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页岩气藏是一种具有吸附解吸作用过程,且储层物性为特低孔渗性的特殊气藏,国内外很多学者从不同的角度出发,对页岩气渗流规律展开了研究,得到了较符合页岩气藏渗流规律的成果。通过考虑页岩气藏的纳米级孔隙特征,页岩气的吸附解吸、扩散渗流特征,结合多段压裂水平井的流体渗流模型,建立了一个新的更适用于页岩气藏的多段压裂水平井的渗流数学模型。通过引入表观渗透率函数、点源函数理论、叠加原理,Laplace变换和Stehfest数值反演等数学方法 ,得到页岩气藏多段压裂水平井井底压力的连续点源解,绘制不同条件下的压力动态曲线,将储层中流体的渗流阶段分为6个阶段,并对相关参数进行了敏感性分析,得出吸附指数、窜流系数和弹性储容比在吸附解吸阶段影响明显。将该渗流数学模型应用于国内某页岩气藏压裂水平井,模型拟合参数和实际储层测井参数误差在3%~5%,说明该模型可为页岩气藏的不稳定产能预测和评价提供理论依据。
Shale gas reservoirs are a kind of special gas reservoirs with adsorption-desorption process and reservoir properties of extra-low porosity and permeability. Many scholars at home and abroad have studied the law of seepage of shale gas from different perspectives, More in line with the law of seepage shale gas results. By considering the nanoscale pore features of shale gas reservoirs, the adsorption and desorption of shale gas, the characteristics of diffusion and percolation, combined with the fluid seepage model of multi-fractured horizontal wells, a new multistage fracturing more suitable for shale gas reservoirs Seepage Mathematical Model of Horizontal Well. Through the introduction of apparent permeability function, point source function theory, superposition principle, Laplace transform and Stehfest numerical inversion and other mathematical methods, the continuous point source solution of bottom hole pressure in multi-fractured horizontal well of shale gas reservoir is obtained. Under different conditions The pressure dynamic curve of the reservoir is divided into six phases and the sensitivity of the relevant parameters is analyzed. The results show that the adsorption index, channeling coefficient and elastic storage ratio have obvious influence on the adsorption and desorption stages. Applying the seepage mathematical model to fractured horizontal wells in a shale gas reservoir in China, the error between the model fitting parameters and the actual reservoir logging parameters is between 3% and 5%, indicating that this model can be used for unstable productivity of shale gas reservoirs Provide a theoretical basis for prediction and evaluation.