P. Schmoldt, PhD - MTNet - DIAS
P. Schmoldt, PhD - MTNet - DIAS P. Schmoldt, PhD - MTNet - DIAS
6. Using magnetotellurics to gain information about the Earth estimators exhibit a breakdown point of zero, meaning that the smallest amount of erroneous data may seriously bias the final estimate [Smirnov, 2003]. An approach with a considerable higher breakdown point (ε ∗ = 50 %) was presented by Siegel [1982] using a repeated median algorithm, and an application for MT processing has been developed by Smirnov [2003]. Therein, the author uses a reduced M-estimator to supplement the initial Siegel estimator approximation in order to enhance the performance for short time-series. 6.3. Deriving subsurface structure using magnetotelluric data Deriving the distribution of Earth properties and thereby enhancing knowledge about geological processes is the aim of most geophysical investigations. In MT, the electric properties of the Earth are studied, which are usually derived through an inversion of the dataset (cf. Sec. 6.3.3). Overviews about general principles of inversion processes and related theory are given, among others, by Aster et al. [2005]; Tarantola [2005]; their application for MT problems was reviewed by Avdeev [2005]; Börner [2010]; Siripunvaraporn [2010]. Here a condensed description of the parts relevant for MT inversion is given; namely a characterisation of common forward modelling methods, followed by an illustration of the basic inversion approach, and lastly an examination of the non-uniqueness problem of MT inversion. Thereafter, different solvers for the MT inversion problem are discussed and common inversion codes are presented. At first, however, the principles of traditional analytical transformations are illustrated. 6.3.1. Analytical direct transformation Analytical approaches aim to find mathematical relationships between MT response data and the resistivity-depth distribution of the subsurface. The three most commonly used relations for 1D MT transformation were derived by Niblett and Sayn-Wittgenstein [1960], Bostick [1977], and Weidelt et al. [1980]. All approaches calculate the resistivity at the so-called Niblett-Bostick depth δNB from a given apparent resistivity ρa and the magnetic permeability µ0 at the related period, i.e. δNB = ρa(T)T 2πµ0 . (6.13) The Niblett-Bostick depth is related to the skin depth δs as δs = √ 2δNB (cf. Sec. 3.3), hence referring to a depth at which the amplitude of the wave F0 is reduced by a factor e − 1 √ 2 (approximately F0/2): 114 F(δNB) = F0e − πµ0 ρaT δNB = F0e − 1 √ 2 . (6.14)
6.3. Deriving subsurface structure using magnetotelluric data Analytical direct transformations can provide a first insight to the subsurface structures and their results can be used to create a starting model for subsequent inversion. Moreover, depth estimations from analytical transformations are also commonly used during processing of MT data, e.g. strike estimation (Sec. 9.6.1). Niblett-Bostick transformation The so-called Niblett-Bostick transformation refers to the two independently-developed formulations by Niblett and Sayn-Wittgenstein [1960], and Bostick [1977]. Both equations use apparent resistivity values ρa (or its inverse apparent conductivity σa) and its depthderivative to derive a 1D resistivity-depth (or conductivity-depth) profile, i.e. Niblett and Sayn-Wittgenstein [1960]: and Bostick [1977]: with ∂σa(T) σNB(δNB) = σa(T) + δNB , (6.15) m(T) = ∂δNB 1 + m(T) ρNB(δNB) = ρa(T) 1 − m(T) ∂ log(ρa(T)) ∂ log(T) = T ρa(T) (6.16) ∂ρa(T) , (6.17) ∂T in where δNB is given in Equation 6.13. It was shown by Jones [1983b] that the transformation by Niblett and Sayn-Wittgenstein and Bostick are equivalent. Jones [1983b] further points out that an alternative expression of the Bostick resistivity at depth δNB can be used, i.e. π ρW(δNB) = ρa(T) − 1 . (6.18) 2φ(T) This formulation is related to the ‘appproximate phase’ [Weidelt et al., 1980] (next paragraph) and uses phase φ(T) and apparent resistivity ρa(T) information at one period to estimate the resistivity. The resistivity is derived directly without the extra step of calculating the apparent resistivity gradient, which speeds up the calculation process; however, the two formulations yield different resistivity estimates (i.e. ρW ρNB). Schmucker and Weidelt transformation Like the formulation in Equation 6.18, and unlike the approaches by Niblett and Sayn- Wittgenstein and Bostick (Eqs. 6.15-6.16), the ρ ∗ − z ∗ transform [Schmucker, 1987] uses phase information φ(T) and does not require prior calculation of the derivative. The transformation calculates the resistivity for a depth z ∗ which is equivalent to the skindepth δs 115
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6. Using magnetotellurics to gain information about the Earth<br />
estimators exhibit a breakdown point of zero, meaning that the smallest amount of erroneous<br />
data may seriously bias the final estimate [Smirnov, 2003]. An approach with a<br />
considerable higher breakdown point (ε ∗ = 50 %) was presented by Siegel [1982] using a<br />
repeated median algorithm, and an application for MT processing has been developed by<br />
Smirnov [2003]. Therein, the author uses a reduced M-estimator to supplement the initial<br />
Siegel estimator approximation in order to enhance the performance for short time-series.<br />
6.3. Deriving subsurface structure using<br />
magnetotelluric data<br />
Deriving the distribution of Earth properties and thereby enhancing knowledge about geological<br />
processes is the aim of most geophysical investigations. In MT, the electric properties<br />
of the Earth are studied, which are usually derived through an inversion of the dataset<br />
(cf. Sec. 6.3.3). Overviews about general principles of inversion processes and related<br />
theory are given, among others, by Aster et al. [2005]; Tarantola [2005]; their application<br />
for MT problems was reviewed by Avdeev [2005]; Börner [2010]; Siripunvaraporn<br />
[2010]. Here a condensed description of the parts relevant for MT inversion is given;<br />
namely a characterisation of common forward modelling methods, followed by an illustration<br />
of the basic inversion approach, and lastly an examination of the non-uniqueness<br />
problem of MT inversion. Thereafter, different solvers for the MT inversion problem are<br />
discussed and common inversion codes are presented. At first, however, the principles of<br />
traditional analytical transformations are illustrated.<br />
6.3.1. Analytical direct transformation<br />
Analytical approaches aim to find mathematical relationships between MT response data<br />
and the resistivity-depth distribution of the subsurface. The three most commonly used<br />
relations for 1D MT transformation were derived by Niblett and Sayn-Wittgenstein [1960],<br />
Bostick [1977], and Weidelt et al. [1980]. All approaches calculate the resistivity at the<br />
so-called Niblett-Bostick depth δNB from a given apparent resistivity ρa and the magnetic<br />
permeability µ0 at the related period, i.e.<br />
δNB =<br />
<br />
ρa(T)T<br />
2πµ0<br />
. (6.13)<br />
The Niblett-Bostick depth is related to the skin depth δs as δs = √ 2δNB (cf. Sec. 3.3),<br />
hence referring to a depth at which the amplitude of the wave F0 is reduced by a factor<br />
e − 1 √ 2 (approximately F0/2):<br />
114<br />
F(δNB) = F0e −<br />
<br />
πµ0<br />
ρaT δNB<br />
= F0e − 1 √<br />
2 . (6.14)