一个新的目录和对2022年亚得里亚海上地震序列的洞察,使用基于机器学习的程序
1Istituto Nazionale di Geofisica e Vulcanologia, 00143 Rome, Italy.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
一种新的机器学习方法生成了2022/2023年亚得里亚海海上序列的详细地震目录. 这份目录增强了对低级地震和断层系统活动的理解.
科学领域:
- 地质物理学 地质物理学
- 地震学 地震学
- 机器学习 机器学习
背景情况:
- 亚得里亚海离岸地区是地震活跃的,之前的研究表明与亚得里亚海断层系统有联系.
- 描述地震序列,特别是低强度事件,对于理解构造过程至关重要.
研究的目的:
- 开发和应用基于机器学习的程序,以创建2022/2023年亚得里亚海海上序列的全面地震目录.
- 改善该地区低级地震的检测和表征.
主要方法:
- 利用机器学习从连续波形数据中自动选择和关联相位.
- 处理了来自意大利40个国家地震网络站和5个SISMIKO网络站的数据.
- 分析了3个月的地震活动 (2022年11月1日 - 2023年1月31日).
主要成果:
- 创建了一个大小为ML 0.4或更大的2780次地震的目录.
- 提供了有关较低级地震事件的增强信息.
- 结果支持将地震序列归因于亚得里亚海断层系统,特别是科尼利亚断层推力.
结论:
- 基于机器学习的程序显示了创建非常完整的地震目录的巨大潜力.
- 这项研究为亚得里亚海沿岸的地震序列及其因果结构提供了新的见解.
- 这种方法即使在具有挑战性的地震监测场景中,即使具有有限的中心距离和近地线覆盖范围,也有效.
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