迭代Marchenko格式对非理想采样数据的适应性
Adaptation of the iterative Marchenko scheme for imperfectly sampled data
摘要：
Marchenko方法从地表的反射数据中检索对地球地下虚拟源的响应，考虑到多次反射的所有阶次。该方法是基于两个积分表示的聚焦和格林函数。在离散形式中，这些积分由采集几何上的有限求和表示。因此，该方法需要理想的几何形状的定期采样和共定位的源和接收器。最近，新的表示，处理不完全采样数据。这些新的表示法使用点扩散函数（PSF）来重建结果，就好像它们是使用完美的几何体获得的一样。在这里，迭代Marchenko计划适应，使用这些新的表示，占不完美的采样。这种新的方法进行了测试的二维数值例子。结果表明，所提出的计划和标准的迭代计划之间有明显的改善。通过消除对完美几何形状的要求，Marchenko方法可以更广泛地应用于现场数据。
英文摘要：
The Marchenko method retrieves the responses to virtual sources in the Earth's subsurface from reflection data at the surface, accounting for all orders of multiple reflections. The method is based on two integral representations for focusing- and Green's functions. In discretized form, these integrals are represented by finite summations over the acquisition geometry. Consequently, the method requires ideal geometries of regularly sampled and co-located sources and receivers. Recently new representations were derived, which handle imperfectly sampled data. These new representations use point-spread functions (PSFs) that reconstruct results as if they were acquired using a perfect geometry. Here, the iterative Marchenko scheme is adapted, using these new representations, to account for imperfect sampling. This new methodology is tested on a 2D numerical example. The results show clear improvement between the proposed scheme and the standard iterative scheme. By removing the requirement for perfect geometries, the Marchenko method can be more widely applied to field data.
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