基于EMD的地震数据速度谱优化方法
Optimization method for seismic data velocity spectrum based on empirical mode decomposition
刘玉萍 1张衡 1张宝金 1顾元1
作者信息
- 1. 自然资源部海底矿产资源重点实验室,中国地质调查局广州海洋地质调查局,广东广州 511458;天然气水合物勘查开发国家工程研究中心,广东广州 511458
- 折叠
摘要
地震波在地层中的传播速度可间接反映地下岩性及地质构造特征,速度的提取与分析影响地震数据处理和解释全过程.目前,速度谱分辨率低,导致拾取的速度不准确,构建的速度模型精度经常不能满足复杂地质构造的地震成像要求.为此,提出基于经验模态分解(EMD)的地震数据速度谱优化方法.该方法是一种频移处理技术,能有效提高地震数据低频端能量的信噪比.首先,基于Hilbert变换获得地震数据的瞬时振幅;其次,对瞬时振幅进行EMD;然后,筛选分解后的本征模量(IMF),选择具有有益表达速度谱信息的本征模态模量;最后,构建新的速度谱数据.经过优化后的地震数据频谱分辨率更高,有效频带向低频端移动.实验测试和实际资料处理结果表明,所提方法能有效扩大速度谱拾取的寻优区间,提高速度分析准确性,提升地震资料成像品质.该方法在成果数据处理和速度谱优化方面具有广泛的应用价值.
Abstract
The propagation velocity of seismic waves in geological formations can indirectly reflect the subsur-face lithology and geological structural features.The extraction and analysis of velocity greatly influence the en-tire process of seismic data processing and interpretation.Currently,the low resolution of velocity spectra leads to inaccurate velocity picking,and the accuracy of constructed velocity models often fails to meet the require-ments for imaging complex geological structures.To address this issue,an optimization method for seismic data velocity spectrum based on Empirical Mode Decomposition(EMD)is proposed.This method is a fre-quency shift processing technique that effectively improves the signal-to-noise ratio of low-frequency energy in seismic data.Firstly,the instantaneous amplitude of seismic data is obtained based on Hilbert transform.Se-condly,the instantaneous amplitude is decomposed using EMD.Then,the intrinsic mode functions(IMFs)obtained from the decomposition are screened,and the ones containing useful information of velocity spectrum are selected.Finally,a new velocity spectrum is constructed.The optimized seismic data spectrum has a higher resolution and the effective frequency band is shifted towards the low-frequency end.Experimental tests and practical data processing results show that the proposed method effectively expands the optimized interval for velocity spectrum picking,improves the accuracy of velocity analysis,and enhances the imaging quality of seismic data.This method has wide application value in seismic data processing and velocity spectrum optimi-zation.
关键词
Hilbert变换/经验模态分解(EMD)/速度谱/频移/地震数据Key words
Hilbert transform/empirical mode decomposition(EMD)/velocity spectrum/frequency shift/seismic data引用本文复制引用
基金项目
中国地调局项目(DD20201118)
&&(DD20240090)
国家自然科学基金(92262304)
出版年
2024
国家科技期刊平台
NSTL
万方数据