中国石油大学学报（自然科学版）2026，Vol.50Issue(1)：76-83,8.DOI:10.3969/j.issn.1673-5005.2026.01.008
基于二维经验模态分解的稀疏反演弱信号增强方法
Weak signal enhancement via sparse inversion of bidimensional empirical mode decomposition
摘要
Abstract
Seismic exploration in western regions characterized by complex surface and subsurface conditions faces persistent challenges,including weak deep seismic signals,insufficient resolution of target layers,and difficulties in structural imaging and characterization.There is an urgent need for a processing workflow specifically designed for prestack gathers in western datasets to improve the signal-to-noise ratio.This paper proposes a weak-signal enhancement method based on two-dimen-sional empirical mode decomposition combined with compressed sensing.The method performs high-dimensional adaptive de-composition of seismic gathers from western exploration areas,generating physically constrained bidimensional intrinsic mode functions(BIMFs)that preliminarily separate weak signals from strong background noise.The BIMFs are then grouped,and different sparse inversion parameters are applied to each group to suppress noise while preserving weak signal components.Finally,the processed groups are recombined to reconstruct seismic data with enhanced weak reflections.Application to real seismic data from western China demonstrates the effectiveness of the proposed method.The results show that the approach a-daptively decomposes seismic data according to the physical propagation characteristics of seismic waves,effectively avoiding damage to deep weak reflection signals caused by excessive processing parameters.关键词
压缩感知/二维经验模态分解/弱信号增强/信噪比/深层地震数据Key words
compressed sensing/bidimensional empirical mode decomposition/weak signal enhancement/signal to noise ra-tio/deep scismic data分类
天文与地球科学引用本文复制引用
陈飞旭,李振春,王伟奇..基于二维经验模态分解的稀疏反演弱信号增强方法[J].中国石油大学学报（自然科学版）,2026,50(1):76-83,8.基金项目
国家自然科学基金项目(42074133,42574163) （42074133,42574163）
