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Optimization of Filter Length in Least Squares Adaptive Subtraction Using a Model Selection Approach
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 81st EAGE Conference and Exhibition 2019, Jun 2019, Volume 2019, p.1 - 5
Abstract
Summary
This paper proposes a data driven method to select the optimal filter length in least square adaptive subtraction. The method comes from the field of statistical modeling, where it is used to find the optimal size of a %parametric model that fits an observed set of data. The paper establishes the similarity between under-fitting and residual multiples, over-fitting and and primary leakage. The proposed method is tested on real data and shows benefit in cases where a constant filter length is known to produce a compromised demultiple result.
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