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SENSITIVITY ANALYSIS OF THE NETWORK CONFIGURATION TO SEISMIC SOURCES LOCATION USING TIME REVERSAL IMAGING WITH PEAK AVERAGE POWER RATIO (PAPR) PARAMETER.

Anna Franczyk

First published: 2018-06-20https://doi.org/10.5593/sgem2018/2.2/s08.050View metrics

Abstract

The accuracy of location of seismic sources using time reversal imaging techniques is considered in this article. The location procedure is performed using backpropagation of the recorded and reversed seismic signal from receiver throughout assumed geological model. The new imaging parameters, peak average power ratio (PAPR) coefficient is used for efficient visualization of the backpropagation of the seismic energy. The detection of seismic wave focusing was carried out on the basis of the high PAPR parameter values computed after backpropagation of seismic waves. Several numerical computation for the different network configurations were performed in order to conduct the sensitivity analysis of the network configuration to seismic sources location. Parameters that describe geometry of the seismic network such as number of sensors of the receiver network, the angle of filling and the distance from source point to the receiver point are considered in this work. Results presented in this paper were obtained by numerical algorithm of wave source location based on the acoustic wave equation implemented using finite difference method.

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Title
SENSITIVITY ANALYSIS OF THE NETWORK CONFIGURATION TO SEISMIC SOURCES LOCATION USING TIME REVERSAL IMAGING WITH PEAK AVERAGE POWER RATIO (PAPR) PARAMETER.
Authors
Anna Franczyk
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 18th International Multidisciplinary Scientific GeoConference SGEM2018, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2018
Pages
395-402
SWS Citekey
Franczyk20188395402
ISSN
1314-2704
ISBN
978-619-7408-40-9
Language
en
Publication type
Conference Paper
Keywords
numerical modellingwave equationsensitivity analysisMorris Screaning
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