Data Processing and Analyzing of Magnetotellurics Survey Data in Time Domain

Abstract

Data processing of magnetotelluric (MT) survey has been based on the Fast Fourier Transform (FFT). The FFT processing gives us the response functions (RFs) of the earth fast and easily. However, applying FFT processing to MT data may not be optimum always, since the source of MT is the transient fluctuation of electric current in the ionosphere. The FFT assumes time series to be a stationary so that we focused on an IIR filter called ‘pole on pedestal’ that extracts the signal at a specific frequency. Combining this IIR filter and the Hilbert transform, the RFs are calculated in time domain. For removing the segment contaminated by noise before calculating the RFs, we applied the maximum entropy method (MEM) to the selection of the segments contaminated by large noise. The MEM searches and removes these contaminated segments easily. As a result, we developed the time domain processing of MT data using MEM and IIR filter, and applied this processing to the real data acquired at the Nankai trough. Comparing the conventional and novel data processing, our novel data processing gives us more optimum RFs than the conventional processing. In addition, we discussed the time-domain separation of up-going/down-going electromagnetic waves based on the plane wave decomposition. All our attempts support an idea that the time-domain analysis of magnetotelluric data would give us more accurate and detailed subsurface information.