GEOPHYSICS最新文献_第10页

Fractional-order velocity-dilatation-rotation viscoelastic wave equation and numerical solution based on constant-Q model 分数阶速度-扩张-旋转粘弹性波方程及基于常数 Q 模型的数值解法

GEOPHYSICS Pub Date : 2024-01-22 DOI: 10.1190/geo2023-0290.1

Guanghui Han, Bing-Shout He, Huixing Zhang, Enjiang Wang

{"title":"Fractional-order velocity-dilatation-rotation viscoelastic wave equation and numerical solution based on constant-Q model","authors":"Guanghui Han, Bing-Shout He, Huixing Zhang, Enjiang Wang","doi":"10.1190/geo2023-0290.1","DOIUrl":"https://doi.org/10.1190/geo2023-0290.1","url":null,"abstract":"The viscoelastic wave equations based on the constant- Q (CQ) model can accurately describe the amplitude dissipation and phase distortion of waves in anelastic medium. However, only three velocity or displacement components can be obtained directly by solving such equations. Starting from the time-domain second-order displacement viscoelastic wave equation, we derived the decoupled P- and S-wave displacement vector viscoelastic wave equation by using the polarization difference of P- and S- waves propagation in isotropic media. The equation can be transformed into the velocity-dilatation-rotation viscoelastic wave equation containing the first-order temporal derivative and fractional Laplacian operators which can be solved directly by using the staggered-grid finite-difference and pseudo-spectral methods. We use the low-rank decomposition method to approximate the derived mixed space-wavenumber domain fractional Laplacian operators for modeling wave propagation in heterogeneous attenuating medium. We also demonstrated the precision of the proposed equation by comparing the numerical solutions with the analytical solutions. Furthermore, compared with the conventional velocity-stress viscoelastic wave equation, experimental results demonstrate that the proposed equation can separate the pure P- and S-waves from the mixed wavefield during wavefield continuation, but also be decoupled to the equation containing predominantly amplitude attenuation or phase distortion term.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139608997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

APrU dictionary learning with NSAM sparse coding for audio magnetotelluric denoising 利用 NSAM 稀疏编码进行 APrU 字典学习，实现音频磁性去噪

GEOPHYSICS Pub Date : 2024-01-19 DOI: 10.1190/geo2023-0205.1

Jin Li, Yucheng Luo, Guang Li, Yecheng Liu, Jingtian Tang

{"title":"APrU dictionary learning with NSAM sparse coding for audio magnetotelluric denoising","authors":"Jin Li, Yucheng Luo, Guang Li, Yecheng Liu, Jingtian Tang","doi":"10.1190/geo2023-0205.1","DOIUrl":"https://doi.org/10.1190/geo2023-0205.1","url":null,"abstract":"Audio magnetotelluric (AMT), as a commonly used passive geophysical technique, provides outstanding metal ore exploration capabilities based on the resistivity structure of the Earth. However, the accuracy of AMT in translating geoelectrical structures decreases when the data collected in mining areas are of poor data 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 propose a new denoising method that combines atom-profile updating dictionary learning (APrU) with nucleus sampling attention mechanism sparse coding (NSAM). First, we use APrU to accurately learn the characteristics of the noise in the AMT data; then, we apply the updated dictionary to perform sparse coding on the AMT data by NSAM to obtain the noise; finally, we subtract the noise from the original AMT data to obtain the denoised data. Our experimental results suggest that the proposed method can learn an over-complete dictionary via the to-be-processed AMT data, thereby enabling the sparse representation of the noise within the learned dictionary. We also demonstrate the efficacy of this method with a set of field data collected from the Lu-zong mining area, and the attained denoised data faithfully restores the geoelectrical structures with heightened accuracy. The findings confirm that the proposed method realizes the unsupervised learning of the AMT data and allows us to achieve precise denoising performance.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ℓ1–2-norm regularized basis pursuit seismic inversion based on exact Zoeppritz equation 基于精确佐伊普里兹方程的ℓ1-2 正则化基础追求地震反演

