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1.
运用Matlab工具软件,对地磁数字信号中的干扰分量进行FFT变换,滤除地电测值对地磁Z、D分量的干扰信号,清晰的反映出地磁变化的真实信息,从而提高对地磁数据的分析处理能力,对数据的异常识别、判定提高准确性,对资料的分析研究有一定实用价值。 相似文献
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基于频谱分解的碳酸盐岩储层识别 总被引：1，自引：0，他引：1
频谱分解技术是将地震信号从时间域转换到频率域,分析频率对不同尺度地质体的振幅、相位响应特征的一项技术.频谱分解能够得到高于传统分辨率的解释结果,提高刻画储层分布的能力.本文详述了短时傅里叶变换、连续小波变换和S变换的数学原理及适用性:短时傅里叶变换使用固定时窗,不能根据信号的变化调整分辨率,只适合分析分段平稳或近似平稳的信号;连续小波变换使用移动的、尺度可变的小波作为时窗,具有多分辨率特点,但是实际中选择能反映信号特征的小波函数不易;S变换使用频率的倒数来调节时窗,具有多分辨率特征,对数据处理的适应性较强.将这三种方法分别应用于碳酸盐岩储层发育区,利用靠近地震主频的35 Hz分频剖面,分析了不同时窗大小的短时傅里叶变换效果,不同类型小波的连续小波变换效果,并对比了不同频谱分解算法对储层的描述精度.通过分析得出分频剖面比常规地震剖面更有利于储层识别,且S变换效果最好. 相似文献
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谱图重排的谱分解理论及其在储层探测中的应用 总被引：1，自引：0，他引：1
谱分解理论是把单道地震记录分解为连续的时频谱平面,是地震资料处理和解释的重要技术之一.由于谱分解方法的多解性,所以同一道地震记录因为分解方法不同,得到的时频谱是不一样的.短时傅里叶变换,小波变换,S变换和匹配追踪算法都是对信号开窗分析,这些方法都受到不确定性原理的限制.Wigner-Ville变换避开了不确定性原理的限制,但是交叉项的存在限制了本方法的使用.本文利用谱图重排的时频分析方法(RSPWV)对合成的单道地震记录和实际的地震资料进行了分析.与短时傅里叶变换和匹配追踪算法的比较得出:此方法具有较高的时频分辨率,能够很好地识别气层. 相似文献
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云计算下采用三点阵次声源定位方法,在自动识别震前震源次声波过程中不能自动筛选识别大量的异常次声波数据,导致震前监测准确度不高且效率低下。因此提出一种云计算环境下震前震源异常次声波自动识别方法,构建JNS异常次声波数据采集筛查模组,全天候实时扫描访问端口,快速反馈异常次声波数据,采用NDS异常次声波数据序列异常检测算法快速识别错误序阵,准确回查、定位和锁定异常次声波数据;利用震前震源异常次声波自动识别方法分类识别异常次声波信号,判断该信号是否是地震可疑信号。实验结果表明,所提方法可有效自动识别震前震源异常次声波信号类型,信号分类准确率最大值达到99.99%;多次识别耗时最大均值仅为1.3min,具有准确率高和效率快的优势。 相似文献
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随着地磁场模型的日趋完善和滤波技术的不断成熟,地磁匹配方法在近几年得到迅速发展,它一般用于近地卫星,还未用于海洋环境.针对这一问题,本文结合地磁场特点和海洋地磁测量的现状,分析了水下地磁匹配的可行性.分别从匹配的地磁模型和测量值中存在干扰磁场两方面,指出了制约该技术发展的几个因素.在此基础上,提出了地磁用于水下载体定位的两条技术途径,一是用小波变换滤去地磁异常,与大尺度地磁模型匹配定位;另外,也提出了利用地磁异常,结合同时定位与构图(SLAM)算法实现自主导航. 相似文献
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为探明路基中隐藏病害的类型和空间位置,应用探地雷达方法对公路路基质量进行了无损检测.在地层介质强衰减和噪声干扰作用下,探地雷达信号存在信噪比低、深部复杂目标体难以识别的问题.针对探地雷达路基实测信号非线性和非平稳的特点,采用信号均衡和希尔伯特-黄变换相结合的方法,首先对数据进行均衡处理以突出深层弱信号,在此基础上对单道信号进行经验模态分解以获得固有模态函数,通过希尔伯特变换对固有模态函数的瞬态属性特征进行分析,进而将希尔伯特-黄变换应用于整个探地雷达的数据剖面,最后通过综合对比瞬时振幅剖面和瞬时相位剖面对探测结果进行了分析和解释.结果 表明,信号均衡可以有效缓解深部信号衰减问题,基于希尔伯特.黄变换可以从多属性参数角度对探地雷达信号进行处理与解释,可以较好的识别异常体的位置和属性信息,提高了探地雷达解释结果的可靠性. 相似文献
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前兆观测干扰信号频谱特征分析 总被引：2，自引：2，他引：0
地震前兆观测数据中干扰信号频繁出现,大大增加了地震前兆异常信息提取难度。本文选用基于傅里叶变换的功率谱、傅里叶谱以及基于希尔伯特-黄变换的边际谱方法,针对黑龙江地区数字化水位和竖直摆倾斜测项中的典型干扰信号进行分析,提取了水位高频干扰、周期干扰以及竖直摆倾斜的风扰、同震应变等常见干扰信号的频谱特征。通过对比3种频谱分析方法的差异性,发现功率谱法和傅里叶谱对提取干扰和噪声等平稳信号更加有效,而边际谱法对提取同震应变波等非平稳信号的效果更加显著。 相似文献
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受窗函数的影响,短时傅里叶变换、小波变换、S变换等传统时频分析方法的分辨率不高.为了提高信号时频变换分辨率,发展了同步挤压小波变换算法;该算法将信号的时频谱值向其中心频率位置挤压,改善了信号时频分析结果,使得信号时频分辨率得到了很大的提升.但由于传统算法时窗固定,处理缺乏灵活性;因此,本文对S变换窗函数进行扩展,提出了同步挤压广义S变换.通过自适应窗函数挤压信号在S域的时频谱值,提高了算法的灵活性和时频分析聚焦能力.运用同步挤压广义S变换对南海某工区实际地震数据进行分频处理,结果显示含油气层能量随着频率的增加而逐渐衰减.因此,使用同步挤压广义S变换对地震数据进行分析处理,不仅可以对储层含油气性进行准确的检测,还可以对地层进行精确的标定. 相似文献
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本文采用Hilbert-Huang变换分别对磁暴干扰下的“天宫二号”空间实验室大气质谱信号和乌鲁木齐地磁基准台FHDZ-M15所产出地磁数据进行特征分析.实验首先采用小波分析方法分析两种信号的能量谱,结果可得:“天宫二号”空间实验室大气质谱信号和M15地磁信号在磁暴时段能量较为集中,且幅值较大.该实验表明两种信号的能量分布成正相关性.基于Hilbert-Huang变换的时频聚集性及处理非平稳信号的能力,实验进一步采用Hilbert-Huang变换对磁暴干扰下的两种信号进行时频特性分析.通过对两种信号的Hilbert-Huang谱分析可得:“天宫二号”空间实验室大气质谱信号和M15地磁信号在磁暴干扰下的频率均主要集中在0.2 Hz之内.同时,Hilbert-Huang谱实验清晰反映出了两种信号能量随时间和频率的分布情况. 相似文献
