Advanced modeling and simulation of flow in subsurface reservoirs with fractures and wells for a sustainable industry
Open Access
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 75, 2020
Advanced modeling and simulation of flow in subsurface reservoirs with fractures and wells for a sustainable industry
Numéro d'article 75
Nombre de pages 7
Publié en ligne 26 octobre 2020
  • Austin-Adigio M., Gates I. (2019) Non-condensable gas co-injection with steam for oil sands recovery, Energy 179, 736–746. [CrossRef] [Google Scholar]
  • Butler R. (1997) Thermal recovery of oil and bitumen, GravDrain’s Blackbook. [Google Scholar]
  • Chen Z., Huan G., Ma Y. (2006) Computational methods for multiphase flows in porous media. Computational science and engineering series, Vol. 2, SIAM, Philadelphia. [CrossRef] [Google Scholar]
  • Fairbridge J.K., Cey E., Gates I.D. (2012) Impact of intraformational water zones on SAGD performance, J. Pet. Sci. Eng. 82, 187–197. [Google Scholar]
  • Gao Y., Guo E., Zhang Y., Shen D., Shi J. (2017) Research on the selection of NCG in improving SAGD recovery for super-heavy oil reservoir with top-water, in: SPE Kuwait Oil & Gas Show and Conference, 15–18 October, Kuwait City, Kuwait, Society of Petroleum Engineers. [Google Scholar]
  • Hu J., Zhang C., Rui Z., Yu Y., Chen Z. (2017) Fractured horizontal well productivity prediction in tight oil reservoirs, J. Pet. Sci. Eng. 151, 159–168. [Google Scholar]
  • Ma Z., Leung J.Y. (2019) Integration of data-driven modeling techniques for lean zone and shale barrier characterization in SAGD reservoirs, J. Pet. Sci. Eng. 176, 716–734. [Google Scholar]
  • Moussa T. (2019) Performance and economic analysis of SAGD and VAPEX recovery processes, Arab. J. Sci. Eng. 44, 6, 6139–6153. [Google Scholar]
  • Ru Z., An K., Hu J. (2019) The impact of sulfur precipitation in developing a sour gas reservoir with pressure-sensitive effects, Adv. Geo-Energy Res. 3, 3, 268–276. [CrossRef] [Google Scholar]
  • Wang C., Leung J. (2015) Characterizing the effects of lean zones and shale distribution in steam-assisted-gravity-drainage recovery performance, SPE Reserv. Evalu. Eng. 18, 3, 329–345. [CrossRef] [Google Scholar]
  • Wang Z., Li Z., Sarma H.K., Xu Y., Wu P., Yang J., Lu T. (2019) A visualization experimental study on gas penetration through interlayer to improve SAGD performance, J. Pet. Sci. Eng. 177, 959–970. [Google Scholar]
  • Xu J., Chen Z., Dong X., Zhou W. (2017) Effects of lean zones on steam-assisted gravity drainage performance, Energies 10, 4, 471. [Google Scholar]
  • Xu J., Wu K., Li R., Li Z., Li J., Xu Q., Chen Z. (2018) Real gas transport in shale matrix with fractal structures, Fuel 219, 353–363. [CrossRef] [Google Scholar]
  • Yu B., Li J. (2001) Some fractal characters of porous media, Fractals 9, 3, 365–372. [Google Scholar]
  • Yu Y., Chen Z., Xu J. (2019) A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production, Adv. Geo-Energy Res. 3, 4, 375–380. [CrossRef] [Google Scholar]
  • Yuan Z., Liu P., Zhang S., Li X., Shi L., Jin R. (2018) Experimental study and numerical simulation of nitrogen-assisted SAGD in developing heavy oil reservoirs, J. Pet. Sci. Eng. 162, 325–332. [Google Scholar]
  • Zargar Z., Razavi S.M., Ali S.F. (2020) Analytical model of steam-assisted gravity drainage (SAGD) process in relation to constant injection rate, Fuel 265, 116772. [CrossRef] [Google Scholar]
  • Zhou W., Chen S., Dong M. (2016) Novel insights on initial water mobility: Its effects on steam-assisted gravity drainage performance, Fuel 174, 274–286. [CrossRef] [Google Scholar]

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