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Topological Comparisons of Fluvial Reservoir Rock Volumes Using Betti Numbers: Application to CO\(_{2}\) Storage Uncertainty Analysis

  • Asmae Dahrabou
  • Sophie ViseurEmail author
  • Aldo Gonzalez-Lorenzo
  • Jérémy Rohmer
  • Alexandra Bac
  • Pedro Real
  • Jean-Luc Mari
  • Pascal Audigane
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9667)

Abstract

To prevent the release of large quantities of CO\(_{2}\) 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 CO\(_{2}\) storage. These reservoirs are very heterogeneous but their heterogeneities were rarely integrated into CO\(_{2}\) 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, CO\(_{2}\) 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 CO\(_{2}\) 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.

Keywords

Betti Number Reservoir Rock Reservoir Model Cubical Complex Reservoir Characteristic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to thank the ParadigmGeo company and the ASGA for its support in providing the Gocad software and its research plug-ins. This project belong to the ANR H-CUBE project and the authors would like to thank the ANR for funding this research.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Asmae Dahrabou
    • 1
  • Sophie Viseur
    • 2
    Email author
  • Aldo Gonzalez-Lorenzo
    • 3
    • 4
  • Jérémy Rohmer
    • 5
  • Alexandra Bac
    • 3
  • Pedro Real
    • 4
  • Jean-Luc Mari
    • 3
  • Pascal Audigane
    • 5
  1. 1.Neuchâtel UniversityNeuchâteSwitzerland
  2. 2.Aix-Marseille Université, CEREGE UM 34, CNRS, IRDMarseilleFrance
  3. 3.Aix-Marseille Université, CNRS, LSIS UMR 7296MarseilleFrance
  4. 4.Department of Applied Mathematics IUniversity of SevilleSevilleSpain
  5. 5.BRGMOrléansFrance

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