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<dc:title xml:lang="en">Fracture network characterization in enhanced geothermal systems by induced seismicity analysis</dc:title>
<dcterms:alternative xml:lang="fr">Caractérisation de réseaux de fractures dans des systèmes géothermiques stimulés (EGS) par l’analyse de la sismicité induite</dcterms:alternative>
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<dc:subject xml:lang="fr">Réseau de fractures</dc:subject>
<dc:subject xml:lang="en">Enhanced geothermal systems</dc:subject>
<dc:subject xml:lang="en">Induced seismicity</dc:subject>
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<dcterms:abstract xml:lang="fr">Le sujet de cette thèse de doctorat est l’étude de la sismicité induite dans les systèmes géothermiques améliorés afin de caractériser le réseau de fractures souterraines. La première partie de ce travail se concentre sur l’étude de cas que constitue le réservoir géothermique profond de Rittershoffen. Il est démontré comment l’intégration de techniques de traitement avancées peut conduire à une meilleure compréhension de la structure du système de failles et de sa réaction à l’injection répétée de fluide. Dans la deuxième partie de ce travail, une nouvelle méthode est proposée pour mettre en évidence le réseau de fractures dans les nuages sismiques qui ne forment pas de structures planes apparentes. Avec cette méthode, la probabilité d’avoir une fracture à un endroit donné est calculée à partir de la distribution des événements sismiques et de leurs paramètres à la source.</dcterms:abstract>
<dcterms:abstract xml:lang="en">Subject of the doctoral project is to study induced seismicity in enhanced geothermal systems to characterize the underground fracture network. The first part of this work focuses on the case study of the Rittershoffen deep geothermal reservoir. It is demonstrated how the integration of advanced processing techniques can lead to a deeper insight into the structure of the fault system and its reaction to repeated fluid injection. In the second part of this work, a new method is proposed to highlight the fracture network in seismic clouds that do not form apparent planar structures. With this method, the likelihood of having a fracture at a given location is computed from the distribution of seismic events and their source parameters.</dcterms:abstract>
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