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地震 ›› 2000, Vol. 20 ›› Issue (z1): 18-27.

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海城、岫岩地震序列非线性结构特征及判定前震序列的时间结构变异诊断法

罗灼礼1, 王伟君2, 陈凌3   

  1. 1.中国地震局, 北京 100036;
    2.中国地震局分析预报中心 ,北京 100036;
    3.中国地震局地球物理研究所 ,北京100081
  • 收稿日期:2000-05-30 修回日期:2000-06-19 出版日期:2000-09-30 发布日期:2022-09-23
  • 作者简介:罗灼礼 (1941-) ,男 ,广东大埔人 ,研究员, 1997年博士生导师 ,主要从事地震学、地震预报等研究。

The time-frame coefficient method to diagnose nonlinear characteristics of earthquake sequences in Haicheng-Xiuyan Region, Liaoning Province

LUO Zhuo-li1, WANG Wei-jun2, CHEN Lin3   

  1. 1. Science and Technology Committee, CSB, Beijing 100036, China;
    2. Center for Analysis and Prediction, CSB, Beijing 100036, China;
    3. Institute of Geophysics, CSB, Beijing 100081, China
  • Received:2000-05-30 Revised:2000-06-19 Online:2000-09-30 Published:2022-09-23

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摘要： 运用地震序列非线性关系和时间结构变异系数, 对辽宁海城、岫岩从 1975年以来 4次显著地震 (1975, MS 7. 3; 1978, MS 5. 9; 1988, ML 3. 7震群; 1999, MS 5. 6)的地震序列进行了对比研究 ,结果表明, 前震序列、余震序列及一般小震群, 在时间结构特征上有明显的差异。前震序列时间变异系数 δ≈ 1、余震 δ> 1。 只有当该区发震系统的行为具有足够的随机性时 ,才会以主震和余震方式进入新的能量大释放状态和阶段 ,这是一个复杂系统时间不可逆过程的特殊结构和基本特征 ,因此提出了前震序列时间结构变异诊断方法。同时 ,文中还对其他一些地区不同类型地震活动状态和地震序列的非线性时间结构关系进行了类似的分析和讨论。

关键词: 时间变异系数, 非线性, 地震序列和震情诊断, 地震预测

Abstract: Using the nonlinear relations and the time-frame coefficient of earthquake sequence, the four earthquake sequences (1975, MS 7. 3; 1978, MS 5. 9; 1988 ML 3. 7 swarm; 1999, MS 5. 6) occurred in the Haicheng-Xiuyan region of Liaoning Province since 1975 are studied. The result indicates that there are evident differences among the foreshocks sequence, aftershock sequence and small normal swarms in the time-frame characteristics and the time-frame variation coefficient (δ) . δ≈1 for a foreshocks sequence,and δ 1 for an aftershock. A new state, a stage of large energy release with a main earthquake and many aftershocks co me about when the behavior of the earthquake generation system of a region is of enough randomness, which is the special frame and foundational nonlinear features of a complex system with the irreversible process. A time-frame variation coefficient method to diagnose the forerunner earthquake sequence is consequently proposed. A similar study of different types of seismic activity states and nonlinear time-frame relation earthquake sequences that occurred in other regions are also presented.

Key words: Time frame variation coefficient, Nonlinearity, Earthquake sequence and situation diagnosis, Earthquake prediction

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