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Complex Noise Suppression Using a Robust Dictionary Learning Approach

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2025年 22卷

作者： Feng, Zhenjie Anyang Inst Technol Sch Comp Sci & Informat Engn Anyang 455000 Peoples R China

seismic data comprise reflection signals and various types of noise, including random high-frequency ambient noise, high-amplitude noise, and low-frequency ground-roll noise. Noise removal while protecting useful signals has been the long-term research focus of seismic exploration and data processing. Seldom methods can be used to deal with all these types of noise simultaneously, which motivates the study of this research. Here, we propose a systematic and effective method to tackle various kinds of complex seismic noise in seismic data by designing a dictionary learning approach. To deal with random and high-amplitude noise, we propose a robust inversion framework to estimate the signals from noise-corrupted data iteratively. The inversion scheme is inspired by an L1 -norm regularized iterative denoising framework but performs conveniently in terms of the coherency-promoting denoising operator. Then, we propose a bandpass-limited signal retrieving scheme internally within the iterative framework to tackle the ground-roll suppression issue. The iterative robust dictionary learning approach is based on a singular-value decomposition (SVD)-free approach to improve the efficiency without sacrificing the denoising performance. Results from synthetic and real data examples show promising performance of the proposed method.

关键词： Noise Noise reduction Machine learning Dictionaries Vectors Iterative methods Geoscience and remote sensing Reflection Noise measurement Lubricating oils Dictionary learning ground-roll seismic data processing signal leakage

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Amplitude-Preserved processing of The Blackfoot 10 Hz seismic data

Amplitude-Preserved Processing of The Blackfoot 10 Hz Seismi...

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作者： Algarni, Bader Mohammed A. Missouri University of Science and Technology

学位级别：M.S.

The broadband 3C-2D seismic survey was acquired in the Blackfoot Field in southern Alberta. The single-component 10 Hz geophone data were reprocessed to increase vertical resolution and provide a better seismic image of the incised valley channel fill deposits in the Glauconitic Formation. The amplitude-preserved seismic processing of the data was followed by the Kirchhoff prestack time migration. The processing parameters and algorithms used were based on parameter optimization approach. Elevation statics and surface consistent residual statics were utilized to remove near surface delays in the data. seismic noise, such as ground roll and air blast, were attenuated effectively by various algorithms. Amplitude and phase distortions due to near surface conditions were corrected by processing of the surface consistent deconvolution and amplitude balancing. The Kirchhoff prestack time migration was applied to the data to obtain a migrated section that adequately characterizes the subsurface structure. The final stacked seismic section shows a better image of the incised valley of the Glauconitic Formation than the legacy seismic section. Log data from Well 14-09 were utilized to generate synthetic seismogram, establish seismic-to-well tying, and interpret key seismic horizons.

关键词： Amplitude-preserved processing Blackfoot field Migration seismic data processing seismic interpretation

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The application of a homemade boomer source in offshore seismic survey: From field data acquisition to post-processing

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JOURNAL OF APPLIED GEOPHYSICS 2023年 210卷

作者： Zheng, Jianglong Li, Linwei Xie, Jinxing Yan, Ting Jiang, Biao Huang, Xiaoxin Hui, Gege Li, Tianguang Wen, Mingming Huang, Yifan Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai Peoples R China China Geol Survey Guangzhou Marine Geol Survey Guangzhou Peoples R China

This work presents a case study about applying a homemade boomer source working with a well-designed field geometry in an offshore seismic survey. Some measurements were carried out to calibrate the boomer source acoustic characteristics in an anechoic tank. Then a catamaran, taking account of the boomer source signature, is designed to control the source depth and entirely use ghosts as part of the source wavelet. This way, the vertical resolution is sacrificed to signal-to-noise ratio (SNR), and the source wavelet meets the minimum phase char-acteristics. Furthermore, the detailed analytical results of the calibrated source wavelets also provide a reliable basis for determining post-processing parameters. Two surveys have been conducted on the same line using this source in combination with two different hydrophone streamers. Some valuable experiences in field data acquisition and post-processing are analyzed and summarized. The most important one is taking the ghost part of the source wavelet by controlling source depth. This work is a reliable reference to other research on improving the quality of seismic imaging of offshore shallow strata.

关键词： Boomer source Offshore seismic survey Single -channel seismic seismic data processing

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THE RESEARCHES ON processing TECHNIQUES OF OFFS HO RE M ULTICOMPO NENT seismic data

THE RESEARCHES ON PROCESSING TECHNIQUES OF OFFS HO RE M ULTI...

