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Reconstructing Missing Near Offset Data and Primaries from Multiples

机译:从倍数偏移数据和次数丢失缺失的重建

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Traditionally, in surface-related multiple elimination (SRME), multiples are predicted from primaries by a spatial convolution process. However, the same relationship between primaries and multiples can be used to describe a deconvolution process, where multiples are transformed into primaries or data. This method is called a focal transform. The method that is presented in this paper is based on the focal transform and reconstructs the primaries or data in the missing near offsets by minimising the estimated primaries. The result of this method is improved by choosing a different subtraction norm and using the fact that multiples predicted along different ways should be the same.
机译:传统上,在表面相关的多个消除(SRME)中,通过空间卷积过程从初始预测倍数。然而,初学者和倍数之间的相同关系可用于描述解构过程,其中倍数被转换为初始或数据。该方法称为焦点变​​换。本文呈现的方法基于焦点变换,并通过最小化估计的原初级来重建近偏移近偏移的初始或数据。通过选择不同的减法规范并使用沿不同方式预测的倍数应该是相同的,改善了该方法的结果。

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