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1.
Repeating airgun sources are eco-friendly sources for monitoring the changes in the physical properties of subsurface mediums, but their signals decay quickly and are buried in the noises soon after traveling short distances. Stacking waveforms from different airgun shots recorded by a single seismic station (shot stacking) is the most popular technique to detect weak signals from noisy backgrounds, and has been widely used to process the data of Fixed Airgun Signal Transmission Stations (FASTS) in China. However, shot stacking sacrifices the time resolution in monitoring to recover a qualified airgun signal by stacking many shots at distance stations, and also suffers from persistent local noises. In this paper, we carried out several small-aperture seismic array experiments around the Binchuan FAST Station (BCFASTS) in Yunnan Province,China, and applied the array technique to improve airgun signal detection. The results show that seismic array processing combining with shot stacking can suppress seismic noises more efficiently, and provide better signal-to-noise ratio (SNR) and coherent airgun signals with less airgun shots. This work suggests that the array technique is a feasible and promising tool in FAST to increase the time resolution and reduce noise interference on routine monitoring. 相似文献
2.
在深反射地震资料处理中,当来自深部的有效弱信号和噪声干扰频带差异较小且难以区分时,传统滤波方法的应用会受到限制.谱分解方法是一种使用离散傅里叶变换,基于信号的频率-振幅谱等信息生成高分辨率地震图像的方法,通常用来识别介质物性横向分布特征,处理复杂介质内频谱变化和局部相位的不稳定性等问题,包括定位复杂断层和小尺度断裂等.S变换作为一种新的时频分析方法,具有自动调节分辨率的能力,近些年来被广泛应用到勘探地震、大地电磁等数据处理中,逐渐成为地球物理方法中噪声压制的有效方法之一.与常规石油反射地震资料相比,深反射主动源地震为了探测深部结构信息,常采用大药量激发方式、长排列观测系统等,导致深部有效信号基本湮灭在噪声干扰之中.针对深反射数据特点,本文结合谱分解和S变换技术,首先设计了简单的脉冲函数实验数据,证实S变换方法的有效性,同时说明谱分解方法的效果受所用时频分析方法影响较大,而其中决定分辨能力的变换窗函数的选取尤为重要.在此基础上,分别应用到深反射地震资料的单道和叠加剖面实际数据上,对比分析了传统变换谱分解和S变换谱分解的应用效果,单道资料对比结果表明:相比传统谱分解,S变换谱分解方法具有自动调节分辨率的能力,能够精确的标定深反射地震资料中弱信号不同时刻的频率分量;叠加剖面资料应用结果表明:由S变换谱分解得到的剖面结果与其他谱分解方法结果整体上具有较高的一致性,同时清晰地刻画出原叠加剖面上被噪声湮灭的低频细节特征,提高了剖面的分辨率及同相轴连续性;对比结果明显看出,Gabor变换谱分解方法得到的结果同相轴较为破碎,分析原因认为这是由Gabor变换的时频分解方法的定长窗函数所致,窗口大小不会随着信号频率的变化来调节长度,只能在处理的过程中根据一定的记录长度范围选取窗函数参数,而S变换谱分解方法在窗函数的选取时,通过时变信号的局部频率特征自动调节窗口长度,能够更好的刻画各个频段的细节特征,在深反射剖面成像应用中效果尤为明显.本文结果表明S变换谱分解技术在深地震叠加剖面上的应用有效地提高了来自深部弱反射信号的信噪比和分辨率,并刻画出了叠加剖面上所不具有的低频细节特征,在实际深反射地震资料处理中能有效保护低频弱信号获得更好的成像效果.本文为深地震反射资料中弱信号的保护处理找到一种有效的方法. 相似文献
3.