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中国科学院地质与地球物理研究所2003学术年会

作者： Fu Dandan~1 He Hanyi~2 Zhu Hongzhang~1 Shen Lili~1 Li Wenyi~1 Chen Baoshu~1 Han Qingshi~1 Zhu Shufen~1 (1.Exploration Institute of CNOOC Research Center,Hebei 2.Research Center of CNOOC,Beijing)

For the offshore petroleum exploration in China,it has long existed that the fuzzy zones and lithological false bright spots can't be eliminated by the P-wave seismic *** recent years,three massive multi-component seismic explorations of 2D and 3D have been conducted by CNOOC in offshore China,and a set of commercial processing system for offshore multicomponent seismic data(OMS) was *** two sets of 2D multicomponent seismic data acquired in South China Sea have been successfully processed with this system, indicating its mature processing techniques and good converted wave ***,a part of 3D converted -wave processing module has been added into the system by ourself developing,and a trial processing was made for a part of 3D offshore multicomponent seismic data acquired in Bohai *** present,there are still more difficulties and problems in processing 3D multicomponent seismic data,and the 3D converted-wave processing methods also need to be further *** these reasons,the next research direction of multicomponent seismic data processing techniques are proposed.

关键词： offshore multicomponent seismic 2D seismic exploration 3D seismic exploration seismic data processing P-wave converted wave processing technique

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Reverse Time Migration Method for Joint Imaging of Multiples and Primaries in Vertical seismic Profiling

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APPLIED SCIENCES-BASEL 2025年第5期15卷

作者： Lu, Cai Liu, Youming Gao, Jianbo Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Peoples R China

Vertical seismic profiling (VSP) has garnered widespread attention because of its ability to provide high-quality seismic data. Owing to the unique characteristics of VSP observation systems, conventional multiple-wave imaging methods designed for surface seismic data are often not suitable for VSP data. Additionally, the existing research lacks methods capable of simultaneously imaging surface and interbed multiples in asymmetric observation systems. Here, the reverse time migration (RTM) imaging problem of multiple VSP waves is addressed, and a joint RTM imaging method is proposed for primary and multiple waves. Without the need to predict or separate multiple waves, this method utilizes seismic signals containing primary and multiple waves to replace wavelet excitation at the source location. Primary waves, surface multiples, and interbed multiples are simultaneously imaged, addressing the limitations of traditional VSP imaging methods that can only image areas near observation wells. Numerical tests demonstrate that the proposed method provides a broader effective imaging range and higher image quality than traditional VSP RTM methods.

关键词： vertical seismic profiling reverse time migration seismic data processing multiple waves

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Unsupervised Deep Learning for DAS-VSP Denoising Using Attention-Based Deep Image Prior

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Cui, Yang Bin Waheed, Umair Chen, Yangkang King Fahd Univ Petr & Minerals Coll Petr Engn & Geosci Dhahran 31261 Saudi Arabia Univ Texas Austin John A & Katherine G Jackson Sch Geosci Bur Econ Geol Austin TX 78712 USA

Distributed acoustic sensing (DAS) has emerged as a widely used technology in various applications, including borehole microseismic monitoring, active source exploration, and ambient noise tomography. Compared with conventional geophones, the fiber optic cable has unique characteristics that allow it to withstand high-temperature and high-pressure environments. However, due to its high sensitivity, the obtained seismic records are often corrupted with unavoidable background noise, which introduces more uncertainty in the subsequent seismic data processing and interpretation. Thus, the development of robust denoising techniques for DAS data is crucial to minimize the impact of noise and enhance the reliability of seismic data processing and interpretation. In this work, we propose a ground-truth-free method for strong background noise suppression in DAS vertical seismic profiling (DAS-VSP) data. Compared to existing deep learning (DL) methods, the proposed approach demonstrates promising generalizability in handling field examples across different surveys. The proposed method consists of four stages: training set extension with a patching scheme, feature selection with a kurtosis-based method, denoising with a deep image prior (DIP)-based unsupervised neural network, and an unpatching approach for denoised data reconstruction. Numerical experiments conducted on synthetic data and several profiles from the Utah FORGE project and the Gro ss Sch & ouml;nebeck site demonstrate that the proposed method can effectively suppress most of the background noise while preserving hidden signals. Furthermore, the unsupervised learning (USL) approach is unconditionally generalizable when applied to vastly different field data because it does not require pre-labeled datasets for training. The codes related to this article are fully open-source via https://***/cuiyang512/Unsupervised-DAS-Denoising.

关键词： Noise Noise reduction Training Kurtosis Feature extraction Background noise Noise measurement Training data Optical fibers data processing Denoising distributed acoustic sensing (DAS) seismic data processing unsupervised learning (USL)

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Multiple seismic attribute analyses for determination of bottom simulating reflector of gas hydrate seismic data in the Ulleung Basin of Korea

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MARINE GEOPHYSICAL RESEARCH 2010年第1-2期31卷 121-132页

作者： Hien, Doan Huy Jang, Seonghyung Kim, Youngwan Univ Sci & Technol Petr Resources Technol Field Study Sch Engn Taejon 305350 South Korea Korea Inst Geosci & Mineral Resources KIGAM Petr & Marine Res Div Taejon 305350 South Korea

