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SRME and estimation of primaries by sparse inversion: a hybrid approach

机译:SRME和基于稀疏反演的原始估计:一种混合方法

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摘要

Recently, a new approach to multiple removal has been introduced: estimation of primaries by sparse inversion (EPSI). Although based on the same relationship between primaries and multiples as in surface-related multiple elimination (SRME), it involves quite a different process. Instead of the traditional prediction and subtraction of multiples, in EPSI the unknown primaries are the parameters of a large-scale inversion process. The downside is its long calculation times, involving the equivalent of about 100-200 SRME processes. For improving the accuracy and efficiency in multiple removal a hybrid SRME+EPSI is proposed, which makes use of the strongest points of both SRME and EPSI methodologies. It appears that the final result is better than either the SRME or the EPSI algorithm alone and where the calculation time is limited to the equivalent of 10-20 SRME processes.
机译:最近,引入了一种新的多重去除方法:通过稀疏反演(EPSI)估计原色。尽管基于与表面相关的多重消除(SRME)中的原色和倍数之间的关系相同,但是它涉及的过程却截然不同。与传统的倍数预测和减法不同,在EPSI中,未知原色是大规模反演过程的参数。缺点是计算时间长,涉及大约100-200个SRME流程。为了提高多次去除的准确性和效率,提出了一种混合SRME + EPSI,它利用了SRME和EPSI方法学的最强之处。看起来,最终结果比单独的SRME或EPSI算法要好,并且计算时间限于10-20个SRME流程的等效时间。

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