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首页> 外文期刊>Journal of Applied Geophysics >Estimation of Q factors from reflection seismic data for a band-limited and stabilized inverse Q filter driven by an average-Q model
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Estimation of Q factors from reflection seismic data for a band-limited and stabilized inverse Q filter driven by an average-Q model

机译：由平均Q模型驱动的带限且稳定的反Q滤波器的反射地震数据中的Q因子估计

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摘要

Reliable Q estimation is desirable for model-based inverse Q filtering to improve seismic resolution. On the one hand, conventional methods estimate Q from the amplitude spectra or frequency variations of individual wavelets at different depth (or time) levels, which is vulnerable to the effects of spectral interference and ambient noise. On the other hand, most inverse Q filtering algorithms are sensitive to noise, in order not to boost them, sometimes at the expense of degrading compensation effect. In this paper, the average-Q values are obtained from reflection seismic data based on the Gabor transform spectrum of a seismic trace. We transform the 2-D time-variant frequency spectrum into the 1-D spectrum, and then estimate the average-Q values based on the amplitude attenuation and compensation functions, respectively. Driven by the estimated average-Q model, we also develop a modified inverse Q filtering algorithm by incorporating a time-variant bandpass filter (TVBF), whose high cut off frequency follows a hyperbola along the traveltime from a specified time. Finally, we test this modified inverse Q filtering algorithm on synthetic data and perform the Q estimation procedure on a real reflection seismic data, followed by applying the modified inverse Q filtering algorithm. The synthetic data test and the real data example demonstrate that the algorithm driven by average-Q model may enhance the seismic resolution, without degrading the signal-to-noise ratio.
机译：对于基于模型的反Q滤波，需要可靠的Q估计以提高地震分辨率。一方面，常规方法从不同深度（或时间）水平的单个小波的振幅谱或频率变化估计Q，这很容易受到频谱干扰和环境噪声的影响。另一方面，大多数逆Q滤波算法对噪声敏感，以便不对其进行增强，有时会以降低补偿效果为代价。本文基于地震道的Gabor变换谱从反射地震数据中获得平均Q值。我们将二维时变频谱转换为一维频谱，然后分别基于幅度衰减和补偿函数来估计平均Q值。在估计的平均Q模型的驱动下，我们还结合了时变带通滤波器（TVBF），开发了一种改进的逆Q滤波算法，该滤波器的高截止频率沿从指定时间开始的传播时间遵循双曲线。最后，我们对合成数据测试了这种改进的反Q滤波算法，并对真实反射地震数据执行了Q估计程序，然后应用了改进的反Q滤波算法。综合数据测试和真实数据示例表明，平均Q模型驱动的算法可以提高地震分辨率，而不会降低信噪比。

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