Dossier: Quantitative Methods in Reservoir Characterization
Open Access
Issue
Oil & Gas Science and Technology - Rev. IFP
Volume 62, Number 2, March-April 2007
Dossier: Quantitative Methods in Reservoir Characterization
Page(s) 237 - 248
DOI https://doi.org/10.2516/ogst:2007020
Published online 14 June 2007
  • Cosentino L. (2001) Integrated reservoir studies. IFP Publications, Ed. Technip.
  • Deutsch C.V., Dembicki E., Yeung K. (2002) Geostatistical determination of production uncertainty: Application to Fire bag project. Center for Computational Geostatistics (CCG), University of Alberta, Edmonton, Alberta, Canada.
  • Doligez B., Beucher H., Geffroy F., Eschard R. (1999) Integrated reservoir characterization: improvement in heterogeneous stochastic modeling by integration of additional external constraints. In Schatzinger R. and Jordan J. (Eds.), Reservoir Characterization – Recent Advances, AAPG Memoir 71, 333-342.
  • Doligez B., Fournier F., Jolivet G., Gançarski S., Beucher H. (2002) Seismic facies map integration in geostatistical geological model: a field case. EAGE - 64th conference and exhibition of the European Association of Geoscientists & Engineers, Florence, 27-30 May 2002, Extended abstracts 2, 215-218.
  • Dutton S.P.,Flers W.A.,Barton M.D. (2003) Reservoir characterization of a Permian deep-water sandstone, East Ford Field, Delaware Basin, Texas. AAPG Bull. 87, 609-627. [CrossRef]
  • Eaton (2006) On the importance of geological heterogeneity for flow simulation. Sediment. Geol., 184, 187-201.
  • Galli A., Beucher H. (1997) Stochastic models for reservoir characterization: a user-friendly review. SPE38999.
  • Gomes de Souza O. Jr (1997) Stratigraphie séquentielle et modélisation probabiliste des réservoirs d'un cône sous-marin profond (Champ de Namorado, Brésil). Intégration des données géologiques et géophysiques. PhD Thesis, Université Paris 6.
  • Labourdette R., Imbert P., Insalaco E., Hegre J.A. (2005) Reservoirscale 3D sedimentary modeling: Approaches and impact of integrating sedimentology into the reservoir characterization workflow. The Future of Geological Modeling in Hydrocarbon Development Conference. The Geological Society of London, Burlington House, Piccadilly, London.
  • Johann P., Fournier F., Souza O., Eschard R., Doligez B., Beucher H. (1996) 3D stochastic reservoir modeling constrained by well and seismic data on a turbidite field. SPE36501.
  • Journel A.G.,Isaaks E.H. (1984) Conditional indicator simulation: application to a Saskatchewan uranium deposit. J. Math. Geol., 16, 685-718. [CrossRef]
  • Matheron G., Beucher H., de Fouquet C., Galli A., Guerillot D., Ravenne C. (1987) Conditional simulation of the geometry of fluvio deltaic reservoirs. SPE 62nd Annual Conference, Dallas, Texas, 591-599.
  • McLennan J.A., Deutsch C.V (2005) Ranking Geostatistical realizations by measures of connectivity. SPE/PS-CIM/CHOA 98168.
  • Moulière D., Beucher H., Hu L.Y., Fournier F., Terdich P., Melchiori F., Griffi G. (1997) Integration of seismic derived information for reservoir stochastic modeling using truncated Gaussian approach. In Baafi E.Y. and Schofield N.A. (Eds.), Geostatistics Wollongong '96, Vol. 1, Kluwer Academic Pub., Dordrecht.
  • Rudkiewicz J.L., Guérillot D., Galli A. (1990) An integrated software for stochastic modeling of reservoir lithology and property with an example from the Yorkshire Middle Jurassic. In Buller et al. (Eds), North Sea Oil and Gas reservoirs, II; Graham & Trotman Ltd., 399-406.

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.