Spectral decomposition has been widely used to detect frequency-dependent anomalies associated with hydrocarbons. By ignoring the time-variant feature of the frequency content of individual reflected wavelets, we have adopted a sparse time-frequency spectrum and developed a matching pursuit-based sparse spectral analysis (MP-SSA) method to estimate the sparse time-frequency representation of the seismic data. Further, we evaluate a generalized nonstationary convolution model concerning propagation attenuation and frequency-dependent reflectivity, and we mathematically evaluate the sparse time-frequency spectrum of the nonstationary seismic data as being equal to the product of the Fourier spectrum of the source wavelet, frequency-dependent reflection coefficient, and the cumulative attenuation during seismic wave propagation. Therefore, the reflectivity spectrum, which is a combination of the frequency-dependent reflectivity and the propagation attenuation, can be determined by dividing the sparse time-frequency spectrum of the seismic data by the Fourier spectrum of the source wavelet. Application of the matching pursuit-based decomposition methods to synthetic nonstationary convolutional data illustrates that the adopted MP-SSA spectrum shows a higher time resolution than the matching pursuit-based Wigner-Ville distribution and the matching pursuit-based instantaneous spectral analysis spectra. Notably, the MP-SSA method can avoid spectral smearing, which may introduce distortions to the frequency-dependent anomaly estimation. Application of the amplitude versus frequency analysis based on MP-SSA to field data illustrates the potential of using the sparse reflectivity spectral intercept and gradient to detect the hydrocarbon reservoirs.

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基于匹配追踪的稀疏频谱分析：从非平稳地震数据估计频率相关异常

频谱分解已被广泛用于检测与碳氢化合物相关的频率相关异常。通过忽略单个反射小波频率分量的时变特征，我们采用了稀疏的时频谱，并开发了一种基于匹配追踪的稀疏谱分析（MP-SSA）方法来估计稀疏时频表示。地震数据。此外，我们评估了与传播衰减和频率相关的反射率有关的广义非平稳卷积模型，并在数学上将非平稳地震数据的稀疏时频频谱评估为等于源小波的傅立叶频谱，频率-依赖的反射系数，以及地震波传播期间的累积衰减。因此，通过将地震数据的稀疏时间频谱除以源子波的傅立叶频谱，可以确定反射率频谱，该频谱是依赖于频率的反射率和传播衰减的组合。将基于匹配追踪的分解方法应用于合成的非平稳卷积数据表明，所采用的MP-SSA频谱显示的时间分辨率高于基于匹配追踪的Wigner-Ville分布和基于匹配追踪的瞬时频谱分析频谱。值得注意的是，MP-SSA方法可以避免频谱拖尾，这会给依赖于频率的异常估计带来失真。