Pengyuan Sun

China National Petroleum Corporation (China)

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Jianlei Zhang

Nankai University

Hui Zhou

China University of Petroleum, Beijing

Hanming Chen

China University of Petroleum, Beijing

Jinwei Fang

China University of Mining and Technology

Zhongping Qian

China National Petroleum Corporation (China)

Baohua Kong

Northeast Agricultural University

Xiangyang Li

University of Chinese Academy of Sciences

Qingchen Zhang

Institute of Geodesy and Geophysics

Ying-ao Zhu

Northeast Agricultural University

Yufeng Wang

China University of Geosciences

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China National Petroleum Corporation (China)

Northeast Agricultural University

China University of Petroleum, Beijing

Chinese Academy of Sciences

China University of Petroleum, East China

University of Chinese Academy of Sciences

Jilin University

University of Science and Technology of China

Research Institute of Petroleum Exploration and Development

Ocean University of China

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3D elastic full waveform inversion using frequency selection strategy

Jinwei Fang Hui Zhou Qingchen Zhang Hanming Chen Zheng‐Sen Zhou

Full waveform inversion (FWI) serves as a useful tool to quantitatively investigate the properties of the media. One of the biggest challenges is its huge computational cost, especially for the three-dimensional (3D) case. Multisource approach is a helpful method to speed up full waveform inversion, as well as migration. However, current elastic FWI algorithms with simultaneous sources, such as random time series and random polarity methods may be subjected to crosstalk noise, which is a tough problem and affects inversion quality. We develop a novel 3D elastic full waveform inversion method with multisource frequency encoding based on phase sensitive detection (PSD) without the crosstalk. We propagate seismic wavefield excited by the encoded sources with a series of single frequency components. Extracting the wavefield corresponding to each single frequency source by PSD and calculating the total gradients of the objective function with respect to model parameters by summing the gradients of all single frequencies, we can effectively avoid the crosstalk in our multisource FWI algorithm. The numerical examples show that our scheme can effectively separate the wavefield of a single source from the blended wavefields and obtain crosstalk-free inversion results. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 9:20 AM Presentation Time: 10:35 AM Location: Poster Station 10 Presentation Type: Poster

Crosstalk

10.1190/segam2019-3215278.1

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Data-driven low-frequency signal recovery using deep-learning predictions in full-waveform inversion

Geophysics (2020)

Jinwei Fang Hui Zhou Yunyue Elita Li Qingchen Zhang Lingqian Wang

The lack of low-frequency signals in seismic data makes the full-waveform inversion (FWI) procedure easily fall into local minima leading to unreliable results. To reconstruct the missing low-frequency signals more accurately and effectively, we have developed a data-driven low-frequency recovery method based on deep learning from high-frequency signals. In our method, we develop the idea of using a basic data patch of seismic data to build a local data-driven mapping in low-frequency recovery. Energy balancing and data patches are used to prepare high- and low-frequency data for training a convolutional neural network (CNN) to establish the relationship between the high- and low-frequency data pairs. The trained CNN then can be used to predict low-frequency data from high-frequency data. Our CNN was trained on the Marmousi model and tested on the overthrust model, as well as field data. The synthetic experimental results reveal that the predicted low-frequency data match the true low-frequency data very well in the time and frequency domains, and the field results show the successfully extended low-frequency spectra. Furthermore, two FWI tests using the predicted data demonstrate that our approach can reliably recover the low-frequency data.

Maxima and minima

10.1190/geo2020-0159.1

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Citations (61)

Pseudo-analytical finite-difference elastic-wave extrapolation based on the k-space method

Geophysics (2017)

Xufei Gong Qizhen Du Qiang Zhao Chengfeng Guo Pengyuan Sun

Cost-effective elastic-wave modeling is the key to practical elastic reverse time migration and full-waveform inversion implementations. We have developed an efficient elastic pseudo-analytical finite-difference (PAFD) scheme for elastic-wave extrapolation. The elastic PAFD scheme is based on a modified pseudo-spectral method, k-space method, in which a pseudo-analytical operator is used to ensure the high accuracy of elastic-wave extrapolation. However, the k-space method is motivated for a pure wave mode, and thus its application in coupled first-order elastic-wave equations may cause the elastic pseudo-analytical operators to suffer from crosstalk between the P- and S-wavefields. The approaches presented attempt to overcome these shortcomings by introducing two improvements to achieve the goal. This is done, first, by performing a predictor-corrector strategy in first-order elastic-wave equations to eliminate those errors during wave extrapolation. Considering the massive computational cost in the spectral domain, we have developed an efficient elastic PAFD implementation, in which an innovative model-adaptive finite-difference coefficient-predicted scheme is provided to reduce the computational cost of elastic pseudo-analytical operator differencing. Dispersion analysis demonstrates the flexibility with varying velocity and superior performance of our PAFD scheme for spatial and temporal dispersion suppression than the existing Taylor-expansion-based scheme. Under the same simulation parameters, several numerical examples prove that the elastic PAFD scheme can provide more accurate simulation results, whereas the conventional scheme suffers from spatial or temporal dispersion errors, even in complex heterogeneous media.

