Application of Curvelet Transform in Suppressing Random Noise of Seismic Data

刁塑; 张恒琪; 王冬年

doi:10.16056/j.1005-7676.2020.01.019

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Application of Curvelet Transform in Suppressing Random Noise of Seismic Data

更新时间：2026-01-19

- Application of Curvelet Transform in Suppressing Random Noise of Seismic Data
- Issue 1, Pages: 87-90(2020)
- 作者机构：
  
  东华理工大学地球物理与测控技术学院
- 作者简介：
- 基金信息：
- DOI：10.16056/j.1005-7676.2020.01.019
  CLC： P631.44
- Published：2020
- 稿件说明：
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[1]刁塑,张恒琪,王冬年.基于曲波变换在地震数据随机噪声压制的应用[J].能源研究与管理,2020(01):87-90.

刁塑, 张恒琪, 王冬年. Application of Curvelet Transform in Suppressing Random Noise of Seismic Data[J]. 2020, (1): 87-90.
[1]刁塑,张恒琪,王冬年.基于曲波变换在地震数据随机噪声压制的应用[J].能源研究与管理,2020(01):87-90. DOI： 10.16056/j.1005-7676.2020.01.019.

刁塑, 张恒琪, 王冬年. Application of Curvelet Transform in Suppressing Random Noise of Seismic Data[J]. 2020, (1): 87-90. DOI： 10.16056/j.1005-7676.2020.01.019.

摘要

目前

常规的曲波变换去噪方法是针对地震数据全局去噪

这样会损失部分有效波能量。为此

采用局部自适应曲波变换去噪方法

通过在不同尺度下设置不同阈值

得到每个尺度下硬阈值函数

压制每个尺度内的随机噪声

可以更多地保留低幅值有效波能量。实际数据处理结果表明

该方法相比常规曲波变换全局去噪方法提高了地震数据的信噪比。

Abstract

The conventional denoising method based on curvelet transform is aimed at the whole denoising of seismic data currently. Part of the effective energy is lost. The adaptive denoising method based on curvelet transform is used to set different threshold at different scales

then the novel method calculate hard threshold function at each scale to suppress random noise in each scale and retain low amplitude effective wave energy. Compared with the conventional method

the novel method improves the signal-to-noise ratio（SNR） of results of processing actual seismic data greatly.

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