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首页> 外文期刊>Pure and Applied Geophysics >Statistical Features of the 2010 Beni-Ilmane, Algeria, Aftershock Sequence
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Statistical Features of the 2010 Beni-Ilmane, Algeria, Aftershock Sequence

机译：2010年Beni-Ilmane，阿尔及利亚，余震序列的统计特征

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Abstract The aftershock sequence of the 2010 Beni-Ilmane ( M ~(W)5.5) earthquake is studied in depth to analyze the spatial and temporal variability of seismicity parameters of the relationships modeling the sequence. The b value of the frequency–magnitude distribution is examined rigorously. A threshold magnitude of completeness equal to 2.1, using the maximum curvature procedure or the changing point algorithm, and a b value equal to 0.96?±?0.03 have been obtained for the entire sequence. Two clusters have been identified and characterized by their faulting type, exhibiting b values equal to 0.99?±?0.05 and 1.04?±?0.05. Additionally, the temporal decay of the aftershock sequence was examined using a stochastic point process. The analysis was done through the restricted epidemic-type aftershock sequence (RETAS) stochastic model, which allows the possibility to recognize the prevailing clustering pattern of the relaxation process in the examined area. The analysis selected the epidemic-type aftershock sequence (ETAS) model to offer the most appropriate description of the temporal distribution, which presumes that all events in the sequence can cause secondary aftershocks. Finally, the fractal dimensions are estimated using the integral correlation. The obtained D ~(2)values are 2.15?±?0.01, 2.23?±?0.01 and 2.17?±?0.02 for the entire sequence, and for the first and second cluster, respectively. An analysis of the temporal evolution of the fractal dimensions D ~(?2), D ~(0), D ~(2)and the spectral slope has been also performed to derive and characterize the different clusters included in the sequence.
机译：摘要深入研究了2010 Beni-Ilmane（M〜（W）5.5）地震的余震序列，以分析建模序列的关系的地震性参数的空间和时间变化。严格检查频率幅度分布的B值。完整性等于2.1的阈值大小，使用最大曲率过程或改变点算法，并且对于整个序列已经获得了等于0.96°的B值。通过其故障型识别并表征了两种簇，表现出等于0.99的B值±0.05和1.04？±0.05。另外，使用随机点处理检查余震序列的时间衰减。通过限制的疫情型余震序列（RetAs）随机模型来完成分析，这允许识别在检查区域中识别弛豫过程的主要聚类图案。分析选择了流行病型余震序列（ETAS）模型，以提供时间分布的最合适的描述，这假定序列中的所有事件都可能导致次要余量。最后，使用整体相关性估计分形尺寸。所获得的D〜（2）值为2.15？±0.01,2.23？±0.01和2.17？±0.02，以及第一和第二簇。还进行了分形尺寸D〜（α2），D〜（0），D〜（2）和光谱斜率的时间演变的分析，以导出和表征序列中包含的不同簇。

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