Geological noise in magnetotelluric data: a classification of distortion types

Details Geological noise in magnetotelluric data: a classification of distortion types Geological noise in magnetotelluric data: a classification of distortion types

Feb 1991

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1991pepi...66...24b&link_type=abstract

Physics of the Earth and Planetary Interiors, Volume 66, Issue 1-2, p. 24-38.

Physics

101

Scientific paper

Decomposition of the magnetotelluric impedance tensor into parameters relevant to a general Earth model that allows for galvanic distortion and regional induction has become a powerful data evaluation tool. Two similar techniques that incorporate superimposition of local three-dimensional and regional two-dimensional structures are considered. Both techniques have two serious limitations: (1) the conductivity structure might be less complex than assumed in the general model and therefore irrelevant model parameters are derived; (2) the regional conductivity structure may be more complicated than indicated by a two-dimensional model. The first problem is addressed in this paper by considering seven classes of general model of increasing complexity. Procedures are suggested that can be used to assign a particular datum to only one of the model classes. Therefore dimensionality parameters are suggested which include conventional and regional skew as well as local and regional structural dimensionality indicators. To address the second problem, an extension of the decomposition technique is presented that allows for a departure from the purely two-dimensional case for regional structures. An example, together with field data, is provided from the German deep drilling site. It explains how the decomposition technique recovers the two impedance phases belonging to a large regional anomaly although the impedance tensors are influenced by strong local distortion. This example also illustrates how the length scale of inductive structures can be estimated from the frequency dependence of the structural dimensionality parameters.

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