In this case study we consider the seismic processing of a challenging land data set from the Arabian Peninsula. It suffers from rough top‐surface topography, a strongly varying weathering layer, and complex near‐surface geology. We aim at establishing a new seismic imaging workflow, well‐suited to these specific problems of land data processing. This workflow is based on the common‐reflection‐surface stack for topography, a generalized high‐density velocity analysis and stacking process. It is applied in a non‐interactive manner and provides an entire set of physically interpretable stacking parameters that include and complement the conventional stacking velocity. The implementation introduced combines two different approaches to topography handling to minimize the computational effort: after initial values of the stacking parameters are determined for a smoothly curved floating datum using conventional elevation statics, the final stack and also the related residual static correction are applied to the original prestack data, considering the true source and receiver elevations without the assumption of nearly vertical rays. Finally, we extrapolate all results to a chosen planar reference level using the stacking parameters. This redatuming procedure removes the influence of the rough measurement surface and provides standardized input for interpretation, tomographic velocity model determination, and post‐stack depth migration. The methodology of the residual static correction employed and the details of its application to this data example are discussed in a separate paper in this issue. In view of the complex near‐surface conditions, the imaging workflow that is conducted, i.e. stack – residual static correction – redatuming – tomographic inversion – prestack and post‐stack depth migration, leads to a significant improvement in resolution, signal‐to‐noise ratio and reflector continuity. 相似文献
4.
A novel technique for automatic seismic data processing using both integral and local feature of seismograms 
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下载免费PDF全文 Ping Jin Chengliu Zhang Xufeng Shen Hongchun Wang Changzhou Pan Na Lu Xiong Xu 《地震科学（英文版）》2014,27(3):337-349
A novel technique for automatic seismic data processing using both integral and local feature of seismograms was presented in this paper. Here, the term integral feature of seismograms refers to feature which may depict the shape of the whole seismograms. However, unlike some previous efforts which completely abandon the DIAL approach, i.e., signal detection, phase identification, association, and event localization, and seek to use envelope cross-correlation to detect seismic events directly, our technique keeps following the DIAL approach, but in addition to detect signals corresponding to individual seismic phases, it also detects continuous wave-trains and explores their feature for phase-type identification and signal association. More concrete ideas about how to define wave-trains and combine them with various detections, as well as how to measure and utilize their feature in the seismic data processing were expatiated in the paper. This approach has been applied to the routine data processing by us for years, and test results for a 16 days’ period using data from the Xinjiang seismic station network were presented. The automatic processing results have fairly low false and missed event rate simultaneously, showing that the new technique has good application prospects for improvement of the automatic seismic data processing. 相似文献
5.
In this paper, we discuss high‐resolution coherence functions for the estimation of the stacking parameters in seismic signal processing. We focus on the Multiple Signal Classification which uses the eigendecomposition of the seismic data to measure the coherence along stacking curves. This algorithm can outperform the traditional semblance in cases of close or interfering reflections, generating a sharper velocity spectrum. Our main contribution is to propose complexity‐reducing strategies for its implementation to make it a feasible alternative to semblance. First, we show how to compute the multiple signal classification spectrum based on the eigendecomposition of the temporal correlation matrix of the seismic data. This matrix has a lower order than the spatial correlation used by other methods, so computing its eigendecomposition is simpler. Then we show how to compute its coherence measure in terms of the signal subspace of seismic data. This further reduces the computational cost as we now have to compute fewer eigenvectors than those required by the noise subspace currently used in the literature. Furthermore, we show how these eigenvectors can be computed with the low‐complexity power method. As a result of these simplifications, we show that the complexity of computing the multiple signal classification velocity spectrum is only about three times greater than semblance. Also, we propose a new normalization function to deal with the high dynamic range of the velocity spectrum. Numerical examples with synthetic and real seismic data indicate that the proposed approach provides stacking parameters with better resolution than conventional semblance, at an affordable computational cost. 相似文献
6.
Roberto de Franco 《Geophysical Prospecting》2011,59(3):432-454
This paper presents a signal processing procedure to perform refractor velocity analysis. The procedure enables one to obtain the seismic velocity from the refracted wavefield without the picking of refracted arrival times. Two processing procedures are derived, one starting from a seismic interferometric approach and another, from the conventional reciprocal method and generalized reciprocal method approaches. The theoretical equivalence of the two approaches is also demonstrated. The proposed processing procedure is applied to synthetic data in order to test the influence of some procedural parameters and its capability to reconstruct a known velocity model starting from refracted signals, without and with perturbations, in arrival times and noise; finally, it is applied to a field data set. 相似文献
7.
