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Renard, Philippe
Nom
Renard, Philippe
Affiliation principale
Fonction
Directeur de Recherche
Email
Philippe.Renard@unine.ch
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Résultat de la recherche
Voici les éléments 1 - 2 sur 2
- PublicationAccès libreComparing connected structures in ensemble of random fields(2016-10)
; ; Sausse, JudithVery different connectivity patterns may arise from using different simulation methods or sets of parameters, and therefore different flow properties. This paper proposes a systematic method to compare ensemble of categorical simulations from a static connectivity point of view. The differences of static connectivity cannot always be distinguished using two point statistics. In addition, multiple-point histograms only provide a statistical comparison of patterns regardless of the connectivity. Thus, we propose to characterize the static connectivity from a set of 12 indicators based on the connected components of the realizations. Some indicators describe the spatial repartition of the connected components, others their global shape or their topology through the component skeletons. We also gather all the indicators into dissimilarity values to easily compare hundreds of realizations. Heat maps and multidimensional scaling then facilitate the dissimilarity analysis. The application to a synthetic case highlights the impact of the grid size on the connectivity and the indicators. Such impact disappears when comparing samples of the realizations with the same sizes. The method is then able to rank realizations from a referring model based on their static connectivity. This application also gives rise to more practical advices. The multidimensional scaling appears as a powerful visualization tool, but it also induces dissimilarity misrepresentations: it should always be interpreted cautiously with a look at the point position confidence. The heat map displays the real dissimilarities and is more appropriate for a detailed analysis. The comparison with a multiple-point histogram method shows the benefit of the connected components: the large-scale connectivity seems better characterized by our indicators, especially the skeleton indicators. - PublicationMétadonnées seulementConnectivity of channelized sedimentary bodies: analysis and simulation strategies in subsurface modeling
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La première question nous a conduits à développer une méthode pour comparer objectivement des réalisations en se concentrant sur la connectivité. L'approche proposée s'appuie sur les composantes connexes des simulations, sur lesquelles sont calculés plusieurs indicateurs. Une représentation par positionnement multidimensionnel (MDS) facilite la comparaison des réalisations. Les observations faites grâce au MDS sont ensuite validées par une carte de chaleur et les indicateurs. L'application à un cas synthétique de complexes chenaux/levées montre les différences de connectivité entre des méthodes et des valeurs de paramètres différentes. En particulier, certaines méthodes sont loin de reproduire des objets avec une forme de chenaux.
La seconde question amène deux principaux problèmes. Premièrement, il apparaît difficile de conditionner des objets très allongés, comme des chenaux, à des données de puits ou dérivées de données sismiques. Nous nous appuyons sur une grammaire formelle, le système de Lindenmayer, pour simuler stochastiquement des objets chenaux conditionnés. Des règles de croissance prédéfinies contrôlent la morphologie du chenal, de rectiligne à sinueuse. Cette morphologie conditionne les données au fur et à mesure de son développement grâce à des contraintes attractives ou répulsives. Ces contraintes assurent le conditionnement tout en préservant au mieux la morphologie. Deuxièmement, l'organisation spatiale des chenaux apparaît peu contrôlable. Nous proposons de traiter ce problème en intégrant les processus qui déterminent l'organisation des chenaux. Un premier chenal est simulé avec un système de Lindenmayer. Puis ce chenal migre à l'aide d'une simulation gaussienne séquentielle ou d'une simulation multipoints. Cette approche reproduit les relations complexes entre des chenaux successifs sans s'appuyer sur des modèles physiques partiellement validés et au paramétrage souvent contraignant.
L'application de ces travaux à des cas synthétiques démontre le potentiel de ces approches. Elles ouvrent des perspectives intéressantes pour mieux prendre en compte la connectivité dans les simulations stochastiques de chenaux., Channels are the main sedimentary structures for sediment transportation and deposition from the continents to the ocean floor. The significant permeability of their deposits enables fluid circulation and storage. As illustrated with turbiditic systems, those channel fill is highly heterogeneous. Combined with the spatial organization of the channels, this impacts significantly the connectivity between the permeable deposits. The scarcity of the field data involves an incomplete knowledge of these subsurface reservoir architectures. In such environments, stochastic simulations are used to estimate the resources and give an insight on the associated uncertainties. Several methods have been developed to reproduce these complex environments. They raise two main concerns: how to analyze and compare the connectivity of a set of stochastic simulations? How to improve the representation of the connectivity within stochastic simulations of channels and reduce the uncertainties?
The first concern leads to the development of a method to objectively compare realizations in terms of connectivity. The proposed approach relies on the connected components of the simulations, on which several indicators are computed. A muldimensional scaling (MDS) representation facilitates the realization comparison. The observations on the MDS are then validated by the analysis of the heatmap and the indicators. The application to a synthetic case study highlights the difference of connectivity between several methods and parameter values to model channel/levee complexes. In particular, some methods are far from representing channel-shaped bodies.
Two main issues derive from the second concern. The first issue is the difficulty to simulate a highly elongated object, here a channel, conditioned to well or seismic-derived data. We rely on a formal grammar, the Lindenmayer system, to stochastically simulate conditional channel objects. Predefined growth rules control the channel morphology to simulate straight to sinuous channels. That morphology conditions the data during its development thanks to attractive and repulsive constraints. Such constraints ensure the conditioning while preserving at best the channel morphology. The second issue arises from the limited control on the channel organization. This aspect is addressed by taking into account the evolution processes underlying channel organization. An initial channel is simulated with a Lindenmayer system. Then that channel migrates using sequential Gaussian simulation or multiple-point simulation. This process reproduces the complex relationships between successive channels without relying on partially validated physical models with an often constraining parameterization.
The applications of those various works to synthetic cases highlight the potentiality of the approaches. They open up interesting prospects to better take into account the connectivity when stochastically simulating channels.