Actions for A data variance technique for automated despiking of magnetotelluric data with a remote reference [electronic resource].

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A data variance technique for automated despiking of magnetotelluric data with a remote reference [electronic resource].

Published
Berkeley, Calif. : Lawrence Berkeley National Laboratory, 2011.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
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numbers : digital, PDF file
Additional Creators
Lawrence Berkeley National Laboratory and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
The magnetotelluric method employs co-located surface measurements of electric and magnetic fields to infer the local electrical structure of the earth. The frequency-dependent 'apparent resistivity' curves can be inaccurate at long periods if input data are contaminated - even when robust remote reference techniques are employed. Data despiking prior to processing can result in significantly more reliable estimates of long period apparent resistivities. This paper outlines a two-step method of automatic identification and replacement for spike-like contamination of magnetotelluric data; based on the simultaneity of natural electric and magnetic field variations at distant sites. This simultaneity is exploited both to identify windows in time when the array data are compromised, and to generate synthetic data that replace observed transient noise spikes. In the first step, windows in data time series containing spikes are identified via intersite comparison of channel 'activity' - such as the variance of differenced data within each window. In the second step, plausible data for replacement of flagged windows is calculated by Wiener filtering coincident data in clean channels. The Wiener filters - which express the time-domain relationship between various array channels - are computed using an uncontaminated segment of array training data. Examples are shown where the algorithm is applied to artificially contaminated data, and to real field data. In both cases all spikes are successfully identified. In the case of implanted artificial noise, the synthetic replacement time series are very similar to the original recording. In all cases, apparent resistivity and phase curves obtained by processing the despiked data are much improved over curves obtained from raw data.
Report Numbers
E 1.99:lbnl-4362e
lbnl-4362e
Other Subject(s)
Note
Published through SciTech Connect.
02/15/2011.
"lbnl-4362e"
Geophysical Prospecting ISSN 0016-8025; GPPRAR FT
Kappler, K.
Earth Sciences Division
Funding Information
DE-AC02-05CH11231
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