宽频带地震观测数据中有效信号和干扰噪声经常发生混频效应,常规的频率域滤波方法很难将二者分离.地震波信号属于时变非平稳信号,时频分析方法能够同时得到地震波信号随着时间和频率变化的振幅和相位特征,S变换是其中较为高效的时频分析工具之一.本文以S变换为例,提出了基于相位叠加的时频域相位滤波方法.与传统叠加方法相比,相位叠加方法对强振幅不敏感,对波形一致性相当敏感,更加利于有效弱信号信息的检测.时频域相位滤波方法滤除与有效信号不相干的背景噪声,保留了相位一致的有效信号成分,显著提高了信噪比.运用理论合成的远震接收函数数据和实际的宽频带地震观测数据检验结果显示该方法较传统的带通滤波方法相比,即使在信噪较低且混频严重条件下,时频域相位滤波方法的滤波效果依然很明显,有助于识别能量较弱的有效信号. 相似文献
8.
Dynamic characteristics of structures — viz. natural frequencies, damping ratios, and mode shapes — are central to earthquake‐resistant design. These values identified from field measurements are useful for model validation and health‐monitoring. Most system identification methods require input excitations motions to be measured and the structural response; however, the true input motions are seldom recordable. For example, when soil–structure interaction effects are non‐negligible, neither the free‐field motions nor the recorded responses of the foundations may be assumed as ‘input’. Even in the absence of soil–structure interaction, in many instances, the foundation responses are not recorded (or are recorded with a low signal‐to‐noise ratio). Unfortunately, existing output‐only methods are limited to free vibration data, or weak stationary ambient excitations. However, it is well‐known that the dynamic characteristics of most civil structures are amplitude‐dependent; thus, parameters identified from low‐amplitude responses do not match well with those from strong excitations, which arguably are more pertinent to seismic design. In this study, we present a new identification method through which a structure's dynamic characteristics can be extracted using only seismic response (output) signals. In this method, first, the response signals’ spatial time‐frequency distributions are used for blindly identifying the classical mode shapes and the modal coordinate signals. Second, cross‐relations among the modal coordinates are employed to determine the system's natural frequencies and damping ratios on the premise of linear behavior for the system. We use simulated (but realistic) data to verify the method, and also apply it to a real‐life data set to demonstrate its utility. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
9.
基于小波分析的去噪方法在地震资料叠前处理中得到了广泛应用.本文主要介绍利用小波变换的分频特性来压制相干噪声.通过小波分频技术将叠前地震信号分解为不同频带,然后利用有效波和相干干扰波的频谱差异来区分有效信号和噪声,最后利用加权方法去掉不需要的噪声信息来达到去除相干噪声的目的.实际资料的处理结果表明：基于小波分频方法能很好地压制相干噪声,从而提高地震资料信噪比和分辨率. 相似文献
10.
提出一种基于信号整体与局部特征的地震数据自动处理新方法, 该方法不同于以往仅采用包络线互相关来直接检测事件. 新方法依然按照检测、 识别、 关联和定位等4个步骤进行处理, 但在进行单个震相信号检测的同时, 也检测信号波列并利用其包络线特征来识别和关联震相. 文中详细阐述了数据处理过程中如何定义一个波列及抽取和应用其特征. 相关的数据处理技术目前已成功应用于区域台网的日常数据处理分析中. 作为例子, 给出了对新疆区域台网连续16天数据进行测试处理的结果. 实际应用结果表明, 这种新方法可以大幅度降低自动处理结果的误检、 漏检率, 在实际应用中具有很好的前景. 相似文献
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在地震勘探资料处理中,子波的零相位化有助于提高地震资料的分辨率、改善叠加剖面的质量.常规的相位校正方法是利用测井合成记录对井旁地震记录进行相位估计,然后对整条剖面进行常相位校正,该方法没有考虑地震子波相位的非稳态性（相位随时间和空间变化）.虽然通过局部相似度方法利用最大方差模准则或包络最大相似度准则可以估计出随时间和空间变化的相位属性,但是由于零相位判别准则本身具有一定的局限性,因此精度有限.针对这一问题,本文在局部地震属性和局部平面波模型下,提出了一种井约束的非稳态相位校正方法,该方法不仅考虑了子波相位的非稳态性,而且充分利用了测井合成地震记录进行相位校正精度高的优点.理论模型和实际资料处理表明,本文方法可以有效实现信号的零相位化,有利于改善叠加效果,提高资料的分辨率. 相似文献
13.
