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高斯束偏移是一种高效、稳健的深度域成像方法,其不仅保持了射线类偏移的高效、灵活性,而且具有接近波动方程偏移的成像精度.匹配追踪是一种基于匹配寻优算法的信号稀疏分解技术,常用于地震信号的时频分析和去噪处理中.本文将建立在Ricker子波原子库的匹配追踪算法应用于常规的高斯束偏移中,并结合Kirchhoff偏移的单输入道成像方式,发展了一种成像精度更高且适用于低信噪比资料的叠前高斯束成像方法.该方法通过合理地控制匹配追踪稀疏分解的迭代次数,可以有效地去除地震信号中的随机干扰,提高成像结果的信噪比;此外,在偏移过程中,本文方法采用了Kirchhoff偏移的单输入道成像方式,解决了常规高斯束方法对浅层小尺度地质体成像不准的问题,提高浅部反射层的成像精度.两个典型的数值算例验证了本文方法的有效性和适应性.
Gaussian beam migration is an efficient and robust method of depth field imaging, which not only maintains the efficiency and flexibility of ray-like migration, but also has imaging accuracy close to that of wave equation migration. Matching pursuit is a method based on matching optimization The algorithm of signal sparse decomposition is often used in the time-frequency analysis and denoising of seismic signals.In this paper, the matching pursuit algorithm based on Ricker wavelet library is applied to the conventional Gaussian beam migration, combined with the Kirchhoff migration Single input channel imaging method, a pre-stack Gaussian beam imaging method with higher imaging accuracy and suitable for low signal-to-noise ratio data is developed. This method can effectively remove the seismic signal by reasonably controlling the iteration number of matching pursuit sparse decomposition In the process of migration, Kirchhoff offset single-input channel imaging method is adopted in this method to solve the problem that the conventional Gaussian beam method does not image shallow small-scale geological bodies Quasi-problem, improve the imaging accuracy of the shallow reflection layer.Two typical numerical examples verify the effectiveness and adaptability of the proposed method.