用于地震数据时频分析的 W 变换及其改进方法

IF 7 Q1 ENERGY & FUELS Petroleum Exploration and Development Pub Date : 2024-08-01 DOI:10.1016/S1876-3804(24)60513-6
Yanghua WANG , Ying RAO , Zhencong ZHAO
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引用次数: 0

摘要

传统的线性时频分析方法无法同时在时间和频率维度上实现高分辨率和能量聚焦,尤其是在低频区域。为了提高线性时频分析方法在低频区的分辨率,我们提出了 W 变换法,即在线性变换中引入瞬时频率作为参数,构建与地震数据瞬时频率相匹配的分析时间窗。本文将 W 变换法与典型的非线性时频分析方法 Wigner-Ville 分布(WVD)进行了比较。显示时频域能量分布的 WVD 方法能清晰地显示小波的时间引力中心和频率引力中心,而 W 变换的时频谱也具有清晰的能量聚焦引力中心,这是因为引入了任意时间位置对应的瞬时频率作为变换参数。因此,W 变换可以直接以 WVD 方法为基准。我们总结了近年来 W 变换和三种改进方法的发展,阐述了标准 W 变换、啁啾调制 W 变换、分数阶 W 变换和线性规范 W 变换的演变。通过 W 变换在河道砂体识别和储层预测中的三个应用实例,验证了 W 变换可以提高时频谱的分辨率和能量聚焦能力。
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The W transform and its improved methods for time-frequency analysis of seismic data

The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time, especially in the low frequency region. In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region, we have proposed a W transform method, in which the instantaneous frequency is introduced as a parameter into the linear transformation, and the analysis time window is constructed which matches the instantaneous frequency of the seismic data. In this paper, the W transform method is compared with the Wigner-Ville distribution (WVD), a typical nonlinear time-frequency analysis method. The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet, while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing, because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter. Therefore, the W transform can be benchmarked directly by the WVD method. We summarize the development of the W transform and three improved methods in recent years, and elaborate on the evolution of the standard W transform, the chirp-modulated W transform, the fractional-order W transform, and the linear canonical W transform. Through three application examples of W transform in fluvial sand body identification and reservoir prediction, it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.

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CiteScore
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发文量
473
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