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Relative source time functions of seismic events at the Rudna copper mine, Poland: estimation of inversion uncertainties

机译:波兰Rudna铜矿地震事件的相对震源时间函数:反演不确定性的估计

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摘要

The relative source time function (RSTF) inversion uncertainty assessment was performed for two small, mining-induced seismic events (M-W =2.9 and 3.0) that occurred at Rudna copper mine in Poland. The seismograms of selected events were recorded by the seismic net work composed of over 60, short-period, vertical seismometers, recording ground velocity, located in the distance ranging from 400 m up to 8 km from their hypocenters. The RSTFs were calculated for each seismic station independently, using the empirical Green's function technique. The pseudospectral approximation of the sought RSTF by a finite sum of Gaussian kernel functions was used and the inverse problem was solved with the adaptive simulated annealing algorithm. Both methods improved the stability of the deconvolution procedure and physical correctness of the final solution in comparison to the classical deconvolution methods. To estimate the inversion uncertainties, classical Markov-chain Monte-Carlo techniques were used. The uncertainty analysis allows for improved selection of a priori data to the following inversion for kinematic rupture process.
机译:对波兰Rudna铜矿发生的两次小型采矿诱发的地震事件(M-W分别为2.9和3.0)进行了相对震源时间函数(RSTF)反演不确定性评估。选定事件的地震图由地震网络记录,地震网络由60多个短周期垂直地震仪组成,记录了地速,位于距震源400 m至8 km的范围内。使用经验格林函数技术分别为每个地震台计算了RSTF。使用了有限高斯核函数求和的RSTF的伪谱近似,并通过自适应模拟退火算法解决了反问题。与经典的反卷积方法相比,这两种方法都提高了反卷积过程的稳定性和最终解决方案的物理正确性。为了估计反演的不确定性,使用了经典的马尔可夫链蒙特卡罗技术。不确定性分析可以改进对先验数据的选择,然后进行运动破裂过程的后续反演。

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