Abstract
Magnetotelluric (MT) response function estimates can be severely disturbed
by the effects of cultural noise. Methods to isolate and remove these
disturbances are typically based on time-series editing, robust statistics,
remote reference processing, or some combination of the above. Robust
remote reference processing can improve the data quality at a local
site, but only if synchronous recordings of at least one additional
site are available and if electromagnetic noise between these sites
is uncorrelated. If these prerequisites are not met, we suggest an
alternative approach for noise removal, based on a combination of
frequency domain editing with subsequent single site robust processing.
The data pre-selection relies on a thorough visual inspection of
a variety of statistical parameters such as spectral power densities,
coherences, the distribution of response functions and their errors,
etc. Extreme outliers and particularly noisy data segments are excluded
from further data processing by setting threshold values for individual
parameters. Examples from Namibia and Jordan illustrate that this
scheme can improve data quality significantly. However, the examples
also suggest that it is not possible to establish generally valid
rules for selection as they depend strongly on the local noise conditions.
High coherence, for example, can indicate a good signal-to-noise
ratio or strongly correlated noise. However, we found that strong
polarization of the magnetic field channels and the distribution
of response function errors are two important parameters for noise
detection.
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