Matthew Flinders Lecture 1969 - Researches on the Internal Structure of the Earth.

1966 ◽  
Vol 1 (4) ◽  
pp. 39
Author(s):  
KE Bullen
Keyword(s):  
Internal Structure ◽  
The Earth

Planet Earth – our oasis in space

2004 ◽  
Vol 12 (1) ◽  
pp. 111-119
Author(s):  
SIEGFRIED J. BAUER
Keyword(s):  
Magnetic Field ◽  
Solar System ◽  
Internal Structure ◽  
Solid Surface ◽  
Liquid Water ◽  
Atmospheric Environment ◽  
Suitable Habitat ◽  
The Earth

Planet Earth is unique in our solar system as an abode of life. In contrast to its planetary neighbours, the presence of liquid water, a benign atmospheric environment, a solid surface and an internal structure providing a protective magnetic field make it a suitable habitat for man. While natural forces have shaped the Earth over millennia, man through his technological prowess may become a threat to this oasis of life in the solar system.

Review Lecture: The dynamical properties and internal structures of the Earth, the Moon and the planets

1972 ◽  
Vol 328 (1574) ◽  
pp. 301-336 ◽  
Keyword(s):  
Internal Structure ◽  
Recent Progress ◽  
High Pressures ◽  
Artificial Satellites ◽  
The Moon ◽  
The Earth ◽  
Internal Structures ◽  
Theoretical Investigations ◽  
Dynamical Properties ◽  
Very High

The aim of this review is to bring together and relate recent progress in three subjects - the internal structure of the Earth, the behaviour of materials at very high pressures and the dynamical properties of the planets. Knowledge of the internal structure of the Earth has been advanced in recent years, particularly by observations of free oscillations of the whole Earth excited by the very largest earthquakes; as a consequence, it is clear that K. E. Bullen’s hypothesis that bulk modulus is a smooth function of pressure irrespective of composition is close to the truth for the Earth. Understanding of the behaviour of materials at very high pressure has increased as a result both of experiments on the propagation of shock waves and of theoretical investigations along a number of lines and it can now be seen that Bullen’s hypothesis is not true irrespective of chemical composition and crystal structure but that it happens to apply to the Earth because of particular circumstances. Studies of the orbits of artificial satellites and space probes have led to better knowledge of the dynamics of the Moon, Mars and Venus, and there have also been recent improvements in the traditional studies of Uranus and Neptune. Our knowledge of the dynamics of the planets is on the whole rather restricted, and Bullen’s hypothesis only applies directly to the Moon (for which the application is trivial) and possibly to Mars; the dynamical properties do none the less set fairly restrictive limits to the models that can be constructed for other planets. It would be possible for all planets to have cores of similar composition to the Earth ’s, surrounded by mantles of different sorts, silicates for the terrestrial planets and mostly hydrogen for Jupiter, Saturn, Uranus and Neptune.

scholarly journals Internal structure of the Earth

Nature ◽  
1990 ◽  
Vol 344 (6262) ◽  
pp. 106-106 ◽  
Author(s):  
Bernard Wood ◽  
George Helffrich
Keyword(s):  
Internal Structure ◽  
The Earth

scholarly journals Sparsity-based compressive reservoir characterization and modeling by applying ILS-DLA sparse approximation with LARS on DisPat-generated MPS models using seismic, well log, and reservoir data

2016 ◽  
Author(s):  
Mohammad Hosseini ◽  
Mohammad Ali Riahi
Keyword(s):  
Image Processing ◽  
Internal Structure ◽  
Sparse Coding ◽  
Geophysical Methods ◽  
Sparse Approximation ◽  
Distance Functions ◽  
Multiple Point ◽  
Image Modeling ◽  
Training Images ◽  
The Earth

