Open Access
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 75, 2020
Article Number 53
Number of page(s) 18
Published online 04 August 2020
  • Aarnes J.E., Kippe V., Lie K.A. (2005) Mixed multiscale finite elements and streamline methods for reservoir simulation of large geomodels, Adv. Water Resour. 28, 3, 257–271. doi: 10.1016/j.advwatres.2004.10.007. [Google Scholar]
  • Alabert F.G., Modot V. (1992) Stochastic models of reservoir heterogeneity: Impact on connectivity and average permeabilities, in: 67th Annual Technical Conference and Exhibition of the Society of Petroleum Engineers held in Washington, DC, October 4–7, 1992, pp. 355–370. doi: 10.2118/24893-MS. [Google Scholar]
  • Allen E., Boger D.V. (1988) The influence of rheological properties on mobility control in polymer-augmented waterflooding, in: 63rd Annual Technical Conference and Exhibition of the Society of Petroleum Engineers held in Houston, TX, October 2–5, 1988, pp. 449–456. doi: 10.2118/18097-MS. [Google Scholar]
  • Aronofsky J.S. (1952) Mobility ratio – its influence on flood patterns during water encroachment, J. Pet. Technol. 4, 1, 15–24. doi: 10.2118/132-g. [CrossRef] [Google Scholar]
  • Artus V., Noetinger B. (2004) Up-scaling two-phase flow in heterogeneous reservoirs : Current trends, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 59, 2, 185–195. [CrossRef] [Google Scholar]
  • Audigane P., Blunt M.J. (2004) Dual mesh method for upscaling in waterflood simulation, Transp. Porous Media 55, 1, 71–89. doi: 10.1023/B:TIPM.0000007309.48913.d2. [Google Scholar]
  • Barker J.W., Thibeau S. (1997) A critical review of the use of pseudorelative permeabilities for upscaling, SPE Reserv. Eng. 12, 2, 138–143. doi: 10.2118/35491-PA. [CrossRef] [Google Scholar]
  • Buckley S.E., Leverett M.C. (1942) Mechanism of fluid displacement in sands, Trans. AIME 146, 1, 107–116. doi: 10.2118/942107-g. [Google Scholar]
  • Chen Z. (2007) Reservoir simulation: Mathematical techniques in oil recovery, Society for industrial and applied mathematics, Calgari, Alberta, Canada, pp. 1–6. doi: 10.1137/1.9780898717075.ch1. [Google Scholar]
  • Chen Y., Durlofsky L.J. (2006) Adaptive local – global upscaling for general flow scenarios in heterogeneous formations, Transp. Porous Media 62, 157–185. doi: 10.1007/s11242-005-0619-7. [Google Scholar]
  • Christie M.A. (1996) Upscaling for reservoir simulation, J. Pet. Technol. 48, 11, 1004–1010. doi: 10.2118/37324-JPT. [CrossRef] [Google Scholar]
  • Christie M.A., Wallstrom T.C., Durlofsky L.J., Sharp D.H., Zou Q. (2007) Effettive medium boundary conditions in upscaling, Los Alamos National Laboratory Technical Report LA-UR-00-2804. doi: 10.3997/2214-4609.201406146. [Google Scholar]
  • Colecchio I., Boschan A., Otero A.D., Noetinger B. (2020) On the multiscale characterization of effective hydraulic conductivity in random heterogeneous media: a historical survey and some new perspectives, Adv. Water Resour. 140, 103594. doi: 10.1016/j.advwatres.2020.103594. [Google Scholar]
  • Corey A.T. (1954) The interrelation between gas and oil relative permeabilites, Prod. Mon. 19, 1, 38–41. [Google Scholar]
  • Darman N.H., Pickup G.E., Sorbie K.S. (2002) A comparison of two-phase dynamic upscaling methods based on fluid potentials, Comput. Geosci. 6, 1, 5–27. doi: 10.1023/A:1016572911992. [Google Scholar]
  • Dasheng Q. (2010) Upscaling extent vs. information loss in reservoir upscaling, Pet. Sci. Technol. 28, 12, 1197–1202. doi: 10.1080/10916460903057865. [Google Scholar]
  • Deutsch C., Journel A. (1998) GSLIB Geostatistical Software Library and User’s Guide Second Edition, Oxford University Press. [Google Scholar]
  • Durlofsky L.J. (1998) Coarse scale models of two phase flow in heterogeneous reservoirs: Volume averaged equations and their relationship to existing upscaling techniques, Comput. Geosci. 2, 73–92. [Google Scholar]
  • Durlofsky L.J. (2003) Upscaling of geocellular models for reservoir flow simulation: A review of recent progress, in: 7th International Forum on Reservoir Simulation Buhl/Baden-Baden, Germany, June 23–27, 2003, pp. 1–58. [Google Scholar]
