{"title":"基于机器学习的日本海沟构造地震检测与定位","authors":"Kodai Sagae, Masayuki Kano, Suguru Yabe, Takahiko Uchide","doi":"10.1029/2025JB031348","DOIUrl":null,"url":null,"abstract":"<p>Shallow tectonic tremors near trenches have been detected due to the advancement of offshore observation networks. Traditionally, tremors were identified by cross-correlating envelope waveforms between seismic stations. However, this method has struggled to differentiate tremor signals from earthquakes and sometimes missed tremors during active tremor episodes. Addressing these challenges is crucial for monitoring tremors in seismically active regions, such as the Japan Trench. We developed a machine learning-based tremor monitoring system using a dense network of cable-type ocean-bottom seismometers (S-net) in the Japan Trench. The system analyzed continuous waveforms recorded from August 2016 to August 2024. Our analysis detected seven times more tremors than the previous study using envelope cross-correlation. The newly identified tremors expanded the known spatial distribution of tremor activity, both along the strike and dip, revealing a complementary spatial relationship between tremors and earthquakes. Additionally, our catalog improved temporal resolution, uncovering spatiotemporal patterns of tremors synchronized with slow slip events. Seismic energy rates of tremors were calculated, showing spatial variations along the strike and dip, with higher rates near asperities of large earthquakes. A positive correlation between energy rates and recurrence intervals was found, suggesting that these spatial variations reflect frictional heterogeneities on plate boundaries. The enhanced spatiotemporal resolution of our tremor catalog provides valuable insights into the relationship between slow and fast earthquakes.</p>","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"130 6","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025JB031348","citationCount":"0","resultStr":"{\"title\":\"Machine Learning-Based Detection and Localization of Tectonic Tremors in the Japan Trench\",\"authors\":\"Kodai Sagae, Masayuki Kano, Suguru Yabe, Takahiko Uchide\",\"doi\":\"10.1029/2025JB031348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Shallow tectonic tremors near trenches have been detected due to the advancement of offshore observation networks. Traditionally, tremors were identified by cross-correlating envelope waveforms between seismic stations. However, this method has struggled to differentiate tremor signals from earthquakes and sometimes missed tremors during active tremor episodes. Addressing these challenges is crucial for monitoring tremors in seismically active regions, such as the Japan Trench. We developed a machine learning-based tremor monitoring system using a dense network of cable-type ocean-bottom seismometers (S-net) in the Japan Trench. The system analyzed continuous waveforms recorded from August 2016 to August 2024. Our analysis detected seven times more tremors than the previous study using envelope cross-correlation. The newly identified tremors expanded the known spatial distribution of tremor activity, both along the strike and dip, revealing a complementary spatial relationship between tremors and earthquakes. Additionally, our catalog improved temporal resolution, uncovering spatiotemporal patterns of tremors synchronized with slow slip events. Seismic energy rates of tremors were calculated, showing spatial variations along the strike and dip, with higher rates near asperities of large earthquakes. A positive correlation between energy rates and recurrence intervals was found, suggesting that these spatial variations reflect frictional heterogeneities on plate boundaries. The enhanced spatiotemporal resolution of our tremor catalog provides valuable insights into the relationship between slow and fast earthquakes.</p>\",\"PeriodicalId\":15864,\"journal\":{\"name\":\"Journal of Geophysical Research: Solid Earth\",\"volume\":\"130 6\",\"pages\":\"\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025JB031348\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geophysical Research: Solid Earth\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2025JB031348\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Solid Earth","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2025JB031348","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
Machine Learning-Based Detection and Localization of Tectonic Tremors in the Japan Trench
Shallow tectonic tremors near trenches have been detected due to the advancement of offshore observation networks. Traditionally, tremors were identified by cross-correlating envelope waveforms between seismic stations. However, this method has struggled to differentiate tremor signals from earthquakes and sometimes missed tremors during active tremor episodes. Addressing these challenges is crucial for monitoring tremors in seismically active regions, such as the Japan Trench. We developed a machine learning-based tremor monitoring system using a dense network of cable-type ocean-bottom seismometers (S-net) in the Japan Trench. The system analyzed continuous waveforms recorded from August 2016 to August 2024. Our analysis detected seven times more tremors than the previous study using envelope cross-correlation. The newly identified tremors expanded the known spatial distribution of tremor activity, both along the strike and dip, revealing a complementary spatial relationship between tremors and earthquakes. Additionally, our catalog improved temporal resolution, uncovering spatiotemporal patterns of tremors synchronized with slow slip events. Seismic energy rates of tremors were calculated, showing spatial variations along the strike and dip, with higher rates near asperities of large earthquakes. A positive correlation between energy rates and recurrence intervals was found, suggesting that these spatial variations reflect frictional heterogeneities on plate boundaries. The enhanced spatiotemporal resolution of our tremor catalog provides valuable insights into the relationship between slow and fast earthquakes.
期刊介绍:
The Journal of Geophysical Research: Solid Earth serves as the premier publication for the breadth of solid Earth geophysics including (in alphabetical order): electromagnetic methods; exploration geophysics; geodesy and gravity; geodynamics, rheology, and plate kinematics; geomagnetism and paleomagnetism; hydrogeophysics; Instruments, techniques, and models; solid Earth interactions with the cryosphere, atmosphere, oceans, and climate; marine geology and geophysics; natural and anthropogenic hazards; near surface geophysics; petrology, geochemistry, and mineralogy; planet Earth physics and chemistry; rock mechanics and deformation; seismology; tectonophysics; and volcanology.
JGR: Solid Earth has long distinguished itself as the venue for publication of Research Articles backed solidly by data and as well as presenting theoretical and numerical developments with broad applications. Research Articles published in JGR: Solid Earth have had long-term impacts in their fields.
JGR: Solid Earth provides a venue for special issues and special themes based on conferences, workshops, and community initiatives. JGR: Solid Earth also publishes Commentaries on research and emerging trends in the field; these are commissioned by the editors, and suggestion are welcome.