判别小震群序列类型的新方法研究
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摘要
小震群地震活动经常发生,对其可能类型的快速判别,即对正在活动过程中的小震群,究竟是“大震”的前震序列,还是并不伴有大震发生的一般性小震群的快速判别,对于减轻地震灾害和维护社会稳定具有重要的现实意义。近几十年来围绕小震群序列类型的判别所开展的研究,取得了不少的进展,各种方法在地震预测的实际应用中都显示了一定的效能,但多数方法都是统计性的,依其所作的判别难免存在不同程度的不确定性。因此,有必要多途径研究探索物理含义较为明确、结果更为有效的,新的判别方法。
已有理论与震例研究表明,与一般性小震群相比,前震序列的震源机制更趋于一致。鉴于小地震的震源机制不易求解,本研究引进谱振幅相关分析的方法来研究小地震震源机制是否相似的问题,以探讨小震群序列类型判定的可能性。其总体的科学思路是将震群中每个地震的观测位移谱扣除掉传播路径效应、台站场地效应等因素后,得到谱振幅,通过计算谱振幅的相关系数来描述震源机制是否相似的问题。谱振幅相关系数接近于1,表明震群中诸小地震震源机制较相似,判断为前震序列的可能性较大;反之,诸小地震震源机制相似程度较低,判断为一般小震群的可能性较大。
作为对理论推演的检验,选择三个之后伴有“大震”发生和三个之后不伴有大震发生的小震群,分别计算震群序列的谱振幅相关系数。结果表明,1999年11月29日辽宁岫岩5.4级地震前、2001年4月12日云南施甸5.9级地震前和2001年10月27日云南永胜6.0级地震前在未来“大震”震源区或其边缘发生的小震群,谱振幅相关系数不论是平均值还是最小值都在0.85以上,接近于1;而云南2002年1月漾濞、2003年11 ~12月洱源、2005年5 ~6月宾川三个之后不伴有“大震”发生的一般小震群,不论是平均值,还是最大值都在0.80以下(平均值都小于0.70),显著小于1。实测结果和理论推演相吻合,意味着谱振幅相关分析是判别小震群可能类型的一种物理含义较明确,效能较好的新方法。另外,在上述计算过程中,本研究还反演得到了辽宁岫岩及云南西北部地区的P波与S波Q值,以及所用台站的场地效应。
本研究用“传统”的参数统计分析方法对上述六个小震群作了检验,结果显示,多数出现误判。研究表明,就本文收集的资料而言,在一定理论模型指导之下的地震学参量(谱振幅相关系数法)对震群类型识别的效能,要比传统的统计分析方法预测效能高,说明地震波资料携带的孕震信息应该比地震目录的信息丰富。本研究最后指出,只要小震群被周围若干数字化地震台站所记录,即可测定小震群序列的谱振幅相关系数,因此谱振幅相关分析法具有推广应用价值,值得进一步深入研究。
The small earthquake swarms often occur , judging the types quickly or determining whether there will be larger earthquakes following is very important both in the hazard mitigation and social stability. In recent decades, much progress has been made in judging the types of the small earthquake swarms. Various methods were applied in practical efforts of earthquake prediction. But most of them are statistical. The uncertainties of judging the types of earthquake swarms are unavoidable. So it is necessary to broadly explore new methods that have clearer physical meaning and more effect results.
The theoretical and experimental studies show that the focal mechanisms of foreshock sequence are more consistent than those of ordinary small earthquake swarm. Due to the intricacy of calculating the focal mechanism of small earthquakes, we use correlation coefficient of spectral amplitude to study the consistency of focal mechanism of small earthquakes, so as to analyze the possibility of determining the types of small earthquake swarms. The overall scientific thought is that after deducting the propagation path effects, the site effects and some other factors from the spectral of the observed displacement, we get the spectral amplitude of every earthquake in the swarms. We try to study whether the focal mechanisms are similar through analysing the correlation coefficients of source spectral amplitude. If the correlation coefficient is closer to 1.0, it indicates that the focal mechanisms of the small earthquakes are more consistent and the small earthquake swarms are more likely to be the foreshock sequences. On the contrary, the focal mechanisms are less consistent and the small earthquake swarms are more likely to be ordinary small earthquake swarms.
As the cases study to the theoretical deduction, we choose three foreshock sequences and three ordinary small earthquake swarms to calculate their correlation coefficients of spectral amplitude respectively. The results show that the mean and minimal correlation coefficient of spectral amplitude of small earthquake swarms are all above 0.85, closer to 1.0 before the Xiuyan Ms5.4 earthquake in 1999, Shidian Ms5.9 earthquake in 2001 and the Yongsheng Ms6.0 earthquake in 2001; while the mean and maximal correlation coefficients of the ordinary small earthquake swarms are all below 0.8, significantly less than 1.0 in Yangbi swarm(2002), Eryuan swarm (2003) and Binchuan swarm (2005) after which no large earthquake took place. The theoretical deductions coincide with the actual observational results, which implies that the correlation analysis of spectral amplitude is a new method that has more clear physical implication and higher performance. Besides, in the computational process mentioned above, this study also gets the QP, QS of the Xiuyan region and the northwest area of Yunnan Province, and the site effects of the station used in the paper.
