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基于压裂返排数据的致密油有效改造体积计算方法 被引量:2

An approach to calculate the effective stimulated volume of tight oil based on the flowback data after hydraulic fracturing
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摘要 为有效改善致密油井的压裂开发效果,针对当前致密油有效改造体积随时间动态变化规律难以确定的问题,将油藏工程与渗流力学理论相结合,通过对压裂返排数据的分析,反演了大庆油田典型致密油井的动态有效改造体积。结果表明:1)致密油井返排阶段的日产水量变化规律可以采用Arps模型的双曲递减(R^(2)=0.95)或调和递减(R^(2)=0.93)描述,但指数递减的误差较大;2)返排过程中裂缝内流体压力下降,在围岩应力作用下裂缝逐渐闭合,裂缝孔隙度随之减小,造成裂缝有效改造体积减小;3)计算实例表明,大庆致密油的有效改造体积在返排阶段逐渐降至初始值的75%~87%。该成果为准确高效地确定致密油动态有效改造体积,合理优化压裂改造工艺参数提供了指导。 In order to effectively improve the fracturing and development effect of tight oil wells,the dynamic effective stimulated volume of tight oil wells in Daqing Oilfield was inverted by combining reservoir engineering with seepage mechanics theory and analyzing fracturing flowback data,aiming at the problem that it is difficult to determine the dynamic change law of effective stimulated volume of tight oil wells with time.The results show that:1)The variation law of daily water production in the flowback stage of tight wells can be described by hyperbolic decline(R^(2)=0.95)or harmonic decline(R^(2)=0.93)of Arps model,but the error of exponential decline is large;2)During the flowback process,the fluid pressure in the fracture decreases,and the fracture gradually closes under the action of surrounding rock stress,the fracture porosity decreases and the effective stimulated volume of the fracture is reduced;3)The calculation examples show that the effective stimulated volume of Daqing tight oil gradually decreases to 75%~87%of the initial value during the flowback stage.The results provide guidance for accurate and efficient determination of dynamic effective stimulated volume of tight oil and reasonable optimization of fracturing process parameters.
作者 郑继明 ZHENG Jiming(Production Technology Institute of Daqing Oilfield Company Limited,Heilongjiang Daqing 163453,China)
出处 《非常规油气》 2023年第4期139-144,共6页 Unconventional Oil & Gas
基金 国家科技重大专项“松辽盆地致密油开发示范工程”(2017ZX05071)。
关键词 致密油 改造体积 水力压裂 返排数据 产量递减 tight oil stimulated volume hydraulic fracturing flowback data production decline
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