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
Article Number 75
Number of page(s) 7
Published online 26 October 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. [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]

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.