门多西诺三交界处附近不同但相邻的地震序列:2021 年 12 月 20 日威力 6.1 级和 6.0 级 Petrolia 地震,以及 2022 年 12 月 20 日威力 6.4 级 Ferndale 地震

Clara E. Yoon, David R. Shelly
{"title":"门多西诺三交界处附近不同但相邻的地震序列:2021 年 12 月 20 日威力 6.1 级和 6.0 级 Petrolia 地震,以及 2022 年 12 月 20 日威力 6.4 级 Ferndale 地震","authors":"Clara E. Yoon, David R. Shelly","doi":"10.1785/0320230053","DOIUrl":null,"url":null,"abstract":"\n Two earthquake sequences occurred a year apart at the Mendocino Triple Junction in northern California: first the 20 December 2021 Mw 6.1 and 6.0 Petrolia sequence, then the 20 December 2022 Mw 6.4 Ferndale sequence. To delineate active faults and understand the relationship between these sequences, we applied an automated deep-learning workflow to create enhanced and relocated earthquake catalogs for both the sequences. The enhanced catalog newly identified more than 14,000 M 0–2 earthquakes and also found 852 of 860 already cataloged events. We found that deep-learning and template-matching approaches complement each other to improve catalog completeness because deep learning finds more M 0–2 background seismicity, whereas template-matching finds the smallest M < 0 events near already known events. The enhanced catalog revealed that the 2021 Petrolia and 2022 Ferndale sequences were distinct in space and time, but adjacent in space. Though both the sequences happened in the downgoing Gorda slab, the shallower Ferndale sequence ruptured within the uppermost slab near the subduction interface, while the onshore Petrolia sequence occurred deeper in the mantle. Deep-learning-enhanced earthquake catalogs could help monitor evolving earthquake sequences, identify detailed seismogenic fault structures, and understand space–time variations in earthquake rupture and sequence behavior in a complex tectonic setting.","PeriodicalId":273018,"journal":{"name":"The Seismic Record","volume":"36 16","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distinct Yet Adjacent Earthquake Sequences near the Mendocino Triple Junction: 20 December 2021 Mw 6.1 and 6.0 Petrolia, and 20 December 2022 Mw 6.4 Ferndale\",\"authors\":\"Clara E. Yoon, David R. Shelly\",\"doi\":\"10.1785/0320230053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Two earthquake sequences occurred a year apart at the Mendocino Triple Junction in northern California: first the 20 December 2021 Mw 6.1 and 6.0 Petrolia sequence, then the 20 December 2022 Mw 6.4 Ferndale sequence. To delineate active faults and understand the relationship between these sequences, we applied an automated deep-learning workflow to create enhanced and relocated earthquake catalogs for both the sequences. The enhanced catalog newly identified more than 14,000 M 0–2 earthquakes and also found 852 of 860 already cataloged events. We found that deep-learning and template-matching approaches complement each other to improve catalog completeness because deep learning finds more M 0–2 background seismicity, whereas template-matching finds the smallest M < 0 events near already known events. The enhanced catalog revealed that the 2021 Petrolia and 2022 Ferndale sequences were distinct in space and time, but adjacent in space. Though both the sequences happened in the downgoing Gorda slab, the shallower Ferndale sequence ruptured within the uppermost slab near the subduction interface, while the onshore Petrolia sequence occurred deeper in the mantle. Deep-learning-enhanced earthquake catalogs could help monitor evolving earthquake sequences, identify detailed seismogenic fault structures, and understand space–time variations in earthquake rupture and sequence behavior in a complex tectonic setting.\",\"PeriodicalId\":273018,\"journal\":{\"name\":\"The Seismic Record\",\"volume\":\"36 16\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Seismic Record\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1785/0320230053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Seismic Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1785/0320230053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

加利福尼亚州北部门多西诺三交界处相隔一年发生了两次地震序列:第一次是 2021 年 12 月 20 日发生的 Mw 6.1 和 6.0 Petrolia 地震序列,第二次是 2022 年 12 月 20 日发生的 Mw 6.4 Ferndale 地震序列。为了划定活动断层并了解这些序列之间的关系,我们采用了自动深度学习工作流程,为这两个序列创建了增强和重新定位的地震目录。增强型目录新识别了超过 14,000 个 M 0-2 地震,还发现了 860 个已编入目录事件中的 852 个。我们发现,深度学习和模板匹配方法在提高目录完整性方面互为补充,因为深度学习发现了更多的 M 0-2 背景地震,而模板匹配则发现了已知地震附近最小的 M < 0 事件。增强后的目录显示,2021 年 Petrolia 地震序列和 2022 年 Ferndale 地震序列在空间和时间上各不相同,但在空间上相邻。虽然这两个地震序列都发生在下行的戈尔达板块中,但较浅的费恩代尔地震序列发生在俯冲界面附近的最上层板块中,而陆上的彼得罗利亚地震序列发生在地幔更深处。深度学习增强型地震编录有助于监测不断演化的地震序列,识别详细的发震断层结构,了解复杂构造环境中地震破裂和序列行为的时空变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distinct Yet Adjacent Earthquake Sequences near the Mendocino Triple Junction: 20 December 2021 Mw 6.1 and 6.0 Petrolia, and 20 December 2022 Mw 6.4 Ferndale
Two earthquake sequences occurred a year apart at the Mendocino Triple Junction in northern California: first the 20 December 2021 Mw 6.1 and 6.0 Petrolia sequence, then the 20 December 2022 Mw 6.4 Ferndale sequence. To delineate active faults and understand the relationship between these sequences, we applied an automated deep-learning workflow to create enhanced and relocated earthquake catalogs for both the sequences. The enhanced catalog newly identified more than 14,000 M 0–2 earthquakes and also found 852 of 860 already cataloged events. We found that deep-learning and template-matching approaches complement each other to improve catalog completeness because deep learning finds more M 0–2 background seismicity, whereas template-matching finds the smallest M < 0 events near already known events. The enhanced catalog revealed that the 2021 Petrolia and 2022 Ferndale sequences were distinct in space and time, but adjacent in space. Though both the sequences happened in the downgoing Gorda slab, the shallower Ferndale sequence ruptured within the uppermost slab near the subduction interface, while the onshore Petrolia sequence occurred deeper in the mantle. Deep-learning-enhanced earthquake catalogs could help monitor evolving earthquake sequences, identify detailed seismogenic fault structures, and understand space–time variations in earthquake rupture and sequence behavior in a complex tectonic setting.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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