| GHM类正交多小波变换及其在地震资料去噪中的应用 |
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| 引用本文： | 陈香朋,曹思远.GHM类正交多小波变换及其在地震资料去噪中的应用[J].地震地质,2005,27(3):479-486. |
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| 作者姓名： | 陈香朋 曹思远 |
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| 作者单位： | 胜利油田有限公司物探研究院,东营,257022;中国石油大学(北京)物探重点实验室,北京,102249;中国石油大学(北京)物探重点实验室,北京,102249 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 多小波是对小波理论的一个新发展,它可以同时满足正交性、对称性、短支撑等良好的特性要求。文中介绍了多小波基本理论、多小波变换具体过程及预处理方法,提出了基于GHM类多小波变换的地震资料软阈值去噪方法,通过对合成数据和实际资料进行处理分析,表明多小波变换在有效压制随机噪声的同时,能较好地保留原信号的特征信息,是一种行之有效的去噪方法
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| 关 键 词： | 多小波 预处理 去噪 软阈值 |
| 文章编号： | 0253-4967（2005）03-0479-08 |
| 收稿时间： | 2004-05-17 |
| 修稿时间： | 2005-05-13 |
GHM-LIKE ORTHOGONAL MULTIWAVELET TRANSFORM AND ITS APPLICATION TO DE-NOISING OF SEISMIC DATA |
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| CHEN Xiang-peng,CAO Si-yuan.GHM-LIKE ORTHOGONAL MULTIWAVELET TRANSFORM AND ITS APPLICATION TO DE-NOISING OF SEISMIC DATA[J].Seismology and Geology,2005,27(3):479-486. |
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| Authors: | CHEN Xiang-peng CAO Si-yuan |
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| Abstract: | Muhiwavelet is a new development in the wavelet theory and it can offer simultaneously orthogonality, symmetry, and short support. In signal processing, the orthogonality preserves energy, the symmetry avoids signal distortion and the short support reduces the boundary effects. Therefore multiwavelet is very suitable for various signal processing applications, especially denoising. The paper presents muhiwavelet principles, transformation procedures, pre-processing methods and proposes a new GHM-like multiwavelet-based denoising method. In seismic data processing, the attenuation of random noise is an important research subject. Conventional temporal or spatial filtering methods often damage the useful signals while suppressing noise, and the single wavelet transforms can cause signal distortion since it fails to offer simultaneously the orthogonality and symmetry. The paper adopts muhiwavelet and muhiresolution method to remove noise contained in seismic data. Seismic data is first preprocessed to generate a group of vector data, and then approximate and detailed signals of various scales are generated by two-level multiwavelet transformation. Finally detailed signals are processed by soft threshold and denoised seismic data are obtained by reverse muhiwavelet transformation. The denoising experiments of synthetic and real data show that muhiwavelet transform is effective for noise reduction and can preserve signal features at the same time. |
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| Keywords: | muhiwavelet pre-filter de-noising soft threshold |
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