Separation of local and regional information in distorted GDS response functions by hypothetical event analysis

Astronomy and Astrophysics – Astronomy

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Channelled Currents, Electromagnetic Induction, Magnetovariation

Scientific paper

Electromagnetic investigations are usually intended to examine regional structures where induction takes place at a given period range. However, the regional information is often distorted by galvanic effects at local conductivity boundaries. Bahr (1985) and Groom & Bailey (1989) developed a physical distortion model for decomposing the MT impedance tensor, based upon local galvanic distortion of a regional 2-D electromagnetic field. We have extended their method to predict the magnetic variation fields created at an array of sites. The magnetic response functions at periods around 1000 s may be distorted by large-scale inhomogeneities in the upper or middle crust. In this period range, the data measured by a magnetometer array contain common information that can be extracted if the data set is treated as a unit, for example by using hypothetical event analysis. With this technique it is always possible to recover the regional strike direction from distorted data, even if a strong, spatially varying regional vertical field component is present in the data set. The determination of the regional impedance phases, on the other hand, is far more sensitive to deviations from the physical distortion model.
The approach has been used to investigate the Iapetus data set. For the array, which covers an area of 200 km × 300 km in northern England/southern Scotland, the technique revealed a common regional strike azimuth of ca. N125° E in the period range 500-2000 s. This direction differs from the strike indicated by the induction arrows, which seem influenced mainly by local current concentrations along the east-west-striking Northumberland Trough and a NE-SW-striking mid-crustal conductor. Both impedance phases are positive and differ by ca. 10°, which supports the assumptions of distortion fields in the data set and that the regional structure is 2-D.

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