• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.253-258
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• 2006

The Korean peninsula has been known to be very difficult to acquire clean MT and GDS data due to its highly industrialization and civilization. In this environment, a pre-screening step selecting data segments with a proper S/N ration is an essential one. This study modified the automatic pre-screening step based on the spectral power of electromagnetic field (RMP) taking account of the situation of the Korean Peninsula. The modified RMP technique was applied to MT data measured at seven sites located in middle part of the peninsula. In the whole sense, the RMP technique considerably improved the connectivity of apparent resistivity and phase curves around the period of 10 sec. In addition, the results processed by the RMP technique showed a very little difference with those derived from manual editing, and the superior performance of it is found especially in the connectivity of apparent resistivity curve.

• 한국지구과학회:학술대회논문집
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• 2005.02a
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• pp.253-253
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• 2005

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.273-280
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• 2005

Robust magneto-telluric (MT) response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these methods can reduce the influence of unusual data (outlier) in the response (electric field) variable, but often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded influence estimator is described which simultaneously limits the influence of both outlier and leverage point, and has proven to consistently yield more reliable MT response function estimates than conventional robust approach. The bounded influence estimator combines a standard robust M-estimator with leverage weighting based on the statistics of the hat matrix diagonal, which is a standard statistical measure of unusual predictors. Further extensions to MT data analysis are proposed, including a establishment of data rejection criterion which minimize the influence of both electric and magnetic outlier in frequency domain based on statistical distribution of electromagnetic field. The rejection scheme made in this study seems to have an effective performance on eliminating extreme data, which is even not removed by BI estimator, in frequency domain. The effectiveness and advantage of these developments are illustrated using real MT data.