The bottom simulating reflector (BSR), the boundary between the gas hydrate and the free gas zone, is considered to be the most common evidence in seismic data analysis for gas hydrate exploration. Multiple seismic attribute analyses of reflectivity and acoustic impedance from the post-stack deconvolution and complex analysis of instantaneous attribute properties including the amplitude envelope, instantaneous frequency, phase, and first derivative of the amplitude of seismic data have been used to effectively confirm the existence of a BSR as the base of gas hydrate stability zone. In this paper, we consider individual seismic attribute analysis and integrate the results of those attributes to locate the position of the BSR. The outputs from conventional seismic data processing of the gas hydrate data set in the Ulleung Basin were used as inputs for multiple analyses. Applying multiple attribute analyses to the individual seismic traces showed that the identical anomalies found in two-way travel time (TWT) between 3.1 and 3.2 s from the results of complex analyses and l (1) norm deconvolution indicated the location of the BSR.

关键词： seismic data processing Gas hydrate BSR Complex analyses l(1) norm deconvolution

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Progressive denoising of seismic data via robust noise estimation in dual domains

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GEOPHYSICS 2020年第1期85卷 V99-V118页

作者： Lin, Yi Zhang, Jinhai Chinese Acad Sci Key Lab Earth & Planetary Phys Inst Geol & Geophys Beijing Peoples R China Chinese Acad Sci Innovat Acad Earth Sci Beijing Peoples R China Unvers Chinese Acad Sci Beijing Peoples R China

Random noise attenuation plays an important role in seismic data processing. Most traditional methods suppress random noise either in the time-space domain or in the transformed domain, which may encounter difficulty in retaining the detailed structures. We have introduced the progressive denoising method to suppress random noise in seismic data. This method estimates random noise at each sample independently by imposing proper constraints on local windowed data in the time-space domain and then in the transformed domain, and the denoised results of the whole data set are gradually improved by many iterations. First, we apply an unnormalized bilateral kernel in time-space domain to reject large-amplitude signals;then, we apply a range kernel in the frequency-wavenumber domain to reject medium-amplitude signals;finally, we can obtain a total estimate of random noise by repeating these steps approximately 30 times. Numerical examples indicate that the progressive denoising method can achieve a better denoising result, compared with the two typical single-domain methods: the f-x deconvolution method and the curvelet domain thresholding method. As an edge-preserving method, the progressive denoising method can greatly reduce the random noise without harming the useful signals, especially to those high-frequency components, which would be crucial for high-resolution imaging and interpretations in the following stages.

关键词： random noise attenuation robust noise estimation progressive denoising method dual domains seismic data processing

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seismic data interpolation using generalised velocity-dependent seislet transform

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GEOPHYSICAL PROSPECTING 2017年第S1期65卷 82-93页

作者： Liu, Yang Zhang, Peng Liu, Cai Jilin Univ Coll Geoexplorat Sci & Technol 938 Ximinzhu Ave Changchun 130026 Jilin Peoples R China

data interpolation is an important step for seismic data analysis because many processing tasks, such as multiple attenuation and migration, are based on regularly sampled seismic data. Failed interpolations may introduce artifacts and eventually lead to inaccurate final processing results. In this paper, we generalised seismic data interpolation as a basis pursuit problem and proposed an iteration framework for recovering missing data. The method is based on non-linear iteration and sparse transform. A modified Bregman iteration is used for solving the constrained minimisation problem based on compressed sensing. The new iterative strategy guarantees fast convergence by using a fixed threshold value. We also propose a generalised velocity-dependent formulation of the seislet transform as an effective sparse transform, in which the non-hyperbolic normal moveout equation serves as a bridge between local slope patterns and moveout parametres in the common-midpoint domain. It can also be reduced to the traditional velocity-dependent seislet if special heterogeneity parametre is selected. The generalised velocity-dependent seislet transform predicts prestack reflection data in offset coordinates, which provides a high compression of reflection events. The method was applied to synthetic and field data examples, and the results show that the generalised velocity-dependent seislet transform can reconstruct missing data with the help of the modified Bregman iteration even for non-hyperbolic reflections under complex conditions, such as vertical transverse isotropic (VTI) media or aliasing.

关键词： Interpolation Iterative scheme seismic data processing

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seismic data restoration based on the Grassmannian rank-one update subspace estimation method

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JOURNAL OF APPLIED GEOPHYSICS 2018年 159卷 731-741页

作者： Zhou, Yatong Han, Chunying Hebei Univ Technol Sch Elect & Informat Engn Xiping Rd 5340 Tianjin 300401 Peoples R China

Anew low-rank based framework has been proposed for simultaneous noise attenuation and data reconstruction, which uses an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The online subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analyzing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data is mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the proposed subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional singular value decomposition (SVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed reconstruction method can obtain better performance. More specifically, the proposed method outperforms the singular spectrum analysis (SSA) method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Reconstruction seismic data processing Noise Subspace tracking

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