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Automatic Stratification Strategy of Well Logging Curves Based on Wavelet Transform

机译:基于小波变换的测井曲线自动分层策略

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Based on the feature analysis of well logging signal noise, we try to establish a well logging noise model in this paper. The problems focus on the implementation of Symlet wavelet and cubic spline wavelet on curves stratification of well logging signal. According to the specialty of well logging signals, we adopt discrete wavelet transform and wavelet packet to be used to decompose the logging signal, which can saves vertical resolution of logging curve, and maximum possible recovery of thin layer information. The simulations indicate the wavelet analysis method for automatic logging curve stratification proposed in this article better reflects the interface of lithology change and the result of automatic stratification is basically consistent with the actual situation, which shows obvious theoretical and practical significance to the research of well logging curves stratification.
机译:在测井信号噪声特征分析的基础上,尝试建立测井噪声模型。问题主要集中在测井信号曲线分层中Symlet小波和三次样条小波的实现上。根据测井信号的特点,采用离散小波变换和小波包分解测井信号,可以节省测井曲线的垂直分辨率,最大程度地恢复薄层信息。仿真结果表明,本文提出的小波分析自动测井曲线分层方法较好地反映了岩性变化的界面,自动分层的结果与实际情况基本吻合,对测井研究具有明显的理论和现实意义。曲线分层。

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