PRINCIPAL COMPONENT ANALYSIS AND LOCAL CORRELA-TION TRACKING AS TOOLS FOR REVEALING AND ANALYZING SEISMO-ELECTROMAGNETIC SIGNAL OF EARTHQAUKE 下载免费PDF全文
下载免费PDF全文 This study provides new seismo-electromagnetic data processing methods to extract the anomalous signals by combining the principal component analysis(PCA)and local correlation tracking(LCT)methods. The PCA method can separate signals of different frequencies by projecting them to different axes according to their energy. So it can solve the problems of identifying the relatively weak signals in strong interference background to a certain extent. The LCT method is more suitable for non-stationary signal processing compared with classical cross-correlation method. This method is based on the good spatial correlation between the magnetic field components of different ELF stations to pick up the correlation coefficient, so as to achieve the purpose of weak anomalies signals identification. As a case study of the M4.6 Jinggu earthquake in Yunnan, China, we investigated the electromagnetic data observed by ELF stations near the epicenter. First, we applied the PCA method to the magnetic-filed data and got the temporal variation of percentage of each principal component. The results indicate that the contribution of the second principal components, which may relate with the earthquake, increased significantly about a week before the earthquake. Then, we applied the LCT method to the magnetic-filed data processing as well, and the results of both north-south and east-west magnetic field components showed that local correlation coefficient saw anomalies about a week before the earthquake, which had a good corresponding relationship with the former results by PCA method. Both means for the same earthquake case got a consistent conclusion, which not only enhanced the reliability of the results, but also confirmed the effectiveness of two methods applied in the earthquake-related electromagnetic anomalies extraction. We also discussed the possible relationship between these anomalies and the earthquake. Although there are no direct evidence and supporting theories in terms of the relationship between abnormal electromagnetic signals and earthquakes at present, the studies in this paper may strengthen the understanding of seismoelectromagnetic phenomena and promote further research. 相似文献
14.
Weak Seismic Signal Extraction Based on the Curvelet Transform 总被引：1，自引：1，他引：0
Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved. 相似文献
15.
由于金属矿区地震记录中随机噪声性质复杂且信噪比低,常规降噪方法难以达到预期的滤波效果.时频峰值滤波(TFPF)方法是实现低信噪比地震勘探记录中随机噪声压制的有效方法,但其在复杂地震勘探随机噪声下时窗参数优化问题仍难以解决.本文充分利用地震勘探噪声的统计特性,结合Shapiro-Wilk(SW)统计量辨识地震勘探记录中的微弱有效信号,提出基于SW统计量的自适应时频峰值滤波降噪方法(S-TFPF).在S-TFPF方案中,对于有效信号集中区,S-TFPF方法根据信号频率特征,选择有利于信号保持的较短时窗长度;对于噪声集中区,按噪声方差自适应增加时窗长度,增强随机噪声压制能力.S-TFPF应用于合成记录和共炮点记录的滤波结果表明,与传统时频峰值滤波方法相比,S-TFPF方法可以有效抑制低信噪比地震勘探记录中的随机噪声,更好地恢复出同相轴. 相似文献
16.
This paper reviews the fundamentals of Radon-based methods using examples from global seismic applications. By exploiting the move-out or curvature of signal of interest, Least-squares and High-resolution Radon transform methods can effectively eliminate random or correlated noise, enhance signal clarity, and simultaneously constrain travel time and ray angles. The inverse formulation of the Radon transform has the added benefits of phase isolation and spatial interpolation during data reconstruction. This study presents a ‘cookbook’ for Radon-based methods in analyzing shear wave bottom-side reflections from mantle interfaces, also know as SS precursors. We demonstrate that accurate and flexible joint Radon- and frequency-domain approaches are particularly effective in resolving the presence and depth of known and postulated mantle reflectors. 相似文献
17.
