Improvement and application of ESPAC method based on cross-correlation spectrum adaptive segmental fitting technology

IF 2.1 4区 地球科学
Mingming Wu, Lianghong Zhang, Hesheng Zeng, Zhixian Gui, Guixi Liu
{"title":"Improvement and application of ESPAC method based on cross-correlation spectrum adaptive segmental fitting technology","authors":"Mingming Wu,&nbsp;Lianghong Zhang,&nbsp;Hesheng Zeng,&nbsp;Zhixian Gui,&nbsp;Guixi Liu","doi":"10.1007/s11600-026-01893-6","DOIUrl":null,"url":null,"abstract":"<div><p>As a convenient and efficient passive-source geophysical method, microtremor exploration is widely used. The traditional Extended Spatial Autocorrelation (ESPAC) method tends to generate high-frequency cross-artifacts with sparse arrays. Although the Modified ESPAC (M-ESPAC) method can eliminate these artifacts, its inversion depth (less than twice the array radius) is much lower than ESPAC’s 3–5 times. To resolve this contradiction, this paper proposes a Further Modified ESPAC (FM-ESPAC) method based on cross-correlation spectrum adaptive segmental fitting. First, it defines the first intersection frequency <i>f</i><sub>01</sub> between the cross-correlation curve and the frequency axis as the adaptive segmentation threshold. Then, adaptive segmental fitting is performed using <i>f</i><sub>01</sub>: the low-frequency band (<i>f</i> ≤ <i>f</i><sub>01</sub>) adopts ESPAC’s zero-order Bessel function J<sub>0</sub> fitting to retain low-frequency responses, while the high-frequency band (<i>f</i> &gt; <i>f</i><sub>01</sub>) uses M-ESPAC’s analytic signal and first-kind zero-order Hankel function H<sub>0</sub><sup>(1)</sup> fitting to eliminate cross-artifacts. Finally, the array-averaged dispersion spectrum is obtained via superposition and normalization. Simulation experiments (triangular/linear arrays) and practical cases (Enshi geothermal exploration, Antarctic ice sheet detection) verify that FM-ESPAC not only eliminates high-frequency cross-artifacts but also inherits ESPAC’s low-frequency information to ensure inversion depth, showing significant advantages in the case of sparse arrays and insufficient spatial sampling.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Geophysica","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s11600-026-01893-6","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

As a convenient and efficient passive-source geophysical method, microtremor exploration is widely used. The traditional Extended Spatial Autocorrelation (ESPAC) method tends to generate high-frequency cross-artifacts with sparse arrays. Although the Modified ESPAC (M-ESPAC) method can eliminate these artifacts, its inversion depth (less than twice the array radius) is much lower than ESPAC’s 3–5 times. To resolve this contradiction, this paper proposes a Further Modified ESPAC (FM-ESPAC) method based on cross-correlation spectrum adaptive segmental fitting. First, it defines the first intersection frequency f01 between the cross-correlation curve and the frequency axis as the adaptive segmentation threshold. Then, adaptive segmental fitting is performed using f01: the low-frequency band (f ≤ f01) adopts ESPAC’s zero-order Bessel function J0 fitting to retain low-frequency responses, while the high-frequency band (f > f01) uses M-ESPAC’s analytic signal and first-kind zero-order Hankel function H0(1) fitting to eliminate cross-artifacts. Finally, the array-averaged dispersion spectrum is obtained via superposition and normalization. Simulation experiments (triangular/linear arrays) and practical cases (Enshi geothermal exploration, Antarctic ice sheet detection) verify that FM-ESPAC not only eliminates high-frequency cross-artifacts but also inherits ESPAC’s low-frequency information to ensure inversion depth, showing significant advantages in the case of sparse arrays and insufficient spatial sampling.

Abstract Image

基于互相关谱自适应分段拟合技术的ESPAC方法改进与应用
微震勘探作为一种方便、高效的被动源地球物理方法,得到了广泛的应用。传统的扩展空间自相关(ESPAC)方法容易产生具有稀疏阵列的高频交叉伪影。虽然改进ESPAC (M-ESPAC)方法可以消除这些伪像,但其反演深度(小于阵列半径的2倍)远低于ESPAC的3-5倍。为了解决这一矛盾,本文提出了一种基于互相关谱自适应分段拟合的进一步改进ESPAC (FM-ESPAC)方法。首先,定义互相关曲线与频率轴的第一个相交频率f01作为自适应分割阈值。然后利用f01进行自适应分段拟合:低频(f≤f01)采用ESPAC的零阶贝塞尔函数J0拟合保留低频响应,高频(f > f01)采用M-ESPAC的解析信号和第一类零阶汉克尔函数H0(1)拟合消除交叉伪像。最后,通过叠加和归一化得到阵列平均色散谱。模拟实验(三角形/线性阵列)和实际案例(恩施地热勘探、南极冰盖探测)验证,FM-ESPAC不仅消除了高频交叉伪像,而且继承了ESPAC的低频信息,保证了反演深度,在阵列稀疏、空间采样不足的情况下具有显著优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Acta Geophysica
Acta Geophysica GEOCHEMISTRY & GEOPHYSICS-
CiteScore
3.80
自引率
13.00%
发文量
251
期刊介绍: Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.
×
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:604180095
Book学术官方微信
小红书