Développement d'outils d'interprétation de données géophysiques

Nacim Foudil Bey. ( 2012 )
Université de Lorraine, Université du Québec en Abitibi-Témisgamingue

Abstract

In recent years with the technology developments, airborne geophysical methods (gravity, mag- netic, and electromagnetic) are widely used in the natural resource exploration at the regional scale. It covers large areas particularly in the areas with dicult access. The first part of this thesis consist on the development of new forward modeling algorithm for the calculation of the components of the gravity and magnetic fields based on a tetrahedron grid. The tetrahedral mesh allows the representation of very complex geological models holding many heterogeneous and faulted zones with an optimal number of elements, this reduces signicantly the time calcu lation. Several inversion techniques use mathematical constraints for the resolution of the inverse problem in order to reduce the number of possible models. However the proposed solutions called also "the most probable model" provide a smooth solutions that cannot represent the geological reality. To circumvent this problem in the second and the third parts of this thesis, we made two major improvements. The first, we integrate Sequential Gaussian Simulation into the inversion procedure to determine a possible distributions of a single property. The second is that we used the Co-Simulation in the case of joint inversion to estimate a posteriori probabilities of the simulated models. The last part of this thesis presents an alternative to the several variables simulation, supervised learning of neural networks allows to establish a relationship between the diferent variables.

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BibTeX Reference

@PHDTHESIS{,
    author = { Foudil Bey, Nacim },
     title = { Développement d'outils d'interprétation de données géophysiques },
      year = { 2012 },
    school = { Université de Lorraine, Université du Québec en Abitibi-Témisgamingue },
  abstract = { In recent years with the technology developments, airborne geophysical methods (gravity, mag-
netic, and electromagnetic) are widely used in the natural resource exploration at the regional
scale. It covers large areas particularly in the areas with dicult access. The first part of this
thesis consist on the development of new forward modeling algorithm for the calculation of the
components of the gravity and magnetic fields based on a tetrahedron grid. The tetrahedral
mesh allows the representation of very complex geological models holding many heterogeneous
and faulted zones with an optimal number of elements, this reduces signicantly the time calcu
lation. Several inversion techniques use mathematical constraints for the resolution of the inverse
problem in order to reduce the number of possible models. However the proposed solutions called
also "the most probable model" provide a smooth solutions that cannot represent the geological
reality. To circumvent this problem in the second and the third parts of this thesis, we made
two major improvements. The first, we integrate Sequential Gaussian Simulation into the inversion procedure to determine a possible distributions of a single property. The second is that we
used the Co-Simulation in the case of joint inversion to estimate a posteriori probabilities of the
simulated models. The last part of this thesis presents an alternative to the several variables
simulation, supervised learning of neural networks allows to establish a relationship between the
diferent variables. }
}