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WAVELET ANALYSIS OF MAGNETOTELLURIC DATA
SUNJAY and MANAS BANERJEE
GEOPHYSICS,BHU,VARANASI 221005 ,INDIA
[email protected]
ABSTRACT
Geophysical data are nonstationary and multiscale in character. The magnetotelluric method has improved
significantly hydrocarbon exploration in regions where seismic exploration is difficult,Seismic reflection is
a highly effective tool for imaging complexstructures in hydrocarbon exploration. However, in certain
scenarios, seismic data quality can be severely diminished. For example,near-surface carbonates and
volcanic rocks can degrade the qualityof seismic data through static effects. Problems can also arise in
overthrust belts, where high-velocity rocks are emplaced over a low-velocity layer. In these situations,
other geophysical methods, such as gravity, magnetics, and magnetotellurics, can be used to provide
alternative or complementary information about the subsurface structure.Tellus(Goddess of the Earth Mater
or Terra Mater (Mother Earth) A telluric current or Earth current, is an electric current which moves
underground.Magnetotellurics (MT) is an electromagnetic geophysical method for inferring the earth's
subsurface electrical conductivity from measurements of natural geomagnetic and geoelectric field
variation at the Earth's surface. Investigation depth ranges from 300 m below ground by recording higher
frequencies down to 10,000 m or deeper with long-period soundings.For audio-frequency magnetotelluric
surveys where the signals are lightning-stroke transients, the conventional Fourier transform method often
fails to produce a high quality impedance tensor. An alternative approach is to use the wavelet transform
method which is capable of localizing target information simultaneously in both the temporal and
frequency domains. Unlike Fourier analysis that yields an average amplitude and phase, the wavelet
transform produces an instantaneous estimate of the amplitude and phase of a signal. Morlet wavelet is
used to transform and analyze audio-frequency magnetotelluric data. With the Morlet wavelet, the
magnetotelluric impedance tensor can be computed directly in the wavelet transform domain. The
lightning-stroke transients are easily identified on the dilation-translation plane. Choosing those wavelet
transform values where the signals are located, a higher signal-to-noise ratio estimation of the impedance
tensor can be obtained. The magnetotelluric (MT) method is based on the induction of natural
electromagnetic (EM) fields in the ground.These natural fields can be categorized into two mainclasses.
High-frequency (HF) signals (with frequenciesover 1 Hz) are mainly due to lightning activity, and the
associated EM waves conveyed in the waveguide made of the ionosphere and the conductive earth.
Magnetotelluric (MT) data consist of the sum of several types of natural sources including transient and
quasiperiodic signals and noise sources (instrumental, anthropogenic) whose nature has to be taken into
account in MT data processing. Most processing techniques are based on a Fourier transform of MT time
series, and robust statistics at a fixed frequency are used to compute the MT response functions, but only a
few take into account the nature of the sources. Moreover, to reduce the influence of noise in the inversion
of the response functions, one often sets up another MT station called a remote station. Continuous wavelet
transform on magnetotelluric time series to reduce the influence of noise even for single site processing.
continuous wavelet transform (CWT) is an easy and efficient way to characterize the magnetotelluric (MT)
response function for transient geomagnetic events. Using this technique, we have shown that most of the
information contained in the source wavelet coefficients is sufficient in datasets to enable the
characterization of the MT impedance tensor. Magnetotellurics (MT) is a geophysical method based on the
use of natural electromagnetic signals to define subsurface electrical resistivity structure through
electromagnetic induction. MT waves are generated in the Earth’s atmosphere and magnetosphere by a
range of physical processes, such as magnetic storms, micropulsations, lightning activity. Since the
underground MT wave propagation is of diffusive type, the longer is the wavelength (i.e. the lower the
wave frequency) the deeper will be the propagation depth. Frequency band commonly used in MT
prospecting (10-4 Hz to 104 Hz), the investigation depth ranges from few hundred meters to hundreds of
kilometers. This means that magnetotellurics is inherently a multiscale method and, thus, appropriate for
applications at different scale ranging from aquifer system characterization to petroleum and geothermal
research. Application of the Wavelet transform to the MT data analysis could represent an excellent tool to
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emphasize characteristics of the MT signal at different scales. The use of a Discrete Wavelet (DWT)
decomposition of measured MT time-series data allows to retrieve robust information about the subsoil
resistivity over a wide range of spatial (depth) scales.
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