Suppression of surface-related and internal multiples is an outstanding challenge in seismic data processing. The former is particularly difficult in shallow water, whereas the latter is problematic for targets buried under complex, highly scattering overburdens. We have developed a two-step, amplitude- and phase-preserving, inversion-based workflow that addresses these problems. We apply robust estimation of primaries by sparse inversion (R-EPSI) to solve simultaneously for the surface-related primaries Green’s function and the source wavelet. A significant advantage of the inversion approach of the R-EPSI method is that it does not rely on an adaptive subtraction step that typically limits other demultiple methods such as surface-related multiple elimination. The resulting Green’s function is used as the input to a Marchenko equation-based approach to predict the complex interference pattern of all overburden-generated internal multiples at once. In this approach, no a priori information about the subsurface is needed. In theory, the interbed multiples can be predicted with correct amplitude and phase and, again, no adaptive filters are required. We illustrate this workflow by applying it on an Arabian Gulf field data example. It is crucial that all preprocessing steps are performed in an amplitude-preserving way to restrict any impact on the accuracy of the multiple prediction. In practice, some minor inaccuracies in the processing flow may end up as prediction errors for which corrections will be needed. Hence, we conclude that the use of conservative adaptive filters were necessary to obtain the best results after interbed multiple removal. The obtained results indicate promising suppression of surface-related and interbed multiples.

中文翻译：

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通过稀疏反演和基于Marchenko方程的工作流对原始数据进行稳健的估计，以在浅水层和复杂覆盖层的情况下进行多重抑制：阿拉伯海湾的2D案例研究

在地震数据处理中，抑制与地面有关的和内部的倍数是一个巨大的挑战。前者在浅水中特别困难，而后者对于埋在复杂的，高度分散的覆盖层下的目标是有问题的。我们已经开发了一个两步，基于幅度和相位保持，基于反转的工作流程来解决这些问题。我们应用稀疏反演（R-EPSI）对原色进行鲁棒估计，以同时解决与表面相关的原色Green函数和源小波。R-EPSI方法的反演方法的一个显着优势是它不依赖于自适应减法步骤，该步骤通常会限制其他解乘方法，例如与表面相关的多重消除。所得的格林函数用作基于Marchenko方程的方法的输入，以一次预测所有上覆层生成的内部倍数的复杂干涉图样。在这种方法中，不需要有关地下的先验信息。从理论上讲，可以以正确的幅度和相位来预测交织倍数，并且再次不需要自适应滤波器。我们通过将其应用于阿拉伯海湾实地数据示例来说明此工作流程。至关重要的是，所有预处理步骤均应以保持幅度的方式执行，以限制对多重预测精度的任何影响。在实践中，处理流程中的一些细微误差可能最终会成为预测误差，需要对其进行校正。因此，我们得出的结论是，在多次插入去除之后，必须使用保守的自适应滤波器来获得最佳结果。获得的结果表明有希望的抑制表面相关和互穿倍数。