A New First Arrival Pickup Algorithm Based On Information Theory for the Seismic Signals

DOI

10.2991/meici-17.2017.47How to use a DOI?

Keywords

Seismic Data; First Arrivals; Pickup; Information Theory; Mutual Information

Abstract

For the seismic data with low SNRs, the first arrival automatic picking method is very important but difficult. In the paper, we proposed a new method based on the mutual information in information theory. The mutual information between signals and noises is zeros, thus random noises have less effects on first arrivals pickup. The paper compares the principle of STA/LTA, AIC, fractal dimension of three kinds with the proposed method for seismic data first-break picking method, and at the same times, the paper presents a detailed test and verification of the simulation data, and compares first-break picking accuracy and efficiency of the three algorithms through actual data with different S/N ratios. The results show that for the data with high S/N ratio, first break picking accuracy of these four methods is relatively high. When SNR decreases, first-arrival time that the proposed method picks has higher precision and good noise immunity. However, mutual information based method has lower efficiency and is limited by algorithm principle. it is difficult to separately pick first breaks for fractal dimension and AIC method. So it is a very good method to identify seismic events and determine preliminarily the time range of first breaks by the proposed method.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - MingYue Zhai
PY  - 2017/10
DA  - 2017/10
TI  - A New First Arrival Pickup Algorithm Based On Information Theory for the Seismic Signals
BT  - Proceedings of the 7th International Conference on Management, Education, Information and Control (MEICI 2017)
PB  - Atlantis Press
SP  - 218
EP  - 223
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-17.2017.47
DO  - 10.2991/meici-17.2017.47
ID  - Zhai2017/10
ER  -