Wavelet analysis as a tool to characteriseand remove environmental noisefrom self-potential time series

D. Chianese, G. Colangelo, M. D'Emilio, M. Lanfredi, V. Lapenna, M. Ragosta, M. F. Macchiato

Abstract


Multiresolution wavelet analysis of self-potential signals and rainfall levels is performed for extracting fluctuations
in electrical signals, which might be addressed to meteorological variability. In the time-scale domain of the wavelet transform, rain data are used as markers to single out those wavelet coefficients of the electric signal which can be considered relevant to the environmental disturbance. Then these coefficients are filtered out
and the signal is recovered by anti-transforming the retained coefficients. Such methodological approach might
be applied to characterise unwanted environmental noise. It also can be considered as a practical technique to
remove noise that can hamper the correct assessment and use of electrical techniques for the monitoring of geophysical phenomena.

Keywords


self-potential signals;wavelet analysis

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References


DOI: https://doi.org/10.4401/ag-3257
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Published by INGV, Istituto Nazionale di Geofisica e Vulcanologia - ISSN: 2037-416X