Topological Comparisons of Fluvial Reservoir Rock Volumes Using Betti Numbers: Application to CO2 Storage Uncertainty Analysis

• Main Authors: Dahrabou, Asmae, Viseur, Sophie, Gonzalez-Lorenzo, Aldo, Rohmer, Jeremy, Bac, Alexandra, Real, Pedro, Mari, Jean-Luc, Audigane, Pascal
• Other Authors: Université de Neuchâtel = University of Neuchatel (UNINE), Centre Européen de Recherche et d'Enseignement des Géosciences de l'Environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Universidad de Sevilla = University of Seville, GMOD-LSIS (GMOD-LSIS), Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU), Bureau de Recherches Géologiques et Minières (BRGM), Alexandra Bac and Jean-Luc Mari (Eds.)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2016
• Subjects: [INFO]Computer Science [cs]; [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]; [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]; [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]; Ocean acidification
• Online Access: https://amu.hal.science/hal-01341013; https://doi.org/10.1007/978-3-319-39441-1_10

International audience To prevent the release of large quantities of CO2 into the atmosphere, carbon capture and storage (CCS) represents a potential means of mitigating the contribution of fossil fuel emissions to global warming and ocean acidification. Fluvial saline aquifers are favourite targeted reservoirs for CO2 storage. These reservoirs are very heterogeneous but their heterogeneities were rarely integrated into CO2 reservoir models. Moreover, contrary to petroleum reservoirs, the available dataset is very limited and not supposed to be enriched. This leads to wide uncertainties on reservoir characteristics required for CSS management (injection location, CO2 plume migration, etc.). Stochastic simulations are classical strategies in such under-constrained context. They aim at generating a wide number of models that all fit the available dataset. The generated models serve as support for computing the required reservoir characteristics and their uncertainties. A challenge is to optimize the uncertainty computations by selecting stochastic models that should have a priori very different flow behaviours. Fluid flows depend on the connectivity of reservoir rocks (channel deposits). In this paper, it is proposed to study the variability of the Betti numbers in function of different fluvial architectures. The aim is to quantify the impact of fluvial heterogeneities and their spatial distribution on reservoir rock topology and then on CO2 storage capacities. Representative models of different scenarios of channel stacking and their internal heterogeneities are generated using geostatistical simulation approaches. The Betti numbers are computed on each generated models and statistically analysed to exhibit if fluvial architecture controls reservoir topology.