Paper Info
Title
Automatic Seismic Signal Detection via Record Segmentation
Abstract
The automatic seismic signal detection constitutes a very interesting and challenging task. The main difficulty in solving this problem is attributed to the fact that both the statistical properties of seismic noise and the characteristics of the recorded events are in general unknown. In this paper, by exploiting the particular nature of the signals we are treating, as well as a number of very interesting properties possessed by exchangeable random variables, we formulate the problem at hand as a record segmentation one and propose the use of two functionally linked test statistics for its efficient and robust solution, in a two-step procedure. By following this approach, we succeed not only in detecting a seismic wave arrival, but also in identifying the entire interval occupied by the signal, while minimizing the number of the required parameters. The performance of the proposed technique is confirmed by a series of experiments, both in synthetic and real seismic data sets.
Year
DOI
Venue
2015
10.1109/TGRS.2014.2386255
Geoscience and Remote Sensing, IEEE Transactions  
Keywords
Field
DocType
geophysical signal processing,geophysical techniques,seismic waves,automatic seismic signal detection,exchangeable random variables,real seismic data sets,record segmentation,seismic noise statistical properties,seismic wave arrival,signal nature,two-step procedure,detection algorithms,seismic signal processing,time of arrival estimation,robustness,testing,random variables,signal detection,estimation,noise
Seismic inversion,Detection theory,Robustness (computer science),Seismic noise,Seismic wave,Artificial intelligence,Statistical hypothesis testing,Computer vision,Pattern recognition,Segmentation,Synthetic seismogram,Statistics,Mathematics
Journal
Volume
Issue
ISSN
53
7
0196-2892
Citations 
PageRank 
References 
3
0.47
2
Authors
2
Name
Order
Citations
PageRank
Erion-Vasilis M. Pikoulis143.21
Emmanouil Z. Psarakis2985.36