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This study considers the possibility of using the new methods of time-frequency transforms, such as chirplet and warblet transforms, to analyze the digital observational data of geomagnetic pulsations of Pc5 type. For this purpose, necessary algorithms of calculation and appropriate software were developed. The chirplet transform method (CT) is used to analyze signals with a linear frequency modulation. A chirplet variation, the so-called warblet transform, is used to analyze signals with a nonlinear frequency modulation. Since, in studying geomagnetic pulsations, it is difficult to make assumptions on the character of the behavior of the instantaneous frequency of the signal, the special generalized warblet transform (GWT) was used for the analysis. The GWT has a high spatiotemporal resolution and was developed to analyze oscillations both with a periodic and nonperiodic change of the instantaneous frequency. The software developed for GWT calculation was used to study daytime geomagnetic Pc5 pulsations with durations of several hours that were detected via the network of ground-based magnetometers of the Scandinavian IMAGE profile during the magnetic storm of May 29–30, 2003. For the first time, temporal variations of the instantaneous frequency of geomagnetic pulsations are determined and their possible use in studying the fine spatial structure of Pc5 waves is shown. 相似文献
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磁线圈对地磁场的物理模拟及对地磁导航研究的意义 总被引：1，自引：0，他引：1
利用磁线圈对地球基本磁场开展动态模拟,将地磁场随空间的变化转化为在实验室中随时间的变化,能够为地磁导航系统的匹配试验提供物理仿真的地磁场环境。本项研究依照虚拟仪器技术思路,对磁线圈、恒流电源、磁通门磁力仪(或Overhauser磁力仪)和工控机进行数字化连接,并采用LabVIEW编程进行驱动控制,通过自动调节线圈绕组中的电流大小来实现对磁场的物理模拟并进行实时监测,尝试组建了地磁场动态模拟系统,并分别开展了对地磁场总强度和三分量信号的动态模拟实验。模拟系统可以实现天然地磁场和人工编制两种动态信号的输出模拟,且拟合效果良好。地磁场动态模拟系统的初步建立为今后地磁匹配试验等研究提供了仿真磁场环境。 相似文献
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In this paper, we compare the denoising- and inversion-based deblending methods using Stolt migration operators. We use Stolt operator as a kernel to efficiently compute apex-shifted hyperbolic Radon transform. Sparsity promoting transforms, such as Radon transform, can focus seismic data into a sparse model to separate signals, remove noise or interpolate missing traces. Therefore, Radon transforms are a suitable tool for either the denoising- or the inversion-based deblending methods. The denoising-based deblending treats blending interferences as random noise by sorting the data into new gathers, such as common receiver gather. In these gathers, blending interferences exhibit random structures due to the randomization of the source firing times. Alternatively, the inversion-based deblending treats blending interferences as a signal, and the transform models this signal by incorporating the blending operator to formulate an inversion problem. We compare both methods using a robust inversion algorithm with sparse regularization. Results of synthetic and field data examples show that the inversion-based deblending can produce more accurate signal separation for highly blended data. 相似文献
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A method to identify the P-arrival of microseismic signals is proposed in this work, based on the algorithm of intrinsic timescale decomposition (ITD). Using the results of ITD decomposition of observed data, information of instantaneous amplitude and frequency can be determined. The improved ratio function of short-time average over long-time average and the information of instantaneous frequency are applied to the time-frequency-energy denoised signal for picking the P-arrival of the microseismic signal. We compared the proposed method with the wavelet transform method based on the denoised signal resulting from the best basis wavelet packet transform and the single-scale reconstruction of the wavelet transform. The comparison results showed that the new method is more effective and reliable for identifying P-arrivals of microseismic signals. 相似文献
