摘要
基于传统的三重介质模型,建立了考虑基质向人工裂缝窜流和未压裂区产能贡献的裂缝性页岩气藏分段压裂水平井的三重介质产能预测模型,并得到了Laplace空间下的解析解,采用Stefest数值反演绘制了无因次产量随时间变化的双对数产量典型曲线,划分出8个流动阶段,最后对影响裂缝性页岩气藏分段压裂水平井产量典型曲线的主要因素进行了分析。分析结果表明:储容比对产量典型曲线影响较小;3个窜流系数对产量典型曲线的不同阶段有着明显不同的影响;人工裂缝半长和气藏宽度对产量典型曲线中期和后期有着较大的影响;敏感性分析也证实了基质向人工裂缝窜流和未压裂区产能贡献的必要性。研究结果为裂缝性页岩气开发动态预测提供了理论方法,对页岩气开发的产能预测和动态分析具有一定的指导意义。
Based on the traditional triple-media model, a new triple-media model is established for the productivity prediction of the staged fractured horizontal well in the fractured shale gas reservoirs considering the cross flow be- tween the matrix and artificial fractures and moreover the productivity contribution of the un-stimulated zone （ non- SRV } , the analytical solutions of the model in Laplace space are obtained, with the help of Stehfest numerical in- version, the type bilogarithmic production curves between the dimensionless rate and time are plotted, eight new flow regimes are divided, finally the main influencing factors are analyzed for the typical production curves of the staged fractured horizontal well in the fractured shale gas reservoirs. The analyses show that the storativity ratio has little effect on the production type curve; three interporosity flow coefficients have a distinct different influences on the different stages of the rate type curve ; the artificial fracture half-length and the gas reservoir width have consid- erable influences on the rate type curve at the middle and late stages; the sensitivity analysis also proves the neces- sity of the above two considerations. These research achievements provide a theoretical method for the prediction of fractured shale gas development performances, and moreover possess a certain significances for the productivity pre- diction and dynamic analysis of the shale gas development.
出处
《大庆石油地质与开发》
CAS
CSCD
北大核心
2016年第1期158-165,共8页
Petroleum Geology & Oilfield Development in Daqing
基金
国家重大科技专项(2011ZX05013-006)的部分研究内容
关键词
页岩气藏
分段压裂水平井
三重介质
典型曲线
影响因素
产能预测
shale gas reservoir
staged/segregated/segmented/fractured horizontal well
triple-media
typicalcurve
influencing factor
productivity prediction
