IASPEI - Picture Gallery

IUGG XXIV General Assembly July 2-13, 2007 Perugia, Italy
(S) - IASPEI - International Association of Seismology and Physics of the Earth's
Interior
JSS009 Poster presentation 2063
Wavelets in the analysis of seismoelectromagnetic signals
Mr. George Hloupis
Laboratory of Geophysics & Seismology Technological Educational Institute of Crete
George Hloupis, Filippos Vallianatos, John Makris, Dimos Triantis
The study of electromagnetic field recordings before the occurrence of a significant seismic event has
been proposed by many researchers as a possible indication of an earthquake precursor. In a
considerable set of cases, along with these proposals, a theoretical model has been developed in order
to explain suasively the observed recordings. There is no arguing that what all the prementioned efforts
tried to reveal is a set of signals than can be proved that were generated from an earthquake
generation mechanism. On this direction, the initial and crucial step is the revealing of the candidate
earthquake precursor (CEP) from the whole recording which is a two-step process. Primary, there must
be an identification of a CEP signal using well-known automated methods and possible knowledge
databases. Eventually the isolation method of the CEP signal must be able to separate it from acquaint
periodic events (daily and seasonal variations) as well as independent non-seismic events (i.e. industrial
noise). Without knowing the exact earthquake generation mechanism we cannot allegate that we can
identify CEP signals based on their characteristics. An alternative approach is to identify CEP signals
based on pattern recognition methods.The purpose of this study is to propose a pattern recognition
scheme for CEP signals based on wavelet analysis. Wavelets has been widely used in various studies in
order to derive non-stationarities and hidden irregularities from underlying signals. At the same time
their intrinsic ability to split the signal in different scales provides an analysis frame where we can
rapidly identify and isolate the signals under interest. The proposed method uses electric and magnetic
recordings from an 1Hz acquisition system. The recorded signals after appropriate preprocessing they
analyzed using wavelets and classified according to their scale-to-scale behavior. The recording period
separated into three sub-periods: One consisting the Kythira (36.21 North, 23.41 East) earthquake
and two without any significant seismic activity. From the results we can exclude some interesting
indicators of CEP signals primarily in electrical field recordings.
Keywords: wavelet, electromagnetic precursors