Abstract. In the earth sciences, there is only one single true reality for a property of any dimension whereas many realization models of the reality might exist. In other words, a set of interpreted multiplicities of an unknown property can be found but only one unique fact exists and the task is to return from the multiplicities to the uniqueness of the reality. Such an objective is mathematically provided by sparse approximation methods. The term "approximation" indicate the sufficiency of an interpretation that is close enough to the true mode, i.e. reality. In geosciences, the multiplicities are provided by multiple-point statistical methods. Realistic modeling of the earth interior demands for more sophisticated geostatistical methods based on true available images, i.e. the training images. Among available MPS methods, the DisPat algorithm is a distance-based MPS method which generate appealing realizations for stationary and nonstationary training images by classifying the patterns based on distance functions using kernel methods. Advances in nonstationary image modeling is an advantage of the DisPat method. Realizations generated by the MPS methods form the training set for the sparse approximation. Sparse approximation is consisted of two steps, i.e. sparse coding and dictionary update, which are alternately used to optimize the trained dictionary. Model selection algorithms like LARS are used for sparse coding. LARS optimizes the regression model sequentially by choosing a proper number of variables and adding the best variable to the active set in each iteration. Out of numerous training dictionary methods given in the literature, the ILS-DLA is a variant of the MOD algorithm where the latter is inspired by the GLA and the whole trained dictionary is sequentially updated by alternating between sparse coding and dictionary training steps. The ILS-DLA is different from the MOD for addressing the internal structure of the dictionary by considering overlapping or non-overlapping blocks and modifying the MOD algorithm according to the internal structure of the trained dictionary. The ILS-DLA is faster than the MOD in the sense that it inverts for smaller blocks constructing the trained dictionary rather than inverting for the entire block. The subject of this paper is an integration study between sparse approximations from image processing and compressed sensing, multiple-point statistics from the field of geostatisitcs, and the geophysical methods and reservoir engineering from the branch of petroleum science. This paper specifically emphasizes the utilization of image processing in solving reservoir complexities and enhancing reservoir models.

Venus internal structure and global deformation

2021 ◽  
Author(s):  
Christelle Saliby ◽  
Agnes Fienga ◽  
Giorgio Spada ◽  
Daniele Melini ◽  
Anthony Memin
Keyword(s):  
Gravity Field ◽  
Internal Structure ◽  
Terrestrial Planet ◽  
Love Number ◽  
Tidal Forces ◽  
The Earth ◽  
Mass Redistribution ◽  
Love Numbers ◽  
Fortran 90 ◽  
Global Deformation

<p>Tidal forces acting on a planet cause a deformation and mass redistribution in its interior, involving surface motions and variation in the gravity field, which may be observed in geodetic experiments. The change in the gravitational field of the planet, due to the influence of an external gravity field, described primarily by its tidal Love number k of degree 2 (denoted by k<sub>2</sub>) can be observed from analysis of a spacecraft radio tracking. The planet’s deformation is linked to its internal structure, most effectively to its density and rigidity. Hence the tidal Love number k<sub>2</sub> can be theoretically approximated for different planetary models, which means comparing the observed and theoretical calculation of k<sub>2</sub> of a planet is a window to its internal structure.</p> <p>The terrestrial planet Venus is reminiscent of the Earth twin planet in size and density, which leads to the assumption that the Earth and Venus have similar internal structures. In this work, with a Venus we investigate the structure and elastic parameters of the planet’s major layers to calculate its frequency dependent tidal Love number k<sub>2</sub>. The calculation of k<sub>2</sub> is done with ALMA, a Fortran 90 program by <em>Spada [2008]</em> for computing the tidal and load Love numbers using the Post-Widder Laplace inversion formula. We test the effect of different parameters in the Venus model (as a layer’s density, rigidity, viscosity and thickness) on the tidal Love numbers k<sub>2 </sub>and different linear and non-linear combinations of k<sub>2</sub> and<sub> </sub>h<sub>2</sub> (as the tidal Love number h<sub>2</sub> describes the radial displacement due to tidal effects).</p>

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