Magnetotelluric data processing and dimensionality analysis
Speaker: Hsiu-Po Yeh
Abstract
The digital time series collected during an Magnetotelluric (MT) survey can easily total a few Gigabytes, but the data that will finally be interpreted with numerical modeling schemes typically consist of a few hundred numbers per site that represent the frequency-dependent transfer functions. In the spectral analysis, we got many problems, so the MT scientists developed some techniques to solve these problems. Jones et al. (1989) used 8 data processing programs to analyze these techniques, and made some remarks. It is concluded that robust processing methods should become adopted for the analysis of MT data, and that whenever possible remote reference fields should be used to avoid bias due to uncorrelated noise contributions. After the estimation, we can analysis the dimensionality form the Impedance tensor. Bahr (1991) proposed the use of four rotational invariant parameters to classify the types of the geoelectrical dimensionality, and Marti et al. (2005) summarized the dimensionality cases. It is a good method to estimate the dimensionality, but when the data affected by an important level of noise, the errors and biases of the invariants can be important and the dimensionality using the method can be undetermined. That means this method also indicate the noise level. Also for other analysis, data processing is one of the most important parts in the MT study.
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