guanchao, Wang, Shangxu, Yuan, Sanyi, Lian, Shijie

    Published in Journal of applied geophysics (01-05-2018)
    “…Accurate initial model or available low-frequency data is an important factor in the success of full waveform inversion (FWI). The low-frequency helps…”
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  19. 19

    The influence of errors in the source wavelet on inversion‐based surface‐related multiple attenuation by Yuan, Sanyi, Wang, Shangxu, Yuan, Fengfan, Liu, Yong

    Published in Geophysical Prospecting (01-03-2018)
    “…ABSTRACT We investigate the influence of source wavelet errors on inversion‐based, surface‐related multiple attenuation, in order to address how the inverted…”
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