The principle of least-squares-inverse filtering and its application

YANG Sheng-xiong; FU Xi; WU Ya-dong; WEN Peng-fei

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YANG Sheng-xiong, FU Xi, WU Ya-dong, WEN Peng-fei. The principle of least-squares-inverse filtering and its application[J]. Haiyang Xuebao, 2004, 26(3): 75-81.

Citation:

YANG Sheng-xiong, FU Xi, WU Ya-dong, WEN Peng-fei. The principle of least-squares-inverse filtering and its application[J]. Haiyang Xuebao, 2004, 26(3): 75-81.

YANG Sheng-xiong, FU Xi, WU Ya-dong, WEN Peng-fei. The principle of least-squares-inverse filtering and its application[J]. Haiyang Xuebao, 2004, 26(3): 75-81.

Citation:

YANG Sheng-xiong, FU Xi, WU Ya-dong, WEN Peng-fei. The principle of least-squares-inverse filtering and its application[J]. Haiyang Xuebao, 2004, 26(3): 75-81.

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The principle of least-squares-inverse filtering and its application

Received Date: 2004-01-01
Rev Recd Date: 2004-05-07

Abstract

Abstract

In order to improve the resolution of seismic profiles in vertical,the aim of deconvolution is to suppress the ground filtering in exploration.The leas-tsquares error is adopted,that is,considering sum of all anticipant output error as the least condition,to decide the inverse filtering factor.Three kinds of anticipation output is introduced:YUShi wavelet,Ricker wavelet,Buttworth wavelet.These wavelets help to improve the effect of zero-phase.According to the principle above,a software for least-squares-inverse filtering is developed.The results indicate this method not only improves the resolution but also maintains a relatively high ratio of signal-to-noise,especially in the detection of gas hydrate.
- deconvolution,
- least-square-sinverse filtering,
- YuShi wavelet,
- Ricker wavelet,
- Buttworth wavelet

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References(12)

References

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