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2022-0336.1

Guangtan Huang, Shuying Wei, Davide Gei, Tongtao Wang

{"title":"ℓ1–2-norm regularized basis pursuit seismic inversion based on exact Zoeppritz equation","authors":"Guangtan Huang, Shuying Wei, Davide Gei, Tongtao Wang","doi":"10.1190/geo2022-0336.1","DOIUrl":"https://doi.org/10.1190/geo2022-0336.1","url":null,"abstract":"Sparsity constraints have been widely adopted in the regularization of ill-posed problems to obtain subsurface properties with sparseness feature. However, the target parameters are generally not sparsely distributed, and sparsity constraints lead to results that are missing information. Besides, smooth constraints (e.g., ℓ2 norm) lead to insufficient resolution of the inversion results. To overcome this issue, an effective solution is to convert the target parameters to a sparse representation, which can then be solved with sparsity constraints. For the estimation of elastic parameters, a high-resolution and reliable seismic basis pursuit inversion is proposed based on the exact Zoeppritz equation. Furthermore, the ℓ1–2 norm is proposed as a constraint, where a regularized function is minimized with the alternating direction method of multipliers (ADMM) algorithm. Numerical examples and real data applications demonstrate that the proposed method can not only improve the accuracy of the inversion results, especially the S-wave velocity and density information, but also increase the resolution of the inversion results. Furthermore, the ℓ1–2-norm constraint has better noise suppression demonstrating great potential in practical applications.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Target-oriented acquisition geometry design based on Full-Wavefield Migration 基于全波场迁移的目标导向采集几何设计

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0578.1

B. Revelo‐Obando, G. Blacquière

{"title":"Target-oriented acquisition geometry design based on Full-Wavefield Migration","authors":"B. Revelo‐Obando, G. Blacquière","doi":"10.1190/geo2023-0578.1","DOIUrl":"https://doi.org/10.1190/geo2023-0578.1","url":null,"abstract":"The ultimate goal of survey design is to find the acquisition parameters that enable acquiring high-quality data suitable for optimal imaging. This, while fulfilling budget, health, safety and environmental constraints. We propose a target-oriented acquisition design algorithm based on Full-Wavefield Migration. The algorithm optimizes a receiver density function that indicates the number of receivers per unit area required for obtaining the best possible image quality. The method makes use of available seismic data to create a reference model which is included in the proposed objective function. To make the design target-oriented, the objective function is multiplied with a mask that gives more weight to the target areas of interest. The results of the 2D and 3D implementations show an optimized receiver density function with higher values at the zones where more data is needed for improving image quality. The corresponding receiver geometries have more receivers placed at these areas. We validate the results by computing the images of the target zone using uniform and optimized geometries. The use of the latter shows an improvement in the image quality at the target zone. Additionally, we compute the number of receivers required for achieving a certain signal-to-noise ratio after imaging based on the optimized receiver density function.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139615782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gradient-based surface NMR for groundwater investigation 基于梯度的表面核磁共振用于地下水调查

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0311.1

Darya Morozov, Cristina McLaughlin, Elliot D. Grunewald, Trevor Irons, David O. Walsh

