Kim Keehoon, Rodgers Arthur, Wright Melissa
Geophysical Monitoring Program, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
Mission Support and Test Services, Limited Liability Company (LLC), Las Vegas, Nevada 89030, USA.
J Acoust Soc Am. 2018 Dec;144(6):3351. doi: 10.1121/1.5082549.
While the acoustic waveform inversion method is increasingly used in geophysical acoustics to constrain source parameters, the inversion results are often provided without any uncertainty analysis. This study presents a probabilistic representation for acoustic waveform inversion and method to evaluate the inversion uncertainty using ground-truth data. probability distribution of source estimate is described by waveform misfit covariance and the variance of acoustic source model. The probabilistic framework is applied to local explosion infrasound to estimate the yields of explosions and uncertainty. Estimated yields showed overall good agreement with the true yields (less than 25% errors). The uncertainty of the estimated yield is represented by the sum of the waveform inversion uncertainty and source model uncertainty. It is shown that the yield uncertainty attributed to local infrasound inversion (within 10 km) is as small as the uncertainty caused by 10% prediction errors in the acoustic source model. These results indicate that the acoustic source model uncertainty should also be considered for accurate yield estimation and that local infrasound can be a valuable tool to understand the magnitude of the source uncertainty.
虽然声波形反演方法在地球物理声学中越来越多地用于约束源参数，但反演结果往往在没有任何不确定性分析的情况下给出。本研究提出了一种声波形反演的概率表示方法以及使用真实数据评估反演不确定性的方法。源估计的概率分布由波形失配协方差和声源模型的方差描述。该概率框架应用于局部爆炸次声，以估计爆炸产量和不确定性。估计产量与真实产量总体上具有良好的一致性（误差小于25%）。估计产量的不确定性由波形反演不确定性和声源模型不确定性之和表示。结果表明，局部次声反演（在10公里范围内）引起的产量不确定性与声源模型中10%预测误差引起的不确定性一样小。这些结果表明，为了准确估计产量，还应考虑声源模型的不确定性，并且局部次声可以成为了解源不确定性大小的有价值工具。
