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基于经验模态分解的核磁共振测井信号去噪新方法
A New De-noising Method of NMR Log Signals Based on Empirical Mode Decomposition
【摘要】 核磁共振的信噪比在T2谱反演中起着重要作用,信号噪声容易造成解的偏离,这种情况在信噪比小的核磁共振测井中更加突出。把最新发展的经验模态分解方法引入到核磁共振测井信号处理中来,对实测信号进行了去噪和对比分析,结果表明,该方法具有自适应和高效的特点,能反映原始信号的固有特性,经验模态分解方法对消除测井信号的噪声是有效的,与传统的多点平滑结果相比:SNR从18dB左右提高到68dB左右,为T2谱的精确反演奠定了良好的基础。
【Abstract】 The SNR plays an important role in the inversion of NMR’ s T2 spectrum.The noises easily cause the solution of deviate from the truth,and it is a more prominent situation in the small signal to noise ratio of nuclear magnetic resonance logging.The empirical mode decomposition(EMD) was firstly proposed to the processing of NMR logging signals in the paper.The EMD can reflect the intrinsic physical characteristics of original data and the method can adapt to the variations of signals.The results showed that the result after noise filtering by EMD was satisfactory.Comparing with some points smoothing,the SNR is improved from 18 dB to 68dB.It makes the inversion of NMR’ s T2 spectrum more representative and robust.
【Key words】 empirical mode decomposition; nuclear magnetic resonance logging; SNR; de-noising;
- 【文献出处】 核电子学与探测技术 ,Nuclear Electronics & Detection Technology , 编辑部邮箱 ,2010年03期
- 【分类号】TN911.7;P631.817
- 【被引频次】9
- 【下载频次】272