{"title":"Gradient-based surface NMR for groundwater investigation","authors":"Darya Morozov, Cristina McLaughlin, Elliot D. Grunewald, Trevor Irons, David O. Walsh","doi":"10.1190/geo2023-0311.1","DOIUrl":"https://doi.org/10.1190/geo2023-0311.1","url":null,"abstract":"In medical MRI, spatial localization (imaging) is based upon the application of controlled magnetic field gradients on top of the main magnetic field, to spatially modulate the frequency and/or phase of the NMR across the volume of investigation. In this work, we have applied similar physical principles to produce controlled magnetic field gradients during surface NMR-based groundwater investigations. In this approach a gradient pulse of variable amplitude or duration is applied immediately after the excitation pulse, to cause predictable phase encoding of the NMR signal as a function of depth. This approach is also applicable to emerging surface NMR detection methods that use a pre-polarization field with fast non-adiabatic turn off to generate detectable NMR signals from the shallow subsurface. In this case, the gradient pulse is applied after terminating the pre-polarization field and provides a heretofore unavailable means of localizing the NMR response as a function of depth. The application of gradients can also be combined with tip-angle based modulation to yield higher imaging resolution than can be achieved through either gradient- or tip-angle based imaging alone. We implemented this new gradient-based capability into a surface NMR gradient generation accessory that is compatible with the GMR-Flex instrument and developed surface NMR-specific forward modeling and linear inverse models. We validated the accuracy of this novel gradient-based sNMR technology using computer simulations, experiments using a small pool filled with a discrete layer of bulk water, and field experiments at well-characterized groundwater test sites along Ebey Island, WA, and Larned, KS. The gradient-based sNMR imaging observations were compared with high resolution direct push NMR results observed at these sites. The results of computer simulations and field experiments indicate improvements in both detection (signal-to-noise ratio) and spatial resolution of shallow surface water content using surface NMR, compared to traditional surface NMR imaging methods.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient SNR enhancement model for severely contaminated DAS seismic data based on heterogeneous knowledge distillation 基于异构知识提炼的严重污染 DAS 地震数据信噪比高效增强模型

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0382.1

Q. Feng, Shignag Wang, Yue Li

{"title":"Efficient SNR enhancement model for severely contaminated DAS seismic data based on heterogeneous knowledge distillation","authors":"Q. Feng, Shignag Wang, Yue Li","doi":"10.1190/geo2023-0382.1","DOIUrl":"https://doi.org/10.1190/geo2023-0382.1","url":null,"abstract":"Distributed acoustic sensing (DAS) is an emerging seismic acquisition technique with great practical potential. However, various types of noise seriously corrupt DAS signals, making it difficult to recover signals, particularly in low SNR regions. Existing deep learning methods address this challenge by augmenting datasets or strengthening the complex architecture, which can cause over-denoising and a computational power burden. Hence, we propose the heterogeneous knowledge distillation (HKD) method to more efficiently address the signal reconstruction under low SNR. HKD employs ResNet 20 as the teacher and student model (T-S). It utilizes residual learning and skip connections to facilitate feature representation at deeper levels. The main contribution is the training of the T-S framework with different noise levels. The teacher model that was trained using slightly noisy data serves as a powerful feature extractor to capture more accurate signal features, since high quality data is easy to recover. By minimizing the difference between the outputs of T-S models, the student that was trained using severely noisy data can distill the absent signal features from the teacher to improve its own signal recovery, which enables heterogeneous feature distillation. Furthermore, simultaneous learning of negative and positive components (PNL) has been proposed to extract more useful features from the teacher, enabling the T-S framework to learn from both the predicted signal and noise during training. Consequently, a new loss function that combines student denoising loss and HKD loss weighted by PNL was developed to alleviate signal leakage. The experimental results demonstrate that the HKD achieves distinct and consistent signal recovery without increasing computational costs.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139614234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PREDICTING MISSING SONIC LOGS WITH SEISMIC CONSTRAINT 利用地震约束预测丢失的声波测井记录

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0286.1

Nam Pham, Lei Fu, Weichang Li

引用次数: 0

MAU-Net:a multi-branch attention U-Net for full-wavefom inversion MAU-Net：用于全波反演的多分支注意 U-Net

