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中文摘要：
地震资料去噪是地震数据处理非常重要的步骤，现代地震勘探对地震资料信噪比的要求越来越高．总体经验模式分解（ensemble empirical mode decomposition，简写为EEMD）是一种新的时域信号处理方法，它是对经验模式分解（empirical mode decomposition，简写为EMD）的一种改进．EEMD将目标信号经验地分解为几个被称为本征模态函数（intrinsic mode function，简写为IMF）的子信号，它是一个自适应的带通滤波器组．本文介绍了EMD和EEMD分解的基本原理，提出了一种基于EEMD分解的地震信号随机噪声消除的方法．本文利用含噪信号EEMD分解后其有效信号和随机噪声在IMF中差异分布的特点，给出一种地震信号随机噪声消除的新方法．
英文摘要：
Noise attenuation is a very important step for seismic data processing. It is forward demanded to improve the seismic data signal-to-noise rate in modern seismic exploration. The ensemble empirical mode decomposition （EEMD）, which is the betterment of empirical mode decomposition （EMD）, is proposed as a highly effective timedomain filter. The EEMD is an adaptive band-pass filter, which empirically reduces a signal to several subsignals defined as intrinsic mode function （IMF）. The paper introduces the basic principles of EMD and EEMD, and proposes a noise attenuation method based on EEMD. Using the different characteristics of significant signal and noise in IMFs, the method provides a new solution for random noise attenuation of seismic data.
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