Automatic Event Identification From Tectonic Earthquakes with Modified Akaike Information Criterion (mAIC)

International Conference on Science, Infrastructure Technology and Regional Development

自然科学（总论）

Suhendi, Cahli^1 ; Sudibyo, Maria R.P.^1 ; Erlangga, I.F.^1 ; Arbad, Arliandy P.^1

Geophysical Engineering, Institut Teknologi Sumatera, South Lampung, Indonesia^1

关键词: Advanced analysis;    Akaike information criterion;    Characteristic functions;    Event identification;    Low signal-to-noise ratio;    Seismic signals;    Seismic velocities;    Tectonic earthquakes;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/258/1/012037/pdf
DOI  :  10.1088/1755-1315/258/1/012037

学科分类：自然科学（综合）

来源: IOP

【 摘 要 】

It is difficult to identify P- and S-waves arrival time from the recorded seismograms with low Signal - to - Noise Ratio (SNR) because the onset is not always clearly observed. However, the arrival time of P and S-waves are important for the advanced analysis, such as for seismic event localization and seismic velocity tomography. In this paper, we employ Akaike Information Criterion (AIC) with the new characteristic function (CF) so-called mAIC, that is proposed by Hendriana et al. (2018) to detect P- and S - waves onset accurately and automatically from the denoised seismic signal of tectonic earthquake events in Sunda Strait. The mAIC was proposed to overcome the window-dependence of AIC function from continuous seismogram by computing AIC in a translatable window. The results show that mAIC successfully determine the first onsite of P- and S-wave for the denoised seismogram data.