Temperature profile estimation: A study on the Boberg and Lantz steam stimulation model

Abstract

Cyclic steam stimulation (CSS) is widely used for production from heavy oil reservoirs where oil viscosity is manipulated by heat. Many analytical models have been developed to predict the temperature evolution in the reservoir and estimate the oil recovery. However, they often suffer from a number of assumptions which ultimately reduce their efficiency in providing a realistic prediction. In this study, a numerical solution was proposed for two-dimensional heat conduction in heavy oil reservoirs to obtain the temperature evolution during the soaking period. For a better comparison, an industry widely accepted analytical model, knows as the Boberg and Lantz steam stimulation model, together with its modified version later proposed by Bensten and Donohue were considered to examine temperature changes in a synthetic case study. The results obtained indicated that the analytical solutions overestimate the average temperature of the reservoir by 42% after 300 days of injection while the numerical formulation can provide a close prediction. This numerical approach could be a useful tool to estimate the temperature and oil production from heavy oil reservoirs.

Keywords

Thermal EOR / Steam stimulation / Finite element / Boberg and Lantz model / Temperature prediction

References

[1] R. Butler, Thermal Recovery of Oil and Bitumen, publ, GravDrain Inc.(2nd printing), Calgary, Alberta, 1997, p. 528pp.

[2] M. Mohammadi, M. Dadvar, B. Dabir, TiO 2/SiO 2 nanofluids as novel inhibitors for the stability of asphaltene particles in crude oil: mechanistic understanding, screening, modeling, and optimization, J. Mol. Liq. 238 (2017) 326-340.

[3] M. Safari, M. Mohammadi, M. Sedighi, Effect of neglecting geothermal gradient on calculated oil recovery, J. Appl. Geophys. 138 (2017) 33-39.

[4] M. Sedighi, M. Mohammadi, M. Sedighi, Green SAPO-5 supported NiO nanoparticles as a novel adsorbent for removal of petroleum asphaltenes: financial assessment, J. Pet. Sci. Eng. 171 (2018) 1433-1442.

[5] M. Sedighi, M. Mohammadi, M. Sedighi, M. Ghasemi,Biobased cadaverine as a green template in the synthesis of NiO/ZSM-5 nanocomposites for removal of petroleum asphaltenes: financial analysis, isotherms, and kinetics study, Energy Fuels 32 (7) (2018) 7412-7422.

[6] M. Mohammadi, M. Safari, M. Ghasemi, A. Daryasafar, M. Sedighi, Asphaltene adsorption using green nanocomposites: experimental study and adaptive neurofuzzy interference system modeling, J. Pet. Sci. Eng. 177 (2019) 1103-1113.

[7] M. Safari, M.J. Ameri, A. Naderifar, An efficient boundary control for porous media equation: motivated by water coning problem, Can. J. Chem. Eng. 97 (4) (2019) 888-902.

[8] N.A. Menad, Z. Noureddine, A. Hemmati-Sarapardeh, S. Shamshirband, Modeling temperature-based oil-water relative permeability by integrating advanced intelligent models with grey wolf optimization: application to thermal enhanced oil recovery processes, Fuel 242 (2019) 649-663.

[9] T. Guo, J. Wang, I.D. Gates, Pad-scale Control Improves SAGD Performance, Petroleum, 2018.

[10] Z. Yuan, P. Liu, S. Zhang, X. Li, L. Shi, R. Jin, Experimental study and numerical simulation of nitrogen-assisted SAGD in developing heavy oil reservoirs, J. Pet. Sci. Eng. 162 (2018) 325-332.

[11] H. Jia, J.J. Sheng, Simulation study of huff-n-puff air injection for enhanced oil recovery in shale oil reservoirs, Petroleum 4 (1) (2018) 7-14.

[12] S.M.T. Hosseini, S. Esfahani, M.H. Doulatabadi, A.H. Sarapardeh, A.H. Mohammadi, On the evaluation of steam assisted gravity drainage in naturally fractured oil reservoirs, Petroleum 3 (2) (2017) 273-279.

[13] F. Dianatnasab, M. Nikookar, S. Hosseini, M. Sabeti, Study of reservoir properties and operational parameters influencing in the steam assisted gravity drainage process in heavy oil reservoirs by numerical simulation, Petroleum 2 (3) (2016) 236-251.

[14] M. Mohammadpoor, F. Torabi, Extensive experimental investigation of the effect of drainage height and solvent type on the stabilized drainage rate in vapour extraction (VAPEX) process, Petroleum 1 (3) (2015) 187-199.

[15] R.M. Butler, Thermal Recovery of Oil and Bitumen, Prentice Hall, Englewood Cliffs, 1991.

[16] S. Mozaffari, M. Nikookar, M.R. Ehsani, L. Sahranavard, E. Roayaie, A.H. Mohammadi, Numerical modeling of steam injection in heavy oil reservoirs, Fuel 112 (2013) 185-192.

[17] J. Novak, N. Edmunds, M. Cimolai, A History Match of CSS Recovery in the Grosmont, Canadian International Petroleum Conference, Petroleum Society of Canada, 2007.

[18] Y. Zhang, D. Shen, X. Li, G. Liao, Y. Xu, L. Shi, Study on developing low permeability reservoir with waxy oil by cyclic steam stimulation, SPE International Thermal Operations and Heavy Oil Symposium, Society of Petroleum Engineers, 2005.

[19] A.A. Biyouki, N. Hosseinpour, A. Bahramian, A. Vatani, In-situ upgrading of reservoir oils by in-situ preparation of NiO nanoparticles in thermal enhanced oil recovery processes, Colloid. Surf. Physicochem. Eng. Asp. 520 (2017) 289-300.

[20] N. Hosseinpour, Y. Mortazavi, A. Bahramian, L. Khodatars, A.A. Khodadadi, Enhanced pyrolysis and oxidation of asphaltenes adsorbed onto transition metal oxides nanoparticles towards advanced in-situ combustion EOR processes by nanotechnology, Appl. Catal. Gen. 477 (2014) 159-171.

[21] T.C. Boberg, M.B. Rotter, S.D. Stark, History match of multiwell simulation models of the cyclic steam stimulation process at cold lake, SPE Reservoir Eng. 7 (03) (1992) 321-328.

[22] T.C. Boberg, R.B. Lantz, Calculation of the production rate of a thermally stimulated well, J. Pet. Technol. 18 (12) (1966) 1, 613-1,623.

[23] R. Bentsen, D. Donohoe, A dynamic programming model of the cyclic steam injection process, J. Pet. Technol. 21 (12) (1969) 1, 582-1,596.

[24] J. Jones, Why cyclic steam predictive models get no respect, SPE Reservoir Eng. 7 (01) (1992) 67-74.

[25] S. Chandra, Improved Steamflood Analytical Model, Texas A&M University, 2006.

[26] G. Mandl, C. Volek, Heat and mass transport in steam-drive processes, Soc. Petrol. Eng. J. 9 (01) (1969) 59-79.

[27] F. Sun, Y. Yao, G. Li, New analytical equations for productivity estimation of the cyclic CO 2-assisted steam stimulation process considering the non-Newtonian percolation characteristics, J. Pet. Explor. Prod. Technol. 9 (1) (2019) 717-723.

[28] K.-J. Bathe, Finite Element Procedures, Klaus-Jurgen Bathe (2006).

[29] J.N. Reddy, Energy and Variational Methods in Applied Mechanics: with an Introduction to the Finite Element Method, Wiley, New York, 1984.