西南石油大学学报(自然科学版) ›› 2009, Vol. 31 ›› Issue (6): 56-58.DOI: 10.3863/j.issn.1674-5086.2009.06.011

• 地质勘探 • 上一篇    下一篇

S变换时变滤波在去噪处理中的应用研究

杨海涛1 朱仕军2 杨爱国1 常智1 彭才1   

  1. 1. 中国石油川庆钻探工程有限公司地球物理勘探公司,四川 成都 610213; 2.西南石油大学资源与环境学院,四川 成都 610500
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-12-20 发布日期:2009-12-20

APPLICATION RESEARCH ON TIME VARIABLE FILTERING WITH S-TRANSFORM IN DENOISING PROCESSING

YANG Hai-tao1 ZHU Shi-jun2 YANG Ai-guo1 CHANG Zhi1 PENG Cai1   

  1. 1.Sichuan Petroleum Geophysical Prospecting Company,Chuanqing Drilling Engineering Company Limited,CNPC,Chengdu Sichuan 610213,China;2.School of Resources and Enviroment,Southwest Petroleum University,Chengdu Sichuan 610500,China)JOURNAL OF SOUTHWEST PETROLEUM UNIVERSITY(SCIENCE & TECHNOLOGY EDITION),VOL.31,NO.6,56-58,2009(ISSN 1674-5086,in Chinese
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-12-20 Published:2009-12-20

摘要: 针对常用的滤波去噪方法都受到使用条件的限制,实际资料的滤波去噪不能达到良好效果,S变换时变滤波克服了传统滤波去噪方法滤波因子不能随时间、频率变化而变化的缺陷。将地震资料用S变换方法变换到时频域,对不同时间内不同频率的噪声部分充零,再将去噪后的地震数据利用S反变换到时间域,以获得所需要的有效信号。通过理论计算分析和实例计算表明,S变换时变滤波能够有效去除不同时段、不同频率的噪声。该方法具有一定的可行性。

关键词: S变换, 时频分析, 时变滤波, 地震数据处理, 去噪

Abstract: There are several kinds of filtering methods to diminish the noises.However,all of them are restricted by operating conditions,as a result,a satisfactory effect of filtering can not be obtained from actual data.Time variable filtering with S-transform overcomes the shortage that the filtering factors in traditional filtering and denoising approaches will not change with time and frequency variation.Seismic data are transformed to time-frequency domain by using the S-transformation methods,then,the noises at different time intervals and with different frequencies are zeroized partly.Finally,the seismic data after noise elimination are transformed into time domain again by using S-inverse transformation to achieve the effective signals needed.Based on theoretical and real seismic data calculation,it is believed that S-transform is really an effective method eliminating noises at different time intervals and with different frequencies.

Key words: S-transform, time-frequency analysis, time variable filtering, seismic data processing, denoising

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