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地震 ›› 2012, Vol. 32 ›› Issue (3): 1-14.

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地震活动性正常与异常的群体概率特征及其在地震预测中的应用以汶川地震为例

罗灼礼, 王伟君   

  1. 中国地震局地震预测研究所, 北京 100036
  • 收稿日期:2012-02-09 修回日期:2012-04-24 发布日期:2021-08-19
  • 作者简介:罗灼礼(1941-), 男, 广东大埔人, 研究员, 主要从事地震学、 地震预报等研究。

Statistical Group Properties of Seismic Activities in Normal and Abnormal Conditions and Their Applications to Earthquake Prediction a Case Study of the 2008 Wenchuan Earthquake

LUO Zhuo-li, WANG Wei-jun   

  1. Institute of Earthquake Science, CEA, Beijing 100036, China
  • Received:2012-02-09 Revised:2012-04-24 Published:2021-08-19

摘要: 地震事件一般具有离散性, 即它们的发生和转移具有一定的时间和空间间隔。 当孕震系统处于平衡(或正常)状态时, 系统状态变量X(这里以地震活动性为例)的时间序列概率分布表现为单峰型(如泊松分布); 其时间间隔(或等候时间)Δt分布可用负指数分布来描述。 当系统处于非平衡(或异常)状态时, X的概率分布表现为双峰型或多峰型, 其时间间隔Δt(或空间间隔ΔS)可采用幂函数关系来描述。 可以计算X的1~4阶矩统计参数识别X的概率分布性质, 进一步判断系统所处的状态。 根据这个思路, 本文尝试针对地震活动性的群体概率特征, 探索研究地震活动系统时间和空间结构的演变以及正常和异常状态的辨别, 并将这些方法应用于2008年汶川8.0级地震及其余震趋势和强余震预测实践。

关键词: 地震活动状态, 群体概率特征, 地震预测, 汶川地震

Abstract: Earthquake events have discrete properties in space and time during their occurrences and migration. When the seismogenic system is in tranquil(or normal) state, the probability distribution for time sequence of variance X ( i.e. seismicity in this paper) will show single-peak distribution such as Poisson distribution; the time intervals for two events(or waiting time) Δt can be described by negative exponent function. While the system enters into non-tranquil (or abnormal) state, the probability distribution for time sequence of X shows two-peaks or multiple-peak distribution; their waiting time can be described by power function. The distribution properties of X can be discriminated by calculating 1 to 4 order of moment estimators, which will further help to identify the current state of the system. According to this approach, we try to investigate the evolutions of time and space structure in seismogenic system and identify its state. We also apply these methods to the prediction practice of strong aftershocks of the 2008 Wenchuan M8.0 earthquake sequence.

Key words: Seismic Activity, Statistical Group Properties, Earthquake prediction, Wenchuan earthquake

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