Incorrect imaging of internal multiples can lead to substantial imaging artifacts. It is estimated that most seismic images available to exploration and production companies have had no direct attempt at internal multiple removal. Previously, we have considered the role of sparsity promoting transforms for improving practical prediction quality for algorithms derived from the inverse scattering series (ISS). Furthermore, we have developed a demigration-migration approach to perform multidimensional internal multiple prediction with migrated data and provided a synthetic proof of concept. Now, we consider application of the demigration-migration approach to field data from the Norwegian Sea and compare it to a poststack method (from a previous related work). Beyond application to a wider range of data with our approach, we consider algorithmic and implementational optimizations of the ISS prediction algorithms to further improve the applicability of the multidimensional formulations.

中文翻译：

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使用具有稀疏性提升的逆散射序列进行内部多重预测 - 第 2 部分：应用策略和现场数据示例

内部多次波的不正确成像会导致大量成像伪影。据估计，可供勘探和生产公司使用的大多数地震图像都没有直接尝试进行内部多次清除。之前，我们已经考虑了稀疏促进变换的作用，以提高从逆散射序列 (ISS) 派生的算法的实际预测质量。此外，我们开发了一种去迁移 - 迁移方法来使用迁移的数据执行多维内部多重预测，并提供了概念的综合证明。现在，我们考虑将偏移迁移方法应用于挪威海的现场数据，并将其与叠后方法（来自之前的相关工作）进行比较。除了使用我们的方法应用于更广泛的数据之外，