P. Schmoldt, PhD - MTNet - DIAS

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5. Earth’s properties observable with magnetotellurics gation zone for rising hot mantle material (plumes) originating at the CMB, as well as for descending crustal material subducted from the Earth’s surface. Subducting slabs, for instance, may be horizontally deflected in the MTZ and become dehydrated before continuing to sink into the lower mantle [Richard and Bercovici, 2009]. This implies reduced water content in the lower mantle, affecting local composition, density, and temperature conditions. Permeability of the MTZ, hence characteristics of its interaction with such vertical transport mechanisms, is highly dependent on its conditions [e.g. Davies, 1995; Karato et al., 1995; Jin et al., August, 2001; Karato et al., 2001]. The composition of the Earth’s mantle Two classic models exist for the composition of the mantle: pyrolytic (transformation of the compounds caused by heat) and piclogitic (picritic eclogite). In pyrolytic mantle models, the chemical difference between the upper and lower mantle is assumed negligible and differences within the mantle are attributed to mineral phase changes, whereas in piclogitic mantle models a more silica-(and iron-)rich lower mantle is proposed. Pyrolytic models are in good agreement with measured data and are favoured by the majority of authors [e.g. Ringwood, 1975; Poirier, 2000; Xu et al., 2000a]. Recent support for the pyrolytic model was provided, for example, by the results of Matas et al. [2007] proposing that the Earth’s mantle is most likely relatively homogeneous. The authors state that the lower mantle must have an average Mg–Si ratio lower than 1.3 in order to satisfactorily fit 1D seismic profiles. Moreover, Matas et al. [2007] claim that when a low value for the pressure derivative of the shear modulus for perovskite is adopted (µ ′ 0 ≈ 1.6 GPa/km), consistent with the most recent experimental results, the Mg–Si ratio of the bottom part of the lower mantle reduces to a value close to 1.18, thus denoting a more homogeneous mantle composition. The composition of the Earth’s mantle can either be derived directly from rock samples transported from the lithospheric-mantle to the surface as kimberlitic or volcanic xenoliths, or indirectly through interpretation of geophysical measurements. As a result of those measurements it is inferred that olivine, clinopyroxene, orthopyroxene, garnet, and perovskite are the most common minerals in the Earth’s mantle (cf. Fig. 5.11, and Tabs. 5.3 and 5.4). Olivine and its high-pressure polymorphs (wadsleyite, ringwoodite) form the most abundant minerals by volume (50 – 60 %) in the upper mantle, thus dominating its bulk electric conductivity, whereas perovskite and magnesiowüstite account for the majority of the lower mantle minerals [e.g. Ringwood, 1975; Xu et al., 2000a]. In the absence of areas with well-connected networks of fluids, ion conductors, or partial melt, the electric conductivity of the mantle is dominated by semiconduction (Sec. 5.1.3), therefore the conductivity of the mantle is mostly controlled by temperature (Eq. 5.9, Sec.5.3). Exact values of conductivity are dependent on specific parameters of the related materials and their fraction of the local composition. Conductivity of mantle minerals is primarily controlled by proton (H + ) and small polaron conduction (electron holes “hopping” between Fe2+ and Fe3+ ) [Xu et al., 1998a; Yoshino et al., 2008; Yoshino, 2010] 96
Species 5.2. Variation of electric conductivity with depth Whole-mantle models Upper mantle (1) (2) (3) (4) Olivine 47.2 36.5 37.8 51.4 Orthopyroxene 28.3 33.7 33.2 25.6 Clinopyroxene 22.5 16.8 13.6 11.65 Garnet 1.53 11.6 14.2 9.6 Ilmenite 0.2 0.5 0.24 0.57 Chromite - 1.6 0.94 0.44 Tab. 5.3.: Earlier models of mantle mineralogy, 1: Equilibrium condensation [BVP-Project, 1981], 2: Cosmochemical model [Ganapathy and Anders, 1974], 3: Cosmochemical model [Morgan and Anders, 1980], 4: Pyrolite [Ringwood, 1977]; in Anderson [2004]. Polymorph phases of olivine and lower mantle minerals (perovskite and magnesiowüstite) are not considered in these earlier mantle models (cf. Fig. 5.11 and Tab. 5.5). Name Formula Olivine (Mg,Fe)2SiO4 Orthopyroxene (Mg,Fe)2Si2O6 Clinopyroxene (Ca,Na)(Mg,Fe,Al,Ti)(Si,Al)2O6 Garnet (Ca,Al,Mg)3(Al,Fe3+,Cr)2(SiO4)3 Ilmenite FeTiO3 Chromite FeCr2O4 Perovskite CaTiO3 Magnesiowüstite (Mg,Fe)O Tab. 5.4.: Typical mantle rocks and there chemical formula; polymorph phases of olivine are wadsleyite and ringwoodite. 97
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Multidimensional isotropic and anis
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Contents 2.3. Deviation from plane
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Contents 8.3. Inversion of 3D model
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List of Figures 2.1. Amplitude of t
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List of Figures 4.17. Visual repres
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List of Figures 8.2. Ambient noise
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List of Figures 10.10.RMS misfit va
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List of Figures A.15.Result of anis
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List of Tables xviii 5.5. Parameter
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List of Acronyms FE finite element
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List of Symbols Below is a list of
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Symbol SI unit Denotation φ · pha
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Abstract The Tajo Basin and Betic C
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Publications Poster presentations x
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Acknowledgements Team, namely Colin
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Introduction 1 The Iberian Peninsul
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ections from enhanced one-dimension
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Part I Theoretical background of ma
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2. Sources for magnetotelluric reco
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Mathematical description of electro
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yields 3.2. Deriving magnetotelluri
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3.2. Deriving magnetotelluric param
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3.3. Magnetotelluric induction area
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Depth d s d 1 d 2 d n-2 d n-1 t 1 t
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3.4. Boundary conditions materials
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3.5. The influence of electric perm
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Page 85 and 86: Distortion of magnetotelluric data
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Page 91 and 92: J s 0 s 0 4.1. Types of distortion
Page 95 and 96: Scale Type Terminology Example Atom
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Page 99 and 100: 4.2. Dimensionality Fig. 4.12.: The
Page 101 and 102: 1D 2D local 3D/1D 3D/2D regional 4.
