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Visualisation de données volumiques massives : application aux données sismiques

Abstract : Seismic reflection data are a valuable source of information for the three-dimensional modeling of subsurface structures in the exploration-production of hydrocarbons. This work focuses on the implementation of visualization techniques for their interpretation. We face both qualitative and quantitative challenges. It is indeed necessary to consider (1) the particular nature of seismic data and the interpretation process (2) the size of data. Our work focuses on these two distinct aspects : 1) From the qualitative point of view, we first highlight the main characteristics of seismic data. Based on this analysis, we implement a volume visualization technique adapted to the specificity of the data. We then focus on the multimodal aspect of interpretation which consists in combining several sources of information (seismic and structural). Depending on the nature of these sources (strictly volumes or both volumes and surfaces), we propose two different visualization systems. 2) From the quantitative point of view, we first define the main hardware constraints involved in seismic interpretation. Focused on these constraints, we implement a generic memory management system. Initially able to couple visualization and data processing on massive data volumes, it is then improved and specialised to build a dynamic system for distributed memory management on PC clusters. This later version, dedicated to visualization, allows to manipulate regional scale seismic data (100-200 GB) in real-time. The main aspects of this work are both studied in the scientific context of visualization and in the application context of geosciences and seismic interpretation
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Submitted on : Thursday, March 29, 2018 - 1:56:04 PM
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  • HAL Id : tel-01752737, version 1


Laurent Castanie. Visualisation de données volumiques massives : application aux données sismiques. Sciences de la Terre. Institut National Polytechnique de Lorraine, 2006. Français. ⟨NNT : 2006INPL083N⟩. ⟨tel-01752737⟩



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