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一种新的基于卡尔曼滤波的地震记录同相轴跟踪方法及性能分析
引用本文:邓小英, 胡健, 李月, 郑乐, 毕锐锐. 一种新的基于卡尔曼滤波的地震记录同相轴跟踪方法及性能分析[J]. 地球物理学报, 2014, 57(1): 270-279, doi: 10.6038/cjg20140122
作者姓名:邓小英  胡健  李月  郑乐  毕锐锐
作者单位:1. 北京理工大学信息与电子学院, 北京 100081; 2. 中国人民解放军95633部队, 邛崃 611531; 3. 吉林大学通信工程学院, 长春 130012
基金项目:国家自然科学基金项目(41374114)资助.
摘    要:在地震勘探领域中,卡尔曼滤波常用于地震信号的反褶积以提高地震勘探资料的分辨率和信噪比. 不同于此,本文建立一个新的卡尔曼滤波系统模型并利用卡尔曼滤波跟踪地震记录同相轴. 同相轴信息在对地下介质性质、界面的深度、界面的产状以及油气定性判别等方面具有极其重要的作用. 目前多数拾取地震同相轴的方法与地震波的运动规律结合较少.本文依据地震反射波运动规律构建了用于跟踪地震反射同相轴的卡尔曼滤波系统的状态方程和量测方程,并将炮检距、地震子波到达时和层速度等重要物理量融入所建方程,给出滤波模型和初始化方法,分析不同因素对该系统滤波性能的影响. 仿真实验表明,所提出的跟踪滤波系统能较好地拾取地震反射同相轴信息,为拾取地震同相轴提供了一条新途径.

关 键 词:地震勘探记录   卡尔曼滤波   同相轴跟踪
收稿时间:2013-01-28
修稿时间:2013-12-27

A new tracking approach of the seismic record event based on Kalman filtering and its performance analysis
DENG Xiao-Ying, HU Jian, LI Yue, ZHENG Le, BI Rui-Rui. A new tracking approach of the seismic record event based on Kalman filtering and its performance analysis[J]. Chinese Journal of Geophysics (in Chinese), 2014, 57(1): 270-279, doi: 10.6038/cjg20140122
Authors:DENG Xiao-Ying  HU Jian  LI Yue  ZHENG Le  BI Rui-Rui
Affiliation:1. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China; 2. Unit 95633 of PLA, Qionglai 611531, China; 3. College of Communication Engineering, Jilin University, Changchun 130012, China
Abstract:In the field of seismic exploration, the Kalman filter is often used for deconvolution of seismic data in order to improve the resolution and signal-to-noise ratio of seismic records. Differently, a new system model of Kalman filter is established and used to track the event of seismic data in this paper. Events play an important role in many aspects such as judging underground media attributes, depth of interface and oil-gas condition. Few of the present methods for picking the event are related to the motion laws of seismic waves. Based on the time-distance equation of seismic reflected wave, the state equation and measurement equation for the Kalman filtering system for tracking the reflected event are constructed. And the new model involves several important physical quantities such as the arrival time of the seismic wavelet, the offset and the propagation velocity of the seismic wave. Then the filtering model and initialization for the Kalman filter are given. Finally the effects of various parameters on the performances of the Kalman filter are analyzed. The experimental results show that the proposed tracking system can work well in picking the seismic reflected event, which will provide a new solution for picking the seismic event.
Keywords:Seismic record  Kalman filtering  Event tracking
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