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Seismic instantaneous frequency extraction based on the SST-MAW

机译:基于SST-MAW的地震瞬时频率提取

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摘要

The instantaneous frequency (IF) extraction of seismic data has been widely applied to seismic exploration for decades, such as detecting seismic absorption and characterizing depositional thicknesses. Based on the complex-trace analysis, the Hilbert transform (HT) can extract the IF directly, which is a traditional method and susceptible to noise. In this paper, a robust approach based on the synchrosqueezing transform (SST) is proposed to extract the IF from seismic data. In this process, a novel analytical wavelet is developed and chosen as the basic wavelet, which is called the modified analytical wavelet (MAW) and comes from the three parameter wavelet. After transforming the seismic signal into a sparse time-frequency domain via the SST taking the MAW (SST-MAW), an adaptive threshold is introduced to improve the noise immunity and accuracy of the IF extraction in a noisy environment. Note that the SST-MAW reconstructs a complex trace to extract seismic IF. To demonstrate the effectiveness of the proposed method, we apply the SST-MAW to synthetic data and field seismic data. Numerical experiments suggest that the proposed procedure yields the higher resolution and the better anti-noise performance compared to the conventional IF extraction methods based on the HT method and continuous wavelet transform. Moreover, geological features (such as the channels) are well characterized, which is insightful for further oil/gas reservoir identification.
机译:瞬时频率(IF)提取地震数据已被广泛应用于几十年的地震勘探,例如检测地震吸收和表征沉积厚度。基于复杂轨迹分析,Hilbert变换(HT)可以直接提取,这是一种传统方法并易受噪声的影响。在本文中,提出了一种基于SyschroSquezing变换(SST)的鲁棒方法来提取来自地震数据的IF。在该过程中,开发了一种新的分析小波作为基本小波,称为改进的分析小波(MAW)并来自三个参数小波。在经由SST中转换地震信号进入稀疏时频域之后,引入自适应阈值以提高噪声环境中提取的噪声抗扰度和准确性。请注意,SST-MAW重建一个复杂的迹线以提取震动IF。为了证明所提出的方法的有效性,我们将SST-MAW应用于合成数据和场地震数据。数值实验表明,与基于HT方法和连续小波变换的传统提取方法相比,该方法产生了更高的分辨率和更好的抗噪声性能。此外,地质特征(例如通道)很好地表征,这对于进一步的油/气体储层识别是有利的。

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