dc.creator | Dahrabou, Asmae | es |
dc.creator | Viseur, Sophie | es |
dc.creator | González Lorenzo, Aldo | es |
dc.creator | Rohmer, Jérémy | es |
dc.creator | Bac, Alexandra | es |
dc.creator | Real Jurado, Pedro | es |
dc.creator | Mari, Jean-Luc | es |
dc.creator | Audigane, Pascal | es |
dc.date.accessioned | 2021-10-01T09:20:04Z | |
dc.date.available | 2021-10-01T09:20:04Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Dahrabou, A., Viseur, S., González Lorenzo, A., Rohmer, J., Bac, A., Real Jurado, P.,...,Audigane, P. (2016). Topological Comparisons of Fluvial Reservoir Rock Volumes Using Betti Numbers: Application to CO2 Storage Uncertainty Analysis. En CTIC 2016: 6th International Workshop on Computational Topology in Image Context (101-112), Marseille, France: Springer. | |
dc.identifier.isbn | 978-3-319-39440-4 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/126413 | |
dc.description.abstract | 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. | es |
dc.format | application/pdf | es |
dc.format.extent | 12 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | CTIC 2016: 6th International Workshop on Computational Topology in Image Context (2016), pp. 101-112. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Topological Comparisons of Fluvial Reservoir Rock Volumes Using Betti Numbers: Application to CO2 Storage Uncertainty Analysis | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) | es |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-319-39441-1_10 | es |
dc.identifier.doi | 10.1007/978-3-319-39441-1_10 | es |
dc.publication.initialPage | 101 | es |
dc.publication.endPage | 112 | es |
dc.eventtitle | CTIC 2016: 6th International Workshop on Computational Topology in Image Context | es |
dc.eventinstitution | Marseille, France | es |
dc.relation.publicationplace | Cham, Switzerland | es |
dc.identifier.sisius | 21021332 | es |