Fully probabilistic seismic source inversion - Part 1: Efficient parameterisation
Fully probabilistic seismic source inversion - Part 1: Efficient parameterisation
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DOI：
10.5194/se-5-1055-2014
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发表时间：
2013-07
期刊：
影响因子：
3.4
通讯作者：
S. Stähler;K. Sigloch
中科院分区：
文献类型：
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作者：
S. Stähler;K. Sigloch
抽象的。震源反演是地震学中的一个非线性问题，不仅对地震参数本身，而且对其不确定性的估计都具有重要的实际意义。概率源反演(贝叶斯推理)非常适合于这一挑战，前提是参数空间可以选择得足够小，以使贝叶斯抽样在计算上可行。我们提出了一个地震震源机制概率推断框架(PRISM)，它利用以前的非贝叶斯反演信息，有效地对地震深度、矩张量和震源时间函数进行参数和采样。源时间函数被表示为少量经验正交函数的加权和，这些经验正交函数通过主成分分析从1000个源时间函数(STF)的目录中得到。我们使用基于观测波形和预测波形之间互相关失配的似然模型。由此得到的解集合提供了震源参数的全部不确定性和协方差信息，并允许将这些震源不确定性传播到用于地震层析成像的旅行时间估计中。计算工作量如此之大，使得根据远震宽带波形对地震机制和震源时间函数进行常规的全球估计是可行的。
Abstract. Seismic source inversion is a non-linear problem in seismology where not just the earthquake parameters themselves but also estimates of their uncertainties are of great practical importance. Probabilistic source inversion (Bayesian inference) is very adapted to this challenge, provided that the parameter space can be chosen small enough to make Bayesian sampling computationally feasible. We propose a framework for PRobabilistic Inference of Seismic source Mechanisms (PRISM) that parameterises and samples earthquake depth, moment tensor, and source time function efficiently by using information from previous non-Bayesian inversions. The source time function is expressed as a weighted sum of a small number of empirical orthogonal functions, which were derived from a catalogue of >1000 source time functions (STFs) by a principal component analysis. We use a likelihood model based on the cross-correlation misfit between observed and predicted waveforms. The resulting ensemble of solutions provides full uncertainty and covariance information for the source parameters, and permits propagating these source uncertainties into travel time estimates used for seismic tomography. The computational effort is such that routine, global estimation of earthquake mechanisms and source time functions from teleseismic broadband waveforms is feasible.