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Renard, Philippe
Nom
Renard, Philippe
Affiliation principale
Fonction
Directeur de Recherche
Email
Philippe.Renard@unine.ch
Identifiants
Résultat de la recherche
Voici les éléments 1 - 2 sur 2
- PublicationAccès libreA geostatistical approach to the simulation of stacked channels(2017)
;Rongier, G ;Collon, PTurbiditic channels evolve continuously in relation to erosion-deposition events. They are often gathered into complexes and display various stacking patterns. These patterns have a direct impact on the connectivity of sand-rich deposits. Being able to reproduce them in stochastic simulations is thus of significant importance. We propose a geometrical and descriptive approach to stochastically control the channel stacking patterns. This approach relies on the simulation of an initial channel using a Lindenmayer system. This system migrates proportionally to a migration factor through either a forward or a backward migration process. The migration factor is simulated using a sequential Gaussian simulation or a multiple-point simulation. Avulsions are performed using a Lindenmayer system, similarly to the initial channel simulation. This method makes it possible to control the connectivity between the channels by adjusting the geometry of the migrating areas. It furnishes encouraging results with both forward and backward migration processes, even if some aspects such as data conditioning still need to be explored. - PublicationAccès libreStochastic simulation of channelized sedimentary bodies using a constrained L-system(2017)
;Rongier, G ;Collon, PSimulating realistic sedimentary bodies while conditioning all the available data is a major topic of research. We present a new method to simulate the channel morphologies resulting from the deposition processes. It relies on a formal grammar system, the Lindenmayer system, or L-system. The L-system puts together channel segments based on user-defined rules and parameters. The succession of segments is then interpreted to generate non-rational uniform B-splines representing straight to meandering channels. Constraints attract or repulse the channel from the data during the channel development. They enable to condition various data types, from well data to probability cubes or a confinement. The application to a synthetic case highlights the method's ability to manage various data while preserving at best the channel morphology.