利用方差分量估计的地震同震滑动分布反演

提出了基于方差分量估计的地震同震滑动分布反演方法,该方法不仅可以确定不同数据集的相对权重,而且还能得到平滑因子的值,突破了方差分量估计方法仅用于各类数据定权的实际应用范围。模拟算例验证了此方法的有效性,从解的概率后验密度分布分析来看,方差分量估计方法得到的结果是线性和非线性混合方法反演结果的一个解。用方差分量估计方法反演了Bam地震同震滑动分布,并与线性非线性混合方法反演的结果进行了对比分析。两种方法得到的Bam地震断层滑动分布之间的空间互相关系数为0.999 9,地震同震的最大滑动量相同,都为3.04 m;其深度仅有微小区别,前者为4.50 km,后者为4.47 km;平均滑动量前者为0.714 m,后者为0.718 m。但前者反演计算用时227 s,后者却达到1.5×10⁶ s,约17 d,前者仅为后者的1/6 608。结果表明,本文方法相对于线性和非线性混合方法具有计算简单、计算量小和计算效率高的优点。

Coseismic Slip Distribution Inversion Method Based on the Variance Component Estimation

We propose a coseismic slip distribution inversion method based on variance component estimation (VCE), this method not only determines the weight of different data sets but also can get the smoothing factor value. To illustrate and validate this inversion method, we conducted inversions on synthetic data sets. Based on the Bayesian framework and according to the posterior probability density distribution of the unknown parameters, the proposed solution is comparted to one of the linear-non-linear inversion solutions to further demonstrate the use of the proposed method. We conduct inversions on the 2003 Bam earthquake with the proposed method and linear-non-linear inversion method, the spatial cross correlation of the resulting slip distribution was about 0.999, the depth of the max slip of the both were 3.04 m and the depth had little difference, the former was 4.50 km, the latter was 4.47 km. The mean slip in the former was 0.714 m, the latter was 0.718 m. But the inversion time of the former was 227 s, and only about 1/8 000 of the later (reaching 1.5×10⁶ s, about 17 d).These results show that the VCE method is effective and faster than the linear-non-linear inversion method.