scholarly journals Functions of capillary pressure and dissolution in the CO2-flooding process in low-permeability reservoirs

2020 ◽  
Vol 10 (5) ◽  
pp. 1881-1890
Author(s):  
Xiaoliang Huang ◽  
Zhilin Qi ◽  
Wende Yan ◽  
Yingzhong Yuan ◽  
Jie Tian ◽  
...  
2020 ◽  
Vol 194 ◽  
pp. 01041
Author(s):  
Zhaoxia LIU ◽  
Ming GAO ◽  
Shanyan ZHANG ◽  
Wanlu LIU

With the shortage of recoverable reserves in conventional oil reservoirs, the development of low-permeability oil reservoirs has received more and more attention. The oil recovery of low-permeability reservoirs can be significantly improved by CO2 flooding, as it can effectively supply formation energy. CO2 flooding is an effective technology for increasing oil production in low-permeability reservoirs. However, because of the heterogeneity of the reservoir and the effect of natural fractures, CO2 gas channelling easily occurs during CO2 flooding, seriously reducing CO2 flooding effect. In this study, the gas channelling technology of acid-resistant gel foam was investigated. Preferred acid-resistant gel foam system formula was found as 0.1% by mass of AOS foaming agent with 0.3% to 0.4% by mass of instant HPAM polymer and 1% to 2% by mass of water-soluble phenolic resin crosslinking agent. This system still has a good foaming ability and blocking performance under at pH=2 and a salinity of 10×104 mg/L. After 60 days of aging under oil reservoir conditions, there is no obvious water separation, and the plugging strength retention rate reached more than 60%. The gel foam channelling system can be applied to highly heterogeneous and low permeability reservoirs with a permeability gradient higher than 14 and can increase the recovery rate by more than 20% based on the CO2 flooding. Acid-resistant gel foam channelling technology can effectively inhibit CO2 gas channelling and improve CO2 flooding effect in low permeability reservoirs.


Fractals ◽  
2020 ◽  
Vol 28 (03) ◽  
pp. 2050055
Author(s):  
HAIBO SU ◽  
SHIMING ZHANG ◽  
YEHENG SUN ◽  
XIAOHONG WANG ◽  
BOMING YU ◽  
...  

Oil–water relative permeability curve is an important parameter for analyzing the characters of oil and water seepages in low-permeability reservoirs. The fluid flow in low-permeability reservoirs exhibits distinct nonlinear seepage characteristics with starting pressure gradient. However, the existing theoretical model of oil–water relative permeability only considered few nonlinear seepage characteristics such as capillary pressure and fluid properties. Studying the influences of reservoir pore structures, capillary pressure, driving pressure and boundary layer effect on the morphology of relative permeability curves is of great significance for understanding the seepage properties of low-permeability reservoirs. Based on the fractal theory for porous media, an analytically comprehensive model for the relative permeabilities of oil and water in a low-permeability reservoir is established in this work. The analytical model for oil–water relative permeabilities obtained in this paper is found to be a function of water saturation, fractal dimension for pores, fractal dimension for tortuosity of capillaries, driving pressure gradient and capillary pressure between oil and water phases as well as boundary layer thickness. The present results show that the relative permeabilities of oil and water decrease with the increase of the fractal dimension for tortuosity, whereas the relative permeabilities of oil and water increase with the increase of pore fractal dimension. The nonlinear properties of low-permeability reservoirs have the prominent significances on the relative permeability of the oil phase. With the increase of the seepage resistance coefficient, the relative permeability of oil phase decreases. The proposed theoretical model has been verified by experimental data on oil–water relative permeability and compared with other conventional oil–water relative permeability models. The present results verify the reliability of the oil–water relative permeability model established in this paper.


2014 ◽  
Vol 11 (2) ◽  
pp. 279-286 ◽  
Author(s):  
Fenglan Zhao ◽  
Lei Zhang ◽  
Jirui Hou ◽  
Shujun Cao

2009 ◽  
Vol 6 (3) ◽  
pp. 277-283 ◽  
Author(s):  
Rui Wang ◽  
Xiang’an Yue ◽  
Renbao Zhao ◽  
Pingxiang Yan ◽  
Dave Freeman

2019 ◽  
Vol 182 ◽  
pp. 106305 ◽  
Author(s):  
Mingchen Ding ◽  
Yefei Wang ◽  
Wei Wang ◽  
Hailong Zhao ◽  
Dexin Liu ◽  
...  

Fuel ◽  
2019 ◽  
Vol 241 ◽  
pp. 442-450 ◽  
Author(s):  
Yan Zhang ◽  
Mingwei Gao ◽  
Qing You ◽  
Hongfu Fan ◽  
Wenhui Li ◽  
...  

2011 ◽  
Author(s):  
Rui Wang ◽  
Cheng Yuan Lv ◽  
Zengmin Lun ◽  
Xiang-an Yue ◽  
Renbao Zhao ◽  
...  

2012 ◽  
Vol 39 (3) ◽  
pp. 405-411 ◽  
Author(s):  
Shubao TIAN ◽  
Gang LEI ◽  
Shunli HE ◽  
Limin YANG

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