Institute of Geophysics, University of TehranJournal of the Earth and Space Physics2538-371X37420120121Using the determinant data as a replacement for the Static Shift correction in Magnetotelluric surveysUsing the determinant data as a replacement for the Static Shift correction in Magnetotelluric surveys67772430210.22059/jesphys.2012.24302FABehroozOskooiAmir HosseinJavaheri K.Ahmad AliBehroozmandJournal Article19700101Magnetotelluric (MT) method is an electromagnetic method which provides information about subsurface conductivity structures using Earth's natural electromagnetic fields. Static shift is one of disorders arising from shallow conductors; therefore static shift must be corrected as one of MT data processing steps. In the absence of sufficient information about the near surface distortions, which usually is provided by extra works like TEM and VES, one has to consider the determinant data for the inversion to avoid any misinterpretation. In this paper, we use the determinant data as an effective replacement for the static shift correction. Finally, we present a case study to show the application of determinant data.
There are various techniques for static shift removal. One of them is theoretical calculation of static shift relating to near surface buried inhomogenities or surface topographic effects. Alternatively, we can use auxiliary data of known geology of the region or independent measurements such as TEM and VES sounding (Sternberg et al., 1988). In these methods, after calculation of the accurate apparent resistivity values in the site of interest, the curves are transferred to the desired level.
Utilizing determinant data for inversion leads to the best results for the interpretation in the case that the above methods are not accessible.
As a case study, MT data from a site in Inche-Boroon area in the north of Golestan Province, Iran is considered here. After processing, MT data was obtained as apparent resistivity with respect to frequency (or period) which is shown for ,(green curve) and ,(blue curve) in Fig.3. Also, the determinant apparent resistivity data is shown in red. As can be seen, determinant data appears as a mean of and .
According to the correlation of determinant data with geological structures, it is necessary that apparent resistivity data if measured as and , to transfer to the correct level (which is compromised to determinant data).
In order to confirm the effectiveness of determinant data, MT data was collected for station in the vicinity of an exploration well in that area. This data (as a determinant apparent resistivity) and also the information obtained from the well log are shown in Fig.4. Subsurface information of the well log has a good correlation with the 1D model derived from inversion of determinant data such that there is a conductive layer containing salt water table in the depth of 670 to 840 meters which can be seen clearly in the obtained model from determinant data too. This correlation indicates the correctness of subsurface information obtained from modeling of determinant data.
The magnetotelluric data processing is one of the most important steps in MT surveys in the meantime static shift correction has an important role. If the application of common techniques for removing the static shift are not accessible (such as calculation of static shift relating to near surface buried inhomogenities or surface topographic effects, using auxiliary data of known geology of the region or independent measurements such as TEM and VES sounding), to avoid any misinterpretation, it is necessary to make use of determinant data for inversion.
As previously shown, using determinant data as a proper replacement for static shift correction can be applied in magnetotelluric studies and the case study presented here clearly shows this matter and also the correlation between determinant data and subsurface structures.
Using determinant data is always applicable since it is rotation invariant and therefore, the same data is needed for modeling without regarding to the assumed strike in 2D modeling.
Determinant data often fit very well with 2D models relative to TE and TM data and it is easily possible to operate 2D inversion (similar to 1D) by ignoring the details of static shift.Magnetotelluric (MT) method is an electromagnetic method which provides information about subsurface conductivity structures using Earth's natural electromagnetic fields. Static shift is one of disorders arising from shallow conductors; therefore static shift must be corrected as one of MT data processing steps. In the absence of sufficient information about the near surface distortions, which usually is provided by extra works like TEM and VES, one has to consider the determinant data for the inversion to avoid any misinterpretation. In this paper, we use the determinant data as an effective replacement for the static shift correction. Finally, we present a case study to show the application of determinant data.
There are various techniques for static shift removal. One of them is theoretical calculation of static shift relating to near surface buried inhomogenities or surface topographic effects. Alternatively, we can use auxiliary data of known geology of the region or independent measurements such as TEM and VES sounding (Sternberg et al., 1988). In these methods, after calculation of the accurate apparent resistivity values in the site of interest, the curves are transferred to the desired level.
Utilizing determinant data for inversion leads to the best results for the interpretation in the case that the above methods are not accessible.
As a case study, MT data from a site in Inche-Boroon area in the north of Golestan Province, Iran is considered here. After processing, MT data was obtained as apparent resistivity with respect to frequency (or period) which is shown for ,(green curve) and ,(blue curve) in Fig.3. Also, the determinant apparent resistivity data is shown in red. As can be seen, determinant data appears as a mean of and .
According to the correlation of determinant data with geological structures, it is necessary that apparent resistivity data if measured as and , to transfer to the correct level (which is compromised to determinant data).
In order to confirm the effectiveness of determinant data, MT data was collected for station in the vicinity of an exploration well in that area. This data (as a determinant apparent resistivity) and also the information obtained from the well log are shown in Fig.4. Subsurface information of the well log has a good correlation with the 1D model derived from inversion of determinant data such that there is a conductive layer containing salt water table in the depth of 670 to 840 meters which can be seen clearly in the obtained model from determinant data too. This correlation indicates the correctness of subsurface information obtained from modeling of determinant data.
The magnetotelluric data processing is one of the most important steps in MT surveys in the meantime static shift correction has an important role. If the application of common techniques for removing the static shift are not accessible (such as calculation of static shift relating to near surface buried inhomogenities or surface topographic effects, using auxiliary data of known geology of the region or independent measurements such as TEM and VES sounding), to avoid any misinterpretation, it is necessary to make use of determinant data for inversion.
As previously shown, using determinant data as a proper replacement for static shift correction can be applied in magnetotelluric studies and the case study presented here clearly shows this matter and also the correlation between determinant data and subsurface structures.
Using determinant data is always applicable since it is rotation invariant and therefore, the same data is needed for modeling without regarding to the assumed strike in 2D modeling.
Determinant data often fit very well with 2D models relative to TE and TM data and it is easily possible to operate 2D inversion (similar to 1D) by ignoring the details of static shift.https://jesphys.ut.ac.ir/article_24302_7fa3848b11a929a75df55e53e18f86cc.pdf