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0043.1

Hanyang Li, Jiahui Li, Xuegui Li, Hongli Dong, Gang Xu, Mi Zhang

{"title":"MAU-Net:a multi-branch attention U-Net for full-wavefom inversion","authors":"Hanyang Li, Jiahui Li, Xuegui Li, Hongli Dong, Gang Xu, Mi Zhang","doi":"10.1190/geo2023-0043.1","DOIUrl":"https://doi.org/10.1190/geo2023-0043.1","url":null,"abstract":"Data-driven velocity inversion has emerged as a prominent and challenging problem in seismic exploration. The complexity of the inversion problem and the limited data set make it difficult to ensure the stability and generalization of neural networks. To address these concerns, we propose a novel approach called multi-branch attention U-Net (MAU-Net) for velocity inversion. The key distinction of MAU-Net from previous data-driven approaches lies in its ability to not only learn information from the data domain, but also incorporate prior model domain information. MAU-Net consists of two branches: one branch uses seismic records as input to effectively learn the mapping relationship between the data and model domains, while the other branch employs a prior geological model as input to extract features from the model domain, thereby guiding MAU-Net’s learning process. Additionally, we introduce three major improvements in the model branching path to enhance MAU-Net’s utilization of seismic data and handle redundant information. We validate the effectiveness of each improvement through ablation experiments. The performance of MAU-Net is demonstrated with the Marmousi model and 2004 BP model, and it can also be combined with FWI to further improve the quality of the inversion result. MAU-Net exhibits robust performance on field data through the use of transfer learning techniques, further confirming its reliability and applicability.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Seismic amplitude inversion based on a new PP-wave reflection coefficient approximation equation for VTI media 基于新的 VTI 介质 PP 波反射系数近似方程的地震振幅反演

GEOPHYSICS Pub Date : 2024-01-18 DOI: 10.1190/geo2023-0132.1

Xin Fu

{"title":"Seismic amplitude inversion based on a new PP-wave reflection coefficient approximation equation for VTI media","authors":"Xin Fu","doi":"10.1190/geo2023-0132.1","DOIUrl":"https://doi.org/10.1190/geo2023-0132.1","url":null,"abstract":"The research in this paper is to realize the simultaneous AVO/AVA (amplitude variation with offset or angle) inversion of anisotropic parameters for the transversely isotropic media with vertical axis of symmetry (VTI media). First, we introduce a nonlinear PP-wave reflection coefficient approximation equation in terms of only P- and S-wave impedances for isotropic elastic media. Then by replacing the isotropic part of Rüger’s equation with this equation, we obtain a new PP-wave reflection coefficient approximation equation called the ASI Rüger equation for VTI media. To invert parameters for VTI media based on the ASI Rüger equation, we adopt the Bayesian generalized linear inversion method, a combination of generalized linear inversion and Bayesian linear inversion, in which the noise and model perturbation are assumed to conform to the zero mean Gaussian distribution. Compared with Rüger’s equation, the ASI Rüger equation lowers the trade-off between the parameters, and reduces the ill-posedness of the inverse problem. The synthetic and field data tests demonstrate the feasibility of the proposed method for inverting VTI media parameters (the vertical P-wave impedance, the vertical S-wave impedance, Thomsen’s parameters δ and ϵ).","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust multi-dimensional reconstruction via Group Sparsity with Radon operators 通过组稀疏性与拉顿算子实现稳健的多维重建

GEOPHYSICS Pub Date : 2024-01-17 DOI: 10.1190/geo2023-0465.1

Ji Li, Dawei Liu

{"title":"Robust multi-dimensional reconstruction via Group Sparsity with Radon operators","authors":"Ji Li, Dawei Liu","doi":"10.1190/geo2023-0465.1","DOIUrl":"https://doi.org/10.1190/geo2023-0465.1","url":null,"abstract":"Seismic data processing, specifically tasks like denoising and interpolation, often hinges on sparse solutions of linear systems. Group sparsity plays an essential role in this context by enhancing sparse inversion. It introduces more refined constraints, which preserve the inherent relationships within seismic data. To this end, we propose a robust Orthogonal Matching Pursuit algorithm, combined with Radon operators in the frequency-slowness f- p domain, to tackle the strong group-sparsity problem. This approach is vital for interpolating seismic data and attenuating erratic noise simultaneously. Our algorithm takes advantage of group sparsity by selecting the dominant slowness group in each iteration and fitting Radon coefficients with a robust ℓ1-ℓ1 norm by the alternating direction method of multipliers (ADMM) solver. Its ability to resist erratic noise, along with its superior performance in applications such as simultaneous source deblending and reconstruction of noisy onshore datasets, underscores the importance of group sparsity. Both synthetic and real comparative analyses further demonstrate that strong group sparsity inversion consistently outperforms corresponding traditional methods without the group sparsity constraint. These comparisons emphasize the necessity of integrating group sparsity in these applications, thereby showing its indispensable role in optimizing seismic data processing.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139616195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0