Optimization on fracturing fluid flowback model after hydraulic fracturing in oil well

被引:24
|
作者
Qu, Zhanqing [1 ]
Wang, Jiwei [1 ]
Guo, Tiankui [1 ]
Shen, Lin [2 ]
Liao, Hualin [1 ]
Liu, Xiaoqiang [1 ]
Fan, Jiacheng [1 ]
Hao, Tong [1 ]
机构
[1] China Univ Petr East China, Sch Petr Engn, Qingdao 266580, Peoples R China
[2] PetroChina Southwest Oil & Gas Field Co, Nat Gas Res Inst, Chengdu 610213, Peoples R China
基金
中国国家自然科学基金;
关键词
Fracturing fluid flowback; Proppant regurgitation; Proppant settlement; Flowback simulation; Optimization model; SHALE; CONDUCTIVITY; SIMULATION; FAILURE;
D O I
10.1016/j.petrol.2021.108703
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
As an important part in the process of hydraulic fracturing, fracturing fluid flowback after fracturing will directly affect the productivity of the fractured wells. It is of great significance to carry out optimization research on the flowback working system of fracturing fluid (the time of flowback beginning and the size of flowback nozzles) to enhance the efficiency of fracturing. At present, researches on optimization model of fracturing fluid flowback have taken into account the effects of fracturing fluid loss and proppant reflux, while ignoring the effects of proppant sedimentation. A new calculation model of proppant regurgitation velocity has been established in recent years, but it is rarely used in the research of flowback working system. This study innovatively integrated the calculation model of modified proppant sedimentation velocity obtained through experiments, the new calculation model of critical proppant regurgitation velocity, and the wellhead pressure calculation model to form a comprehensive flowback model of fracturing fluid. Then coupled with the flowback criteria of quickly flowback, reducing proppant reflux, and maintaining proppant settlement degree (ratio of proppant settlement distance to crack height) less than 60%, an optimization model of fracturing fluid flowback is constructed and realized by MATLAB software programs. The optimization model were verified by four fractured wells in DaQing Oilfield. The effects of reservoir permeability, reservoir porosity, fracturing fluid density, and proppant particle size on wellhead pressure drop, fracturing fluid flowback rate, and proppant settlement degree were calculated and analyzed by using the above flowback model. The verification results show that the simulated wellhead pressure and flowback flowrate are in good agreement with the actual dataset, with the average errors of 11.9% and 11.6% respectively, which proves the accuracy of the flowback optimization model. Parametric analysis shows that, with the increase of reservoir permeability and reservoir porosity, the wellhead pressure drop velocity increases. When the permeability increases from 1mD to 5mD, the flowback rate of fracturing fluid and proppant settlement degree are reduced by 12.3% and 69.8% respectively. When the porosity increases from 9% to 36%, the proppant settlement degree fall by 25.2%. Moreover, the flowback rate of fracturing fluid decreases linearly and the proppant settlement degree increases linearly with the increase of fracturing fluid density; and the proppant settlement degree increases by 3.5 times when the proppant particle size increases from 0.25 mm to 1.65 mm. Therefore, choosing smaller fracturing fluid density and smaller proppant particle size can ensure higher fluid flowback efficiency and lower proppant settlement degree.
引用
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页数:13
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