Intitulé du poste | PhD student - 3D Modelling and IA |
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Affectation | ISTO |
Durée du contrat | 3 years |
Date de début | 1/10/2021 |
Contacts et renseignements | gautier.laurent@univ-orleans.fr |
Descriptif du poste | Geological knowledge framework and structural interpretation process for building 3D architectures of sub-surfacePh.D. thesis - Structural modellingThree-dimensional representations of sub-surface architectures are key for exploring georessources and quantitatively addressing geoscientific questions (e.g., about tectonics, magmatism). The description of such architectures encompasses a geometrical description of structural objects in a modelled area (e.g., stratigraphic layers, faults, folds) and their spatial and time relationships. This doctoral project will explore an alternative paradigm for modelling 3D geological architectures of subsurface with an improved formalism of concepts and uncertainties (Fig. 1). This project aims at (1) improving the numerical formalisation of knowledge and hypotheses embedded in the subsurface representation and (2) improving the characterization of structural uncertainties. The student in charge of this project will develop an innovative approach that implements the cognitive interpretation process applied by geologists. Its formalisation will rely on:
This new paradigm approaches geomodelling as an automated interpretation process based on artificial intelligence instead of a direct data interpolation. The proposed method will improve the integration of heterogeneous data, scale management, and exploration of epistemic uncertainties, while clarifying the structural concepts embedded in explored architectures. ProfileWe are seeking a student within a Master degree formation with components of either or both structural geosciences and numerical sciences. Candidates should be either:
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Clôture des candidatures | 20/04/2021 |
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