Numerical Simulation of 3D Discrete Fracture Networks Considering Dynamic Closure of Hydraulic Fractures and Natural Fractures

doi:10.19596/j.cnki.1001-246x.8435

Abstract

Abstract:

A characterization method for fracture dynamic closure considering influence of stress state in three-dimensional space is proposed based on an embedded discrete fracture model. Aperture and permeability of fractures in any direction are considered as functions of normal effective stress acting on the fracture surface. Meanwhile, the change of fracture conductivity is used to characterize dynamic closing behavior of proppant-filled hydraulic fractures and opened natural fractures due to the decrease of formation fluid pressure during reservoir development. It shows that the development of tight oil reservoirs is dominated by "fracture-controlled reserves". In evaluating productivity of fractured horizontal wells, the dynamic closure of fractures lead to a partial loss of production, and its influence can not be ignored. Proppant material properties of hydraulic fractures, and stiffness of natural fractures are the main controlling factors. To minimize adverse impact of fracture closure on production it is necessary to increase the concentration and particle size of proppant and improve proppant properties.

Key words: tight oil reservoir, embedded discrete fracture model, fracture closure, numerical simulation, three-dimensional fracture visualization

Xu-lin DU, Lin-song CHENG, Lang-yu NIU, Yu-ming CHEN, Ren-yi CAO, Yong-hong XIE. Numerical Simulation of 3D Discrete Fracture Networks Considering Dynamic Closure of Hydraulic Fractures and Natural Fractures[J]. Chinese Journal of Computational Physics, 2022, 39(4): 453-464.

Figures/Tables 18

Fig.1 Surface stress analysis of natural fracture and hydraulic fracture (a) natural fractures; (b) hydraulic fractures; (c) embedment of proppant particles

Table 1 Regression coefficients in Barree model for different proppants[10]

	k₁	m₁	m₂	m₃	m₄	s₁	w₁
棕砂	0.000 089	2.34	2 550	2.23 × 10^-6	0	22 000	0.116 9
白砂	0.000 15	2.28	3 150	1.4 × 10^-7	0.5	27 000	0.116 4
高密度陶粒	0.000 021	2.6	3 800	3 × 10^-6	0	45 000	0.098

Fig.2 Verification of conductivity model

Fig.3 Basic model of fractured horizontal well

Table 2 Basic parameters in model verification

物理量	参数	物理量	参数
原油标况密度/(kg·m^-3)	820	原油黏度/(mPa·s)	2
基质孔隙度	0.13	基质渗透率/mD	0.1
水力压裂缝孔隙度	0.4	水力压裂缝初始渗透率/mD	20 000
水力压裂缝长度/m	200	水力压裂缝初始开度/m	0.01
水力压裂缝间距/m	200	束缚水饱和度	0.3
原始油藏压力/MPa	20	井底流压/MPa	10

Fig.4 Local grid refinement model for verification

Table 3 Conductivity change of hydraulic fracture

地层压力/MPa	水力压裂缝传导率/(mD·m)
20	86.14
18	79.95
16	74.05
14	68.48
12	63.24
11	60.74

Fig.5 Production results of static and dynamic fractures

Fig.6 Influence of proppant types and particle size

Fig.7 Influence of proppant types and proppant concentration

Fig.8 Influence of proppant particle embedding on fracture aperture reduction

Table 4 Conductivity change of hydraulic fracture

	支撑剂浓度/(g·cm^-2)	支撑剂颗粒的中值直径/μm	支撑剂类型
方案一	0.5	300	棕砂
方案二	2	300	棕砂
方案三	0.5	450	棕砂
方案四	0.5	300	高密度陶粒

Fig.9 Pressure distributions of fractured horizontal well at (a) 30 days; (b) 100 days; (c) 300 days; (d) 1000 days

Fig.10 Production curves of fractured horizontal well

Fig.11 Basic model of complex fracture networks

Fig.12 Pressure distributions of static fracture networks (left) and dynamic fracture networks (right) in different periods(a) 30 days; (b) 100 days; (c) 300 days; (d) 1000 days

Fig.13 Production curves of static fracture networks and dynamic fracture networks (a) daily oil production; (b) cumulative oil production

Fig.14 Formation pressure and production of natural fractures with different initial normal stiffness (a) formation pressure; (b) cumulative oil production

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