论文标题
适应不完美采样数据的迭代Marchenko方案
Adaptation of the iterative Marchenko scheme for imperfectly sampled data
论文作者
论文摘要
Marchenko方法从表面的反射数据中检索了地球地下对虚拟来源的响应，这是所有反射的所有顺序。该方法基于聚焦和格林功能的两个积分表示。以离散的形式，这些积分以对采集几何形状的有限总和表示。因此，该方法需要定期采样和共同定位的来源和接收器的理想几何形状。最近得出了新的表示形式，该表示处理不完美的数据。这些新表示使用点扩展函数（PSF），将其重建结果仿佛是使用完美的几何形状获得的。在这里，使用这些新表示形式对迭代的Marchenko方案进行了调整，以解释不完善的采样。在2D数值示例上测试了这种新方法。结果显示了所提出的方案与标准迭代方案之间的明显改善。通过删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。
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.