  • Durlofsky L.J. (2005) Upscaling and gridding of fine scale geological models for flow simulation, in: 8th International Forum on Reservoir Simulation Iles Borromees, Stresa, Italy, pp. 1–59. [Google Scholar]
  • Dutton S.P., Flanders W.A., Barton M.D. (2003) Reservoir characterization of a Permian deep-water sandstone, East Ford field, Delaware Basin, Texas, Am. Assoc. Pet. Geol. Bull. 87, 4, 609–627. doi: 10.1306/10100201085. [Google Scholar]
  • Dyes A.B., Caudle B.H., Erickson R.A. (1954) Oil production after breakthrough as influenced by mobility ratio, J. Pet. Technol. 6, 4, 27–32. doi: 10.2118/309-g. [CrossRef] [Google Scholar]
  • Eaton T.T. (2006) On the importance of geological heterogeneity for flow simulation, Sediment. Geol. 184, 3–4, 187–201. doi: 10.1016/j.sedgeo.2005.11.002. [CrossRef] [Google Scholar]
  • Ertekin T., Abou-Kassem J., King G. (2001) Basic applied reservoir simulation, in: A. Spivak, J.E. Killough (eds), SPE, Richardson, Texas, pp. 1–8. [Google Scholar]
  • Ganjeh-Ghazvini M. (2019) The impact of viscosity contrast on the error of heterogeneity loss in upscaling of geological models, J. Pet. Sci. Eng. 173, 681–689. doi: 10.1016/j.petrol.2018.10.061. [Google Scholar]
  • Ganjeh-Ghazvini M., Masihi M., Baghalha M. (2015a) Effect of connectivity misrepresentation on accuracy of upscaled models in oil recovery by CO2 injection, Greenh. Gases Sci. Technol. 6, 339–351. doi: 10.1002/ghg. [CrossRef] [Google Scholar]
  • Ganjeh-Ghazvini M., Masihi M., Baghalha M. (2015b) Study of heterogeneity loss in upscaling of geological maps by introducing a cluster-based heterogeneity number, Physica A 436, 1–13. doi: 10.1016/j.physa.2015.05.010. [Google Scholar]
  • Gautier Y., Noetinger B. (1997) Preferential flow-paths detection for heterogeneous reservoirs using a new renormalization technique, Transp. Porous Media 26, 1, 1–23. [Google Scholar]
  • Gautier Y., Blunt M.J., Christie M.A. (1999) Nested gridding and streamline-based simulation for fast reservoir performance prediction, Comput. Geosci. 3, 3–4, 295–320. doi: 10.2523/51931-ms. [Google Scholar]
  • Geoquest. (2010) Eclipse 100 reference manual, Schlumberger. [Google Scholar]
  • Hardy H.H., Beier R.A. (1994) Fractals in reservoir engineering, World Scientific. [CrossRef] [Google Scholar]
  • Hewett T.A. (1986) Fractal distributions of reservoir heterogeneity and their influence on fluid transport, in: 61st Annual Technical Conference and Exhibition of the Society of Petroleum Engineers, New Orieans, LA, October 5–8, 1986. doi: 10.2118/15386-MS. [Google Scholar]
  • Holden L., Nielsen B.F. (2000) Global upscaling of permeability in heterogeneous reservoirs; the Output Least Squares (OLS) method, Transp. Porous Media 40, 2, 115–143. doi: 10.1023/A:1006657515753. [Google Scholar]
  • Juanes R., Spiteri E.J., Orr F.M., Blunt M.J. (2006) Impact of relative permeability hysteresis on geological CO2 storage, Water Resour. Res. 42, 12, 1–13. doi: 10.1029/2005WR004806. [Google Scholar]
  • Karimi-Fard M., Durlofsky L.J. (2016) A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features, Adv. Water Resour. 96, 354–372. doi: 10.1016/j.advwatres.2016.07.019. [Google Scholar]
  • King P.R. (1989) The use of renormalization for calculating effective permeability, Transp. Porous Media 4, 1, 37–58. doi: 10.1007/BF00134741. [Google Scholar]
  • Kyte J.R., Berry D.W. (1975) New pseudo functions to control numerical dispersion, Soc. Pet. Eng. AIME J. 15, 4, 269–276. doi: 10.2118/5105-pa. [CrossRef] [Google Scholar]
  • Liao Q., Lei G., Zhang D., Patil S. (2019) Analytical solution for upscaling hydraulic conductivity in anisotropic heterogeneous formations, Adv. Water Resour. 128, 97–116. doi: 10.1016/j.advwatres.2019.04.011. [Google Scholar]
  • Matthai S.K., Nick H.M. (2009) Upscaling two-phase flow in naturally fractured reservoirs, Am. Assoc. Pet. Geol. Bull. 93, 11, 1621–1632. doi: 10.1306/08030909085. [Google Scholar]
