Numerical Simulation of Water-flooding Reservoirs Considering Permeability Time Variation Based on Mimetic Finite Difference Method

doi:10.19596/j.cnki.1001-246x.8628

Abstract

Abstract:

Since physical properties time variation influences the remaining oil distribution and reservoir development effect, a new method to simulate permeability time variation properties based on mimetic finite difference method is put forward. Firstly, well test permeability is fitted, and a water flooding mathematical model considering the variation of permeability based on scouring time of injected water is proposed. The model is discretized using mimetic finite difference method, which is described in details. Finally, an IMPES scheme is used for the solution of the model and the influence of different permeability multiples on distribution of residual oil, pressure, and streamline is analyzed. The results show that, when the permeability changes with time, more water channeling can occur, inducing a negative effect on oil production. Compared to traditional reservoir characterization methods, this technology reflects real condition of the block and can provide useful guidelines for further production optimization.

Key words: mimetic finite difference method, absolute permeability time variation, numerical simulation, water-flooding reservoirs

Shaochun WANG, Shuoran FU, Lingkong GUO, Zhihao TANG, Na ZHANG, Qian SUN. Numerical Simulation of Water-flooding Reservoirs Considering Permeability Time Variation Based on Mimetic Finite Difference Method[J]. Chinese Journal of Computational Physics, 2023, 40(5): 597-605.

Figures/Tables 10

Fig.1 Permeability variation of well test in K oilfield

Fig.2 Evolution of dimensionless permeability with T0

Fig.3 Numerical simulation calculation process

Fig.4 Schematic of grid-cell of MFD

Fig.5 Conceptual model (a)physical model; (b)meshing

Table 1 Permeability time-varying simulation parameters

组别	最小渗透率/mD	最大渗透率/mD	原油黏度/(mPa·s)	水黏度/(mPa·s)	束缚水饱和度/%	残余油饱和度/%	孔隙度/%	油密度/(kg·m^-3)	水密度/(kg·m^-3)
a	50	50	3.5	1	20	20	25	800	1 000
b	50	500	3.5	1	20	20	25	800	1 000
c	50	1 000	3.5	1	20	20	25	800	1 000
d	50	2 000	3.5	1	20	20	25	800	1 000

Fig.6 Water saturation distributions (a)50-50; (b)50-500; (c)50-1000; (d)50-2000

Fig.7 Pressure distributions (a)50-50; (b)50-500; (c)50-1000; (d)50-2000

Fig.8 Streamline distributions (a)50-50; (b)50-500; (c)50-1000; (d)50-2000

Fig.9 Variation curves of sweep efficiency

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