地球物理学进展 ›› 2018, Vol. 33 ›› Issue (5): 1871-1878.doi: 10.6038/pg2018BB0344

• 固体地球物理及空间物理学(大气、行星、地球动力学、重磁电及地震学、地热学) • 上一篇    下一篇

地震预测方法Ⅷ:地震活动性

赵永红(),徐安东,张琼()   

  1. 北京大学地球物理系,北京 100871
  • 收稿日期:2017-11-20 修回日期:2018-08-29 出版日期:2018-10-20 发布日期:2019-01-11
  • 通讯作者: 张琼 E-mail:zhaoyh@pku.edu.cn;zhangqiong0503@pku.edu.cn
  • 作者简介:赵永红,博士, 教授,1982年毕业于北京大学地质系,主要从事地球动力学、实验岩石力学的教学和研究工作.
  • 基金资助:
    中国博士后科学基金资助项目(2018M630028);国家自然科学基金项目(41274094);国家自然科学基金项目(40821062);国家自然科学基金项目(40872133)

Earthquake prediction Ⅷ: seismic activity method

ZHAO Yong-Hong(),XU An-dong,ZHANG Qiong()   

  1. Department of Geophysics,Peking University,Beijing 100871,China
  • Received:2017-11-20 Revised:2018-08-29 Online:2018-10-20 Published:2019-01-11
  • Contact: Qiong ZHANG E-mail:zhaoyh@pku.edu.cn;zhangqiong0503@pku.edu.cn

摘要:

地震活动性方法是地震预测方法之一.该方法的原理是通过研究一定区域内某个时期的地震活动特性,包括地震的时间、空间分布特点和地震频度、地震强度的变化,利用相关的统计方法来处理历史资料中记载的或当前地震观测系统测定的地震发生的时间、空间位置和强度等基本参数以及这些参数之间的相互关系,从而达到预测未来地震发生的时间、地点和震级的目的.地震活动性测震法根据所采用统计方法的不同可分为许多类.本文综述了其中具有代表性的三种方法,即图像信息学PI算法、地震活动加速指数AI算法和地震动态空区法.对这三种地震活动性测震法的测震原理、特点以及研究进展进行概述,对应用前景给予分析,并对相关震例进行研究和总结.结果表明:地震活动性测震法对研究区域地震记录的完整性要求较高,可以预测的地震信息和预测精度非常有限.

关键词: 地震预测, 地震活动性, PI算法, AI算法, 地震动态空区法

Abstract:

Seismic activity method is one of the earthquake prediction methods. The principle is to use relevant statistical methods dealing with the basic parameters and the relationship among these parameters. Through studying seismic activity characteristics such as frequency of earthquakes and the change of earthquake magnitude in a given region for a certain period, we may predict the three elements of the future earthquake. The three elements are the time, location and magnitude of the earthquake. The seismic activity method included many kinds according to the different statistical methods. This paper summarizes three representative methods, namely, picture informatics algorithm, seismic acceleration index algorithm and seismic dynamic gap method. The picture informatics algorithm also called the PI algorithm. The PI algorithm estimates the probability of future earthquakes on the medium and long term scale by analyzing the fluctuation of seismic activity. In practical applications, the input of the PI algorithm is the regional earthquake catalogue, and the output is the relative probability growth of the strong earthquake or the “hot spot” distribution. The seismic acceleration index algorithm also called the AI algorithm. According to the seismicity law in the past, before the great earthquake, small earthquakes may rapidly increase in epicenter region and neighboring areas. The AI is a parameter that can give a quantitative estimate of the relative enhancement or attenuation of seismicity before moderate and large earthquakes. The seismic dynamic gap method holds that the gaps between strong earthquake sources is the most likely region for future strong earthquakes. By summarizing the principle, characteristic, research progress, related cases and analyzing the application prospect of these three methods, it is not difficult for us to analyze that these methods require higher integrity of seismic records in the study area. Besides, it is very limited to predict the seismic information by these methods and its accuracy is not high.

Key words: earthquake prediction, seismic activity, Picture Informatics algorithm method (PI algorithm), Acceleration Index algorithm method (AI algorithm), seismic dynamic gap method

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