基于NEWUOA的CRS叠加成像技术

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关键词：CRS叠加成像技术;三参数优化;NEWUOA；无导数优化；Nelder-Mead单纯形算法doi：10.13278/j.cnki.jjuese.20250271 中图分类号：P631.4 文献标志码：A

Abstract： The common reflection surface （CRS） stack imaging technique enhances the signal-tonoise ratio of seismic data by utilizing information from adjacent common midpoint gathers，making it a key technology for processing seismic data with low signal-to-noise ratios and low fold coverage. Whether using classical stepwise search or synchronous global search methods for CRS three-parameter optimization，a local optimization algorithm is ultimately required to enhance accuracy. The traditional Nelder-Mead simplex algorithm， with its simple search approach， suffers from relatively low computational efficiency. This paper adopts a derivative-free optimization algorithm called NEWUOA （new unconstrained optimization algorithm） as the precision enhancement method for CRS stacking. This algorithm dynamically constructs a quadratic interpolation model，employs a trust region iterative strategy，and utilizes curvature information of the objective function to improve computational efficiency. The algorithm was tested using a layered undulating model and the Marmousi2 model. The results show that for the simple layered undulating model and the complex Marmousi2 model，the NEWUOA generally outperformed or equaled the Nelder-Mead simplex algorithm in improving coherence values， with a computational efciency increase of approximately 48% and 45% ， respectively，compared to the Nelder-Mead simplex algorithm. This demonstrates that the NEWUOA can significantly enhance computational eficiency while maintaining the accuracy of CRS stack optimization，making it well-suited as a computational tool for precision refinement.

Key words： CRS stack imaging technique; three-parameter optimization; NEWUOA; derivativefree optimization;Nelder-Mead simplex algorithm

0 引言

地震数据处理是地震勘探中的重要环节，其目标是通过反褶积、叠加、偏移等技术手段提升地震数据的信噪比与分辨率。（剩余16095字）