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选取磁通门磁力仪数据,利用经验模态分解法提取地磁脉动,并与传统小波分解法提取的地磁脉动方法作对比,分析子午链区域几个地磁台站提取的地磁脉动的纬度效应和经度效应。结果表明,经验模态分解法提取的地磁脉动形态清晰,易于辨识,与小波法相比,不用选择基函数,更适合于分析非稳态信号。 相似文献
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Noise suppression for microseismic data by non‐subsampled shearlet transform based on singular value decomposition 
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下载免费PDF全文 The existence of strong random noise in surface microseismic data may decrease the utility of these data. Non‐subsampled shearlet transform can effectively suppress noise by properly setting a threshold to the non‐subsampled shearlet transform coefficients. However, when the signal‐to‐noise ratio of data is low, the coefficients related to the noise are very close to the coefficients associated with signals in the non‐subsampled shearlet transform domain that the coefficients related to the noise will be retained and be treated as signals. Therefore, we need to minimise the overlapping coefficients before thresholding. In this paper, a singular value decomposition algorithm is introduced to the non‐subsampled shearlet transform coefficients, and low‐rank approximation reconstructs each non‐subsampled shearlet transform coefficient matrix in the singular value decomposition domain. The non‐subsampled shearlet transform coefficients of signals have bigger singular values than those of the random noise, which implies that the non‐subsampled shearlet transform coefficients can be well estimated by taking only a few largest singular values. Therefore, those properties of singular value decomposition may significantly help minimise overlapping of noise and signals coefficients in the non‐subsampled shearlet transform domain. Finally, the denoised microseismic data are obtained easily by giving a simple threshold to the reconstructed coefficient matrix. The performance of the proposed method is evaluated on both synthetic and field microseismic data. The experimental results illustrate that the proposed method can eliminate random noise and preserve signals of interest more effectively. 相似文献
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地磁参量实时测量野值的在线辨识与改正是影响地磁导航算法定位概率和精度的重要因素.地磁导航定位的研究目前主要集中于匹配定位算法,地磁参量实时测量数据处理的研究较少.本文将多层递阶非平稳时间序列预测模型引入海洋地磁参量实时测量野值在线辨识与改正,利用多层递阶模型对实时测量值进行一步预测,根据迪克松准则进行野值辨识,利用中值滤波和一步预测值对野值进行改正.仿真数据和实测数据的实验室仿真结果表明,本文提出的野值在线辨识与改正算法不仅可以检测全部孤立型野值而且对多数斑点型野值也有较好的辨识效果,对产生野值处信号的复原误差小于5%. 相似文献
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在地震资料中,噪声干扰严重影响了有效信号的提取,为此必须进行信噪分离处理.本文提出一种基于Curvelet变换和KL变换相结合的软硬阈值折衷处理方法.首先对地震数据进行Curvelet变换,然后对各尺度系数选取适当阈值压制噪声干扰,再利用KL变换提取数据中的相干有效信号,最后重构得到去噪后的记录.经合成记录和实际地震资料处理实验证明,该方法与小波变换法相比较,更能有效进行信噪分离,提高地震剖面信噪比和分辨率. 相似文献
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In this paper, a novel data denoising method is proposed for seismic exploration with a vibrator which produces a chirp-like signal. The method is based on fractional wavelet transform (FRWT), which is similar to the fractional Fourier transform (FRFT). It can represent signals in the fractional domain, and has the advantages of multi-resolution analysis as the wavelet transform (WT). The fractional wavelet transform can process the reflective chirp signal as pulse seismic signal and decompose it into multi-resolution domain to denoise. Compared with other methods, FRWT can offer wavelet transform for signal analysis in the timefractional-frequency plane which is suitable for processing vibratory seismic data. It can not only achieve better denoising performance, but also improve the quality and continuity of the reflection syncphase axis. 相似文献