Page 103 and 104: 4.3. General mathematical represent
Page 105 and 106: 4.4. Removal of distortion effects
Page 107 and 108: Parameter Geoelectrical application
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Page 115: Method Applicability Swift angle 2D
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Page 168 and 169: Part II Geology of the study area I
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7. Geology of the Iberian Peninsula
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Recovering a synthetic 3D subsurfac
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direction direction Depth: 12 - 30
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8.2. Generating synthetic 3D model
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Distance from the centre of the mes
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3D N45W 3D-crust TE Rho TE Phi Peri
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8.3. Inversion of 3D model data sch
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Model variation RMS misfit Optimal
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Profile: 3D-crust (TM-only) Depth (
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Parameter Value 8.3. Inversion of 3
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Depth (km) 10 -2 10 -1 10 0 10 1 10
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Depth (km) 10 -2 10 -1 10 0 10 1 10
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Step 1: Isotropic 2D inversion Step
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8.3. Inversion of 3D model data par
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8.4. Summary and conclusions bution
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Regularisation order Smoothing para
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S N 1% 0 Depth (km) 3% Depth (km) 1
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9.1. Profile location Data collecti
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Location (degrees) Recording period
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Geological region Stations Geologic
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9.4. Segregation of data acquired w
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Phase (degrees) 135 90 45 0 Z xy -4
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0 km 10 km 30 km 100 km 300 km Dept
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Pseudo-sections crustal strike dire
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9.8. Analysis of vertical magnetic
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9.8. Analysis of vertical magnetic
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10. Data inversion WinGLink softwar
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a (horizontal smoothing) 10. Data i
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10. Data inversion Short period ran
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10. Data inversion TM+TE Depth (km)
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10. Data inversion (a) Constrained
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10. Data inversion the model into u
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10. Data inversion Depth (km) S N 0
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Depth (km) 10. Data inversion S N 0
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10. Data inversion Group velocity m
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10. Data inversion ductivity of thi
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10. Data inversion Shtrikman upper
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10. Data inversion in the lithosphe
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10. Data inversion isotropic 2D lay
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10. Data inversion Depth (km) Depth
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10. Data inversion tigation is usua
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Depth (km) Depth (km) 10. Data inve
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Modelled Observed Modelled Observed
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Depth (km) 10. Data inversion 0 30
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10. Data inversion Depth off LAB (k
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10. Data inversion Depth (km) S 0 5
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10. Data inversion 10.3. Summary an
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10. Data inversion owing to availab
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11 Summary and conclusions The key
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11.2. PICASSO Phase I investigation
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A. Appendix Eocene 54 Ma 42 Ma 36 M
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A. Appendix A.2. Auxiliary informat
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A. Appendix 292 Fig. A.3.: Issues i
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A. Appendix A.2.4. Computation time
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296 3D-mantle profile Inversion res
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298 07-centre profile The profile 0
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300 3D-crust profile The profile 3D
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302 J-centre profile The J-centre p
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A. Appendix Anisotropy Resistivity
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A. Appendix A.4. Auxiliary figures
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A. Appendix 314 ρ TE(Ω−m) φ T
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A. Appendix 320 pic003 (off-diagona
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A. Appendix 322 pic013 (off-diagona
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Bibliography Abalos, B., J. Carrera
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Bibliography Artemieva, I. M. (2006
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Bibliography Berdichevsky, M., V. D
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Bibliography Cebriá, J.-M., and J.
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Bibliography de Vicente, G., J. Gin
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Bibliography Egbert, G. D., and J.
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Bibliography Ganapathy, R., and E.
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Bibliography Haak, V., and R. Hutto
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Bibliography Hutton, R. (1972), Som
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Bibliography Jones, A. G., and R. W
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Bibliography Kurtz, R. D., J. A. Cr
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Bibliography Lviv Centre of Institu
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Bibliography Merrill, R. T., and M.
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Bibliography Newman, G., and G. Hoh
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Bibliography Pádua, M. B., A. L. P
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Bibliography Prácser, E., and L. S
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Bibliography Ritter, J. R. R., M. J
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Bibliography Serson, P. H. (1973),
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Bibliography Spitzer, K. (2006), Ma
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Bibliography Tikhonov, A. N., and V
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Bibliography Wanamaker, B. J., and
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Bibliography Xu, Y., C. McCammon, a
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