Finite difference

Seismic migration

Operator (biology)

10.1190/geo2017-0088.1

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The Combined Compact Difference Scheme Applied to Shear-Wave Reverse-Time Migration

Applied Sciences (2022)

Chengyao Zhou Wei Wu Pengyuan Sun Wenjie Yin Xiangyang Li

In this paper, the combined compact difference scheme (CCD) and the combined supercompact difference scheme (CSCD) are used in the numerical simulation of the shear-wave equation. According to the Taylor series expansion and shear-wave equation, the fourth-order discrete scheme of the displacement field is established; then, the CCD and CSCD schemes are used to calculate the spatial derivative of the displacement field. Additionally, the accuracy, dispersion, and stability of the CCD and CSCD are analyzed, and numerical simulation analyses are carried out using 1D uniform models. Lastly, based on the processing of artificial boundary reflection using PML boundary conditions, shear-wave reverse-time migrations are carried out using synthetic data. The results show that (1) CCD and CSCD have smaller truncation errors, higher simulation precision, and lower numerical dispersion than other normal difference schemes; (2) CCD and CSCD can use the coarse grid and larger time step to calculate, with less memory and high computational efficiency; (3) finally, the result of the shear-wave reverse-time migration of the 2D synthetic data model show that the reverse-time migration imaging is clear, and the proposed method for shear-wave reverse-time migration is practical and effective.

Seismic migration

Time derivative

10.3390/app12147047

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Citations (2)

Another AVO Cross‐plotting for P‐SV Wave

Pengyuan Sun Jianguo Sun LU Xiu-li

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2003Another AVO Cross‐plotting for P‐SV WaveAuthors: Pengyuan SunJianguo SunXiuli LuPengyuan SunCollege of Geo‐exploration science and technology, Jilin University. Changchun, China, Jianguo SunCollege of Geo‐exploration science and technology, Jilin University. Changchun, China, and Xiuli LuCollege of Geo‐exploration science and technology, Jilin University. Changchun, Chinahttps://doi.org/10.1190/1.1817879 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1817879FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2003ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2003 Pages: 2452 publication data© 2003 Copyright © 2003 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 03 Jan 2005 CITATION INFORMATION Pengyuan Sun, Jianguo Sun, and Xiuli Lu, (2003), "Another AVO Cross‐plotting for P‐SV Wave," SEG Technical Program Expanded Abstracts : 242-245. https://doi.org/10.1190/1.1817879 Plain-Language Summary PDF DownloadLoading ...

10.1190/1.1817879

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An optimized parallelized SGFD modeling scheme for 3D seismic wave propagation

Computers & Geosciences (2019)

Ning Wang Hui Zhou Hanming Chen Yufeng Wang Jinwei Fang

Speedup

10.1016/j.cageo.2019.06.017

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A staggered-grid lowrank finite-difference method for elastic wave extrapolation

Annals of Geophysics (2020)

DU Qi-zhen Jing Ba Dong Han Pengyuan Sun Jianlei Zhang

Elastic wave extrapolation in the time domain is significant for an elastic wave equation-based processing. To improve the simulation reliability and accuracy of decoupled elastic P- and S- waves, we propose the staggered-grid lowrank finite-difference method based on the elastic wave decomposition. For elastic wave propagation, a lowrank finite-difference method based on the staggered grid is derived to improve the accuracy. Regarding the application of the decoupled elastic wave equation, we derive the finite-difference scheme coefficients which are dependent on velocity. Based on the elastic wave decomposition and plane wave theories, we formulate the elastic wave-extrapolation operators, which contain trigonometric adjustment factors. Accordingly, by applying the lowrank method to approximating the operators, the finite- difference scheme is designed to discretize the decoupled wave equation. The derivation processing implies the combination of elastic wave-mode decomposition and extrapolation. The proposed method enables elastic P- and S-waves to extrapolate in the time-space domain separately and produces accurate P-and S-wave components simultaneously. Dispersion analysis suggests that our proposed method is reliable and accurate in a wide range of wavenumber. Numerical simulation tests on a simple model and the Marmousi2 model validate the accuracy and effectiveness of the method, showing its ability in handling complex structures. Although the operators are accurate only when the medium is homogeneous, they are of high accuracy when the velocity gradient is quite small and are applicable when the velocity gradient is large. The subsequent results of reverse time migration for the Marmousi2 model also suggest that the proposed method is enough to serve as an extrapolator in elastic reverse time migration.

Finite difference

Wavenumber

10.4401/ag-8197

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The effects of elastic data on acoustic and elastic full waveform inversion

Journal of Applied Geophysics (2019)

Jinwei Fang Hui Zhou Qingchen Zhang Hanming Chen Pengyuan Sun

Acoustic wave equation

10.1016/j.jappgeo.2019.103876

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Citations (10)

Physicochemical and digestive properties of curcumin stabilized by quaternized chitosan/sodium alginate nanoemulsion coatings

Food Chemistry (2024)

Ying-ao Zhu Yi Deng Pengyuan Sun Yuhang Cao Baohua Kong

Sodium alginate

10.1016/j.foodchem.2024.141551

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Least-squares Gaussian beam migration in viscoacoustic media

Yubo Yue Pengyuan Sun Jianlei Zhang Shihu Wang Jun Liao

Anelastic attenuation causes energy dissipation of seismic waves propagating inside the earth, which leads to amplitude decay and phase distortion of migrated images. To correct for this dissipation effect, we use Gaussian beams as wavefield propagator to formulate an efficient and accurate linearized inversion scheme, denoted as least-squares Q Gaussian beam migration (LSQGBM), to iteratively solve for optimal images in viscoacoustic media. With this method, we can not only compensate for the amplitude loss and phase shift caused by attenuation loss during migration, but also produce images with better balanced amplitudes and higher resolution. Numerical tests on synthetic and field datasets demonstrate the validity and effectiveness of our proposed method. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 1:50 PM Presentation Start Time: 2:15 PM Location: Poster Station 10 Presentation Type: Poster

Seismic migration

Gaussian beam

10.1190/segam2019-3216617.1

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Citations (4)