基于机器学习的日本海沟构造地震检测与定位

IF 4.1 2区 地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS
Kodai Sagae, Masayuki Kano, Suguru Yabe, Takahiko Uchide
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引用次数: 0

摘要

由于近海观测网络的进步,已经探测到海沟附近的浅层构造震动。传统上,地震是通过地震台站之间的相互关联包络波形来识别的。然而,这种方法很难从地震中区分震颤信号,有时会在活动震颤发作期间遗漏震颤。解决这些挑战对于监测地震活跃地区(如日本海沟)的地震至关重要。我们在日本海沟开发了一种基于机器学习的地震监测系统,该系统使用密集的电缆式海底地震仪网络(S-net)。该系统分析了2016年8月至2024年8月记录的连续波形。我们的分析检测到的震动比以前使用包络相互关联的研究多七倍。新发现的地震扩展了已知的地震活动的空间分布,包括沿走向和倾角,揭示了地震和地震之间的互补空间关系。此外,我们的目录提高了时间分辨率,揭示了与慢滑事件同步的地震的时空模式。计算了地震的能量率,显示了沿走向和倾角的空间变化,在大地震的陡岩附近的能量率较高。能量率与重复周期呈正相关,表明这些空间变化反映了板块边界上的摩擦非均质性。我们的地震目录提高了时空分辨率,为慢震和快震之间的关系提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Machine Learning-Based Detection and Localization of Tectonic Tremors in the Japan Trench

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.

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来源期刊
Journal of Geophysical Research: Solid Earth
Journal of Geophysical Research: Solid Earth Earth and Planetary Sciences-Geophysics
CiteScore
7.50
自引率
15.40%
发文量
559
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.
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