强随机噪声干扰是导致地震勘探资料低信噪比的主要原因,如何在强随机噪声干扰下获取有效的信息是值得关注的问题.Duffing振子混沌系统是一个非线性的动力学系统,其对强随机噪声具有免疫能力,而对特定的周期性信号具有敏感性.本文提出一种基于Duffing振子混沌系统的速度分析方法.对CMP道集按照时距曲线关系进行移动窗口截取,将所截取的信号构建为待测信号加入Duffing振子混沌系统,通过相图网格分割方法(GPM)判断系统状态的改变,从而在强随机噪声背景下获得高分辨率的速度谱.理论模型和实际资料的处理结果表明,与传统的水平叠加速度分析方法相比,本方法能够在强随机噪声背景下获得更准确的速度分析结果. 相似文献
18.
随着油气勘探观测环境愈发复杂,采集的地震数据常常掺杂各种噪声信号,导致勘探目标引起的有效微弱信号被覆盖,严重影响高精度的地震勘探数据解译,因而有效的压制地震勘探数据噪声显得越发重要。本文采用字典学习策略,将复杂地震数据进行分块,通过分块数据的字典学习获取字典原子,构建高精度的字典学习地震数据稀疏表示,通过两次迭代更新字典原子,进行数据去噪。将本文的字典学习算法应用于含随机噪声的模拟数据和实测地震勘探数据处理,验证该算法的可行性及有效性。结果表明,本文算法有效去除了随机噪声,保留了有效信号同相轴,提高了信噪比,可为复杂含噪地震数据的去噪处理提供新的技术手段。 相似文献
19.
Jing Liu Youcai Tang Kai Tao Chunquan Yu Jie Chen Jieyuan Ning Yongshun John Chen Yongge Feng 《地震科学（英文版）》2010,23(6):627-636
We have developed a new stacking technique in ambient noise tomography to obtain high-quality dispersion curves of Rayleigh waves.This technique is used to stack the vertical components of the Estimated Green Functions(EGFs) obtained respectively from cross correlation of the ambient noise data recorded by a remote seismic station and one of the short distance seismic stations of a seismic array.It is based on a phase-matched filter and is implemented by a four-step iterative process:signal compression,stacking,signal extraction and signal decompression.The iterative process ends and gives the dispersion curve of Rayleigh wave when the predicted one and the processing result converge.We have tested the method using the vertical components of synthetic Rayleigh wave records.Results show that this new stacking method is stable and it can improve the quality of dispersion curves.In addition,we have applied this method to real data.We see that the results given by our new technique are obviously better than the ones employing the traditional method which is a three-step process:signal compression,signal extraction and signal decompression.In conclusion,the new method proposed in this paper can improve the signal to noise ratio of EGFs,and can therefore potentially improve the resolution of ambient noise tomography. 相似文献
20.
In regions where active source seismic exploration is constrained by limitations of energy penetration and recovery, cost and logistical concerns, or regulatory restrictions, analysis of natural source seismic data may provide an alternative. In this study, we investigate the feasibility of using locally‐generated seismic noise in the 2–6 Hz band to obtain a subsurface model via interferometric analysis. We apply this technique to three‐component data recorded during the La Barge Passive Seismic Experiment, a local deployment in south‐western Wyoming that recorded continuous seismic data between November 2008 and June 2009. We find traffic noise from a nearby state road to be the dominant source of surface waves recorded on the array and observe surface wave arrivals associated with this source up to distances of 5 kms. The orientation of the road with respect to the deployment ensures a large number of stationary points, leading to clear observations on both in‐line and cross‐line virtual source‐receiver pairs. This results in a large number of usable interferograms, which in turn enables the application of standard active source processing methods like signal processing, common offset stacking and traveltime inversion. We investigate the dependency of the interferograms on the amount of data, on a range of processing parameters and on the choice of the interferometry algorithm. The obtained interferograms exhibit a high signal‐to‐noise ratio on all three components. Rotation of the horizontal components to the radial/transverse direction facilitates the separation of Rayleigh and Love waves. Though the narrow frequency spectrum of the surface waves prevents the inversion for depth‐dependent shear‐wave velocities, we are able to map the arrival times of the surface waves to laterally varying group and phase velocities for both Rayleigh and Love waves. Our results correlate well with the known geological structure. We outline a scheme for obtaining localized surface wave velocities from local noise sources and show how the processing of passive data benefits from a combination with well‐established exploration seismology methods. We highlight the differences with interferometry applied to crustal scale data and conclude with recommendations for similar deployments. 相似文献