Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs

被引:4
作者
Liu, Wenchao [1 ]
Yang, Yuejie [1 ]
Qiao, Chengcheng [1 ]
Liu, Chen [1 ]
Lian, Boyu [1 ]
Yuan, Qingwang [2 ]
机构
[1] Univ Sci & Technol Beijing, Sch Civil & Resource Engn, Beijing 100083, Peoples R China
[2] Texas Tech Univ, Bob L Herd Dept Petr Engn, 2500 Broadway, Lubbock, TX 79409 USA
关键词
shale condensate gas; seepage law; productivity prediction; empirical method; characteristic curve analysis; artificial intelligence method; well productivity; RELATIVE PERMEABILITY; HYDROCARBONS RECOVERY; NUMERICAL-SIMULATION; STRESS SENSITIVITY; PREDICTION METHOD; ADSORPTION; FLOW; MODEL; SLIP; OIL;
D O I
10.3390/en16052446
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the continuous development of conventional oil and gas resources, the strategic transformation of energy structure is imminent. Shale condensate gas reservoir has high development value because of its abundant reserves. However, due to the multi-scale flow of shale gas, adsorption and desorption, the strong stress sensitivity of matrix and fractures, the abnormal condensation phase transition mechanism, high-speed non-Darcy seepage in artificial fractures, and heterogeneity of reservoir and multiphase flows, the multi-scale nonlinear seepage mechanisms are extremely complicated in shale condensate gas reservoirs. A certain theoretical basis for the engineering development can be provided by mastering the percolation law of shale condensate gas reservoirs, such as improvement of productivity prediction and recovery efficiency. The productivity evaluation method of shale condensate gas wells based on empirical method is simple in calculation but poor in reliability. The characteristic curve analysis method has strong reliability but a great dependence on the selection of the seepage model. The artificial intelligence method can deal with complex data and has a high prediction accuracy. Establishing an efficient shale condensate gas reservoir development simulation technology and accurately predicting the production performance of production wells will help to rationally formulate a stable and high-yield mining scheme, so as to obtain better economic benefits.
引用
收藏
页数:30
相关论文
共 157 条
[1]  
Adamson AW, 1990, The physical chemistry of surfaces
[2]  
Ambrose R.J., 2010, Society of Petroleum Engineers
[3]  
Ambrose RJ, 2011, P SPE PRODUCTION OPE
[4]  
[Anonymous], 2019, Petrophysical Characterization and Fluids Transport in Unconventional Reservoirs, DOI DOI 10.1016/B978-0-12-816698-7.00006-1
[5]  
[Anonymous], 2013, Test Method for Two Phase Relative Permeability in Rock
[6]  
[Anonymous], 2016, SPE LOW PERM S
[7]  
[Anonymous], 2003, Reservoir physics
[8]  
[Anonymous], 2014, SPE-170801-MS
[9]   ANALYSIS OF DECLINE CURVES [J].
ARPS, JJ .
TRANSACTIONS OF THE AMERICAN INSTITUTE OF MINING AND METALLURGICAL ENGINEERS, 1945, 160 :228-247
[10]  
Auerbach S.M., 2003, Handbook of Zeolite Science and Technology, V1st, DOI 10.1201/9780203911167