Inversion of a velocity model using artificial neural networks

被引:29
作者
Moya, Aaron [1 ,2 ]
Irikura, Kojiro [2 ,3 ]
机构
[1] Univ Costa Rica, Lab Ingn Sism, Inst Invest Ingn, San Jose, Costa Rica
[2] Disaster Prevent Res Inst, Kyoto 6110011, Japan
[3] Aichi Inst Technol Toyota, Disaster Prevent Res Ctr, Aichi 4700392, Japan
关键词
Velocity model; Simulation; Neural networks; Synthetic waveforms; Inversion; Algorithm; EARTHQUAKE; CALIFORNIA; JAPAN;
D O I
10.1016/j.cageo.2009.08.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present a velocity model inversion approach using artificial neural networks (NN). We selected four aftershocks from the 2000 Tottori, Japan, earthquake located around station SMNH01 in order to determine a 1D nearby underground velocity model. An NN was trained independently for each earthquake-station profile. We generated many velocity models and computed their corresponding synthetic waveforms. The waveforms were presented to NN as input. Training consisted in associating each waveform to the corresponding velocity model. Once trained, the actual observed records of the four events were presented to the network to predict their velocity models. In that way, four 1D profiles were obtained individually for each of the events. Each model was tested by computing the synthetic waveforms for other events recorded at SMNH01 and at two other nearby stations: TTR007 and TTR009. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1474 / 1483
页数:10
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