Dual-scattering elastic least-squares reverse time migration

IF 4.2 2区 地球科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mingqian Wang , Huixing Zhang , Bingshou He
{"title":"Dual-scattering elastic least-squares reverse time migration","authors":"Mingqian Wang ,&nbsp;Huixing Zhang ,&nbsp;Bingshou He","doi":"10.1016/j.cageo.2025.105854","DOIUrl":null,"url":null,"abstract":"<div><div>Elastic least-squares reverse time migration (ELSRTM) can enhance imaging resolution and interpret multicomponent seismic data. However, traditional ELSRTM only considers primary scattered waves and cannot accommodate secondary scattered waves in the observed records. This limitation leads to inadequate imaging of steeply dipping and complex structures, where secondary scattered waves are present. To address this issue, we propose dual-scattering elastic least-squares reverse time migration (DS-ELSRTM). We construct the objective function of DS-ELSRTM under the second-order Born approximation and derive its gradient, forming a corresponding computational algorithm and implementation steps. Additionally, we introduce improved DS-ELSRTM strategies to address the weak amplitude matching of secondary scattered waves and the non-stationary gradient issue that arises during the nonlinear process of DS-ELSRTM. By comparing the imaging results of DS-ELSRTM and conventional ELSRTM in numerical experiments with the vertical fault model and Marmousi model, it is demonstrated that the DS-ELSRTM method has advantages in imaging steeply dipping structures and complex geological structures. DS-ELSRTM can produce higher-precision images than conventional ELSRTM.</div></div>","PeriodicalId":55221,"journal":{"name":"Computers & Geosciences","volume":"196 ","pages":"Article 105854"},"PeriodicalIF":4.2000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Geosciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0098300425000044","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Elastic least-squares reverse time migration (ELSRTM) can enhance imaging resolution and interpret multicomponent seismic data. However, traditional ELSRTM only considers primary scattered waves and cannot accommodate secondary scattered waves in the observed records. This limitation leads to inadequate imaging of steeply dipping and complex structures, where secondary scattered waves are present. To address this issue, we propose dual-scattering elastic least-squares reverse time migration (DS-ELSRTM). We construct the objective function of DS-ELSRTM under the second-order Born approximation and derive its gradient, forming a corresponding computational algorithm and implementation steps. Additionally, we introduce improved DS-ELSRTM strategies to address the weak amplitude matching of secondary scattered waves and the non-stationary gradient issue that arises during the nonlinear process of DS-ELSRTM. By comparing the imaging results of DS-ELSRTM and conventional ELSRTM in numerical experiments with the vertical fault model and Marmousi model, it is demonstrated that the DS-ELSRTM method has advantages in imaging steeply dipping structures and complex geological structures. DS-ELSRTM can produce higher-precision images than conventional ELSRTM.
求助全文
约1分钟内获得全文 求助全文
来源期刊
Computers & Geosciences
Computers & Geosciences 地学-地球科学综合
CiteScore
9.30
自引率
6.80%
发文量
164
审稿时长
3.4 months
期刊介绍: Computers & Geosciences publishes high impact, original research at the interface between Computer Sciences and Geosciences. Publications should apply modern computer science paradigms, whether computational or informatics-based, to address problems in the geosciences.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信