| 台站地震资料的时频域自适应极化分析和滤波 |
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| 引用本文： | 马见青,李庆春,王卫东,王美丁,李春兰.台站地震资料的时频域自适应极化分析和滤波[J].西北地震学报,2016,38(1):136-143,149. |
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| 作者姓名： | 马见青 李庆春 王卫东 王美丁 李春兰 |
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| 作者单位： | 长安大学 地质工程与测绘学院, 陕西 西安 710054;长安大学 地质工程与测绘学院, 陕西 西安 710054;长安大学 地质工程与测绘学院, 陕西 西安 710054;西北有色地质勘查局 物化探总队, 陕西 西安 710068;西北有色地质勘查局 物化探总队, 陕西 西安 710068 |
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| 基金项目： | 国家自然科学基金项目(41374145);高等学校博士点基金项目(20120205130002);中央高校基金项目(310826161008) |
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| 摘 要： | 提出一种自适应协方差的时频域极化滤波方法。该方法在广义S变换时频方法的基础上,构造时频域自适应协方差矩阵,通过特征分析计算时频域瞬时极化参数,设计极化滤波器,实现多分量地震极化分析和滤波。其优势在于协方差矩阵的分析时窗的长度由多分量地震数据的瞬时频率确定,可以自适应于有效信号的周期,在每个时频点计算极化参数不需要进行插值处理;结合时间频率信息,解决在时间域或频率域波形或频率重叠的信号具有明显的直观性。模型数据及实际三分量台站地震数据处理结果表明,该极化滤波方法在台站地震资料分析和处理方面具有很好的直观性和较高的分辨率。
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| 关 键 词： | 极化滤波 时频分析 广义S变换 自适应协方差矩阵 多分量地震 |
| 收稿时间： | 2014/11/20 0:00:00 |
Adaptive Polarization Analysis and Filtering of Station Seismic Data in Time-Frequency Domain |
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| MA Jian-qing,LI Qing-chun,WANG Wei-dong,WANG Mei-ding and LI Chun-lan.Adaptive Polarization Analysis and Filtering of Station Seismic Data in Time-Frequency Domain[J].Northwestern Seismological Journal,2016,38(1):136-143,149. |
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| Authors: | MA Jian-qing LI Qing-chun WANG Wei-dong WANG Mei-ding and LI Chun-lan |
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| Institution: | School of Geological Engineering and Surveying, Chang''an University, Xi''an 710054, Shaanxi, China;School of Geological Engineering and Surveying, Chang''an University, Xi''an 710054, Shaanxi, China;School of Geological Engineering and Surveying, Chang''an University, Xi''an 710054, Shaanxi, China;Team of Geophysical and Geochemical Exploration, Northwestern Geology Exploration Bureau for NonferrousMetal Resources, Xi''an 710068, Shaanxi, China;Team of Geophysical and Geochemical Exploration, Northwestern Geology Exploration Bureau for NonferrousMetal Resources, Xi''an 710068, Shaanxi, China |
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| Abstract: | Polarization filtering methods based on a covariance matrix play an important role in the processing of multicomponent seismograms due to their explicit physical meaning, ease of implementation, and high efficiency. Conventional polarization filtering methods that are realized in a time domain have major limitations in resolving seismic signals in which waveforms or frequencies overlap. Time-frequency analysis methods are especially suitable for resolving separate seismic signals that overlap in time but have different spectra for instantaneous signal analysis. These methods can describe frequency components of a signal that change over time. Owing to the advantages of the time-frequency analysis method, it can be used in polarization analysis. This study presents a polarization filtering method based on the generalized S-transform to suppress surface waves in a time-frequency domain. On one hand, we remold the window function of the S-transform and improve the frequency resolution of seismic signals by increasing regulatory factors to create a nonlinear change in the window function with the signal frequency. On the other, we structure the cross-energy matrix in the time-frequency domain using the generalized S-transform, compute instantaneous polarization attributes by eigenanalysis, and design a filtering algorithm in the time-frequency domain to achieve polarization filtering of multicomponent seismic signals. The specialties of this method are that the length of the time window of the covariance matrix is determined by the instantaneous frequency of the multicomponent seismic data and it can adapt to the dominant period of the desired signal. Moreover, it calculates polarization parameters at each time-frequency point and no longer needs to perform interpolation. It is particularly accurate in processing signals with overlapping waveforms or frequencies in the time or frequency domain. The results of processing data from models and real three-component seismograms show that this method has very high clarity, high resolution, and practicability in the data analysis and processing of seismograms. This representation enables the detection of dispersion in polarization attributes, which can be further exploited to infer some physical characteristics of the medium under investigation. Moreover, this representation offers the ability to distinguish between attributes that belong to different coherent events that may overlap in time but with different frequency contents separated by time-dependent frequency cutoffs. Identifying and separating different wave types are made possible by designing filters that operate in the time-frequency domain. Attributes such as azimuth, dip, and signed ellipticity can also be used to improve the filtering algorithms. |
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| Keywords: | polarization filtering time-frequency analysis generalized S-transform adaptive covariance matrix multi-component seismogram |
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