Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform

Abstract

Magnetotelluric (MT) data acquired during September-October I 1994, in northern Canada, were strongly influenced by non-uniform source field contributions from the aurora1 electrojet, and especially by intense auroral episodes. The largest effect on the estimate of the magnetotellwic impedance tensor elements was during intervals of highest magnetic activit.y, which primarily correlated with high auroral activity and wa::; observoo during local night time. In comparison, during the day the effect on the normal magneto telluric impedance tensor response was usually, but not always, small. A robust controlled-leverage processing algorithm was applied to these data in an attempt to extract the stable lLniform field estima.tes of the impedance. The differences between nonrobust and robust processing of the entire data set is compared to that obtained after dividing the time series into daytime and nighttime segments. The nonrobust estima.te using all data is controlled by the nocturnal data, which are, in turn. dominated by non-uniform source effects. However, nonrobust processing of only the daytime data fails to recover a useful result. There is little difference between the robust response for the eutire Wld daytime data. provided that the fruction of auroral activity is not large, i.e., in excess of half of the available data series. In addition, examination of the time-dependence of the response functions shows that the strongest bias is observed during the initial quarter of an auroral event.

The electrical resistivity of Canada’s lithosphere and correlation with other parameters: contributions from Lithoprobe and other programmes

“…The former used the property that the vertical magnetic field tipper response is far more sensitive to non-uniform fields than is the MT response, whereas the latter approach was more mathematical in nature using a frequency domain principal component method. • The application of high-frequency AMT for mineral exploration was advanced by Lithoprobe scientists on a number of fronts (Garcia and Jones 2000), from instrumentation (Phoenix Geophysics' V5A and MTU-5A developments), understanding of AMT source fields (Garcia and Jones 2002a), acquisition methodologies (Jones and McNeice 2002), including a proposed novel telluric-telluric-magnetotelluric (TT-MT) method , down-mine measurements (Queralt et al 2007), specialized wavelet processing (Garcia and Jones 2008), distortion of controlled-source AMT data , 3-D distortion analysis (Garcia and Jones 2002c), and implementation and interpretation (Zhang and Chouteau 1992;Livelybrooks et al 1996;Chouteau et al 1997;Jones and Garcia 2006), including a cautionary tale resulting from regional current systems (Jones and Garcia 2003b). AMT is now being used extensively for mineral exploration, with over 30 000 sites measured over the last decade in Canada alone, and particularly 3-D modelling and inversion are being employed.…”

Using empirical mode decomposition to process marine magnetotelluric data

“…Wavelet analysis is a different approach to handle non‐stationary data and has become a standard data analysis method (e.g. Alexandrescu et al 1995; Suto et al 2006; Garcia & Jones 2008). However, since wavelet analysis gives time‐frequency information over time‐variable windows, a wavelet basis that is suited for all signals in the time‐series has to be selected before processing.…”

New application of wavelets in magnetotelluric data processing: reducing impedance bias

“…In the low-frequency band of extremely low-frequency (ELF) waves, sferics consist of a high-amplitude To analyze ELF waves using the CWT, we have chosen the Cauchy wavelet. Most of the previous work on MT methods with wavelets was based on the Morlet wavelet stemming from its properties of good resolution in terms of both the time and frequency (Zhang and Paulson 1997;Garcia and Jones 2008). However, the shape of the ELF wave (Fig.…”

“…Geomagnetic pulsation signals contain several oscillations so they are very localized in the time and frequency domains simultaneously. Thus, like previous authors (e.g., Zhang and Paulson 1997;Garcia and Jones 2008 for atmospherics signals), we have chosen the Morlet wavelet, which represents the best compromise between the time and frequency resolution. Use of the Cauchy wavelet would be hazardous because of its low-frequency resolution.…”