  • Misaghian N., Assareh M., Sadeghi M.T. (2018) An upscaling approach using adaptive multi-resolution upgridding and automated relative permeability adjustment, Comput. Geosci. 22, 1, 261–282. doi: 10.1007/s10596-017-9688-2. [Google Scholar]
  • Muggeridge A.H., Lake L.W., Carroll H.B., Wesson T.C. (1991) Generation of effective relative permeabilities from detailed simulation of flow in heterogeneous porous media, in: Reservoir characterization II, pp. 197–225. [CrossRef] [Google Scholar]
  • Muskat M. (1938) The flow of homogeneous fluids through porous media, Soil Sci. 46, 2, 169. [Google Scholar]
  • Noetinger B., Artus V., Ricard L. (2004) Dynamics of the water – oil front for two-phase, immiscible flow in heterogeneous porous media. 2 – isotropic Media, Transp. Porous Media 56, 3, 305–328. [Google Scholar]
  • Peaceman D.W. (1997) Effective transmissibilities of a gridblock by upscaling – Comparison of direct methods with renormalization, SPE J. 2, 3, 338–349. doi: 10.2118/36722-PA. [CrossRef] [Google Scholar]
  • Pickup G.E., Ringrose P.S., Corbett P.W.M., Jensen J.L., Sorbie K.S. (1995) Geology, geometry and effective flow, Pet. Geosci. 1, 1, 37–42. doi: 10.1144/petgeo.1.1.37. [CrossRef] [Google Scholar]
  • Preux C. (2011) Study of evaluation criteria for reservoir upscaling, in: 73rd EAGE Conference & Exhibition Incorporating SPE EUROPEC, Vienna, Austria, 23–26 May. doi: 10.3997/2214-4609.20149454. [Google Scholar]
  • Preux C. (2016) About the use of quality indicators to reduce information loss when performing upscaling, Oil Gas Sci. Technol. - Rev. d’IFP Energies nouvelles 71, 1, 7. doi: 10.2516/ogst/2014023. [CrossRef] [Google Scholar]
  • Preux C., Le Ravalec M., Enchéry G. (2016) Selecting an appropriate upscaled reservoir model based on connectivity analysis, Oil Gas Sci. Technol. - Rev. d’IFP Energies nouvelles 71, 5, 60. doi: 10.2516/ogst/2016015. [CrossRef] [Google Scholar]
  • Qi D., Hesketh T. (2004) Quantitative evaluation of information loss in reservoir upscaling, Pet. Sci. Technol. 22, 11–12, 1625–1640. doi: 10.1081/LFT-200027875. [Google Scholar]
  • Rasaei M.R., Sahimi M. (2009) Upscaling of the permeability by multiscale wavelet transformations and simulation of multiphase flows in heterogeneous porous media, Comput. Geosci. 13, 2, 187–214. doi: 10.1007/s10596-008-9111-0. [Google Scholar]
  • Renard P., de Marsily G. (1997) Calculating equivalent permeability: A review, Adv. Water Resour. 20, 253–278. [Google Scholar]
  • Sablok R., Aziz K. (2008) Upscaling and discretization errors in reservoir simulation, Pet. Sci. Technol. 26, 1161–1186. doi: 10.1080/10916460701833863. [Google Scholar]
  • Sanchez-vila X., Guadagnini A., Carrera J. (2006) Representative hydraulic conductivities in saturated groundwater flow, Rev. Geophys. 44, 1–46. doi: 10.1029/2005RG000169. [Google Scholar]
  • Spiteri E.J., Juanes R. (2006) Impact of relative permeability hysteresis on the numerical simulation of WAG injection, J. Pet. Sci. Eng. 50, 2, 115–139. doi: 10.1016/j.petrol.2005.09.004. [Google Scholar]
  • Stedinger J.R., Sule B.F., Loucks D.P. (1984) Stochastic dynamic programming models for reservoir operation optimization, Water Resour. Res. 20, 11, 1499–1505. doi: 10.1029/WR020i011p01499. [Google Scholar]
  • Tan C.T., Homsy G.M. (1992) Viscous fingering with permeability heterogeneity, Phys. Fluids A 4, 6, 1099–1101. doi: 10.1063/1.858227. [CrossRef] [Google Scholar]
  • Tavakoli V. (2018) Rock typing, in: Geological core analysis application to reservoir characterization, pp. 85–99. [CrossRef] [Google Scholar]
  • Thiele M.R., Rao S.E., Blunt M.J. (1996) Quantifying uncertainty in reservoir performance using streamtubes, Math. Geol. 28, 7, 843–856. doi: 10.1007/BF02066004. [Google Scholar]
  • Zhang P., Pickup G.E., Stephen K.D., Ma J., Clark J.D. (2005) Multi-stage upscaling: Selection of suitable methods, Transp. Porous Media 58, 191–216. doi: 10.1007/1-4020-3604-3_10. [Google Scholar]

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