We also study the six small earthquake swarms by means of the traditionally statistical parameter. The results show that most of them are miscarriages. It implies that the prediction performances of the new method put forward in this paper based on some earthquake physical models is more effective than the traditional method of statistical parameters in connection with this six earthquake swarms. It also suggests that seismic data has more seismogenic information than earthquake catalog. According to the study in the paper, it is very obvious that the correlation coefficients of spectral amplitude of the small earthquake swarms can be measured as long as there are some digital seismic stations around. So the correlation analysis of spectral amplitude is worthy of further research.
已有理论与震例研究表明,与一般性小震群相比,前震序列的震源机制更趋于一致。鉴于小地震的震源机制不易求解,本研究引进谱振幅相关分析的方法来研究小地震震源机制是否相似的问题,以探讨小震群序列类型判定的可能性。其总体的科学思路是将震群中每个地震的观测位移谱扣除掉传播路径效应、台站场地效应等因素后,得到谱振幅,通过计算谱振幅的相关系数来描述震源机制是否相似的问题。谱振幅相关系数接近于1,表明震群中诸小地震震源机制较相似,判断为前震序列的可能性较大;反之,诸小地震震源机制相似程度较低,判断为一般小震群的可能性较大。
作为对理论推演的检验,选择三个之后伴有“大震”发生和三个之后不伴有大震发生的小震群,分别计算震群序列的谱振幅相关系数。结果表明,1999年11月29日辽宁岫岩5.4级地震前、2001年4月12日云南施甸5.9级地震前和2001年10月27日云南永胜6.0级地震前在未来“大震”震源区或其边缘发生的小震群,谱振幅相关系数不论是平均值还是最小值都在0.85以上,接近于1;而云南2002年1月漾濞、2003年11 ~12月洱源、2005年5 ~6月宾川三个之后不伴有“大震”发生的一般小震群,不论是平均值,还是最大值都在0.80以下(平均值都小于0.70),显著小于1。实测结果和理论推演相吻合,意味着谱振幅相关分析是判别小震群可能类型的一种物理含义较明确,效能较好的新方法。另外,在上述计算过程中,本研究还反演得到了辽宁岫岩及云南西北部地区的P波与S波Q值,以及所用台站的场地效应。
本研究用“传统”的参数统计分析方法对上述六个小震群作了检验,结果显示,多数出现误判。研究表明,就本文收集的资料而言,在一定理论模型指导之下的地震学参量(谱振幅相关系数法)对震群类型识别的效能,要比传统的统计分析方法预测效能高,说明地震波资料携带的孕震信息应该比地震目录的信息丰富。本研究最后指出,只要小震群被周围若干数字化地震台站所记录,即可测定小震群序列的谱振幅相关系数,因此谱振幅相关分析法具有推广应用价值,值得进一步深入研究。
The small earthquake swarms often occur , judging the types quickly or determining whether there will be larger earthquakes following is very important both in the hazard mitigation and social stability. In recent decades, much progress has been made in judging the types of the small earthquake swarms. Various methods were applied in practical efforts of earthquake prediction. But most of them are statistical. The uncertainties of judging the types of earthquake swarms are unavoidable. So it is necessary to broadly explore new methods that have clearer physical meaning and more effect results.
The theoretical and experimental studies show that the focal mechanisms of foreshock sequence are more consistent than those of ordinary small earthquake swarm. Due to the intricacy of calculating the focal mechanism of small earthquakes, we use correlation coefficient of spectral amplitude to study the consistency of focal mechanism of small earthquakes, so as to analyze the possibility of determining the types of small earthquake swarms. The overall scientific thought is that after deducting the propagation path effects, the site effects and some other factors from the spectral of the observed displacement, we get the spectral amplitude of every earthquake in the swarms. We try to study whether the focal mechanisms are similar through analysing the correlation coefficients of source spectral amplitude. If the correlation coefficient is closer to 1.0, it indicates that the focal mechanisms of the small earthquakes are more consistent and the small earthquake swarms are more likely to be the foreshock sequences. On the contrary, the focal mechanisms are less consistent and the small earthquake swarms are more likely to be ordinary small earthquake swarms.
As the cases study to the theoretical deduction, we choose three foreshock sequences and three ordinary small earthquake swarms to calculate their correlation coefficients of spectral amplitude respectively. The results show that the mean and minimal correlation coefficient of spectral amplitude of small earthquake swarms are all above 0.85, closer to 1.0 before the Xiuyan Ms5.4 earthquake in 1999, Shidian Ms5.9 earthquake in 2001 and the Yongsheng Ms6.0 earthquake in 2001; while the mean and maximal correlation coefficients of the ordinary small earthquake swarms are all below 0.8, significantly less than 1.0 in Yangbi swarm(2002), Eryuan swarm (2003) and Binchuan swarm (2005) after which no large earthquake took place. The theoretical deductions coincide with the actual observational results, which implies that the correlation analysis of spectral amplitude is a new method that has more clear physical implication and higher performance. Besides, in the computational process mentioned above, this study also gets the QP, QS of the Xiuyan region and the northwest area of Yunnan Province, and the site effects of the station used in the paper.
We also study the six small earthquake swarms by means of the traditionally statistical parameter. The results show that most of them are miscarriages. It implies that the prediction performances of the new method put forward in this paper based on some earthquake physical models is more effective than the traditional method of statistical parameters in connection with this six earthquake swarms. It also suggests that seismic data has more seismogenic information than earthquake catalog. According to the study in the paper, it is very obvious that the correlation coefficients of spectral amplitude of the small earthquake swarms can be measured as long as there are some digital seismic stations around. So the correlation analysis of spectral amplitude is worthy of further research.
引文
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