考虑应力敏感与非达西效应的页岩气产能模型

页岩气在储层中存在解吸、扩散和渗流相互作用,同时由于其特殊的孔渗特征,裂缝闭合引起的应力敏感效应和近筒地带的高速非达西效应对页岩气产能影响不能忽略。为此,基于块状模型,综合考虑页岩气解吸、扩散,渗流,应力敏感效应以及非达西渗流,建立了页岩气藏压裂水平井产能模型,应用全隐式有限差分法和牛顿—拉普森迭代法,进行数值离散,获得产量数值解,并绘制了页岩气无因次产量和无因次产量导数曲线。分析结果表明:1页岩气流动过程分为线性流阶段、双线性流阶段、窜流阶段和边界控制流阶段;2应力敏感主要发生在双线性流和边界控制流阶段,随着应力敏感系数的增大,产能降低;3考虑非达西效应影响,页岩气产能降低,并且产能越大,非达西效应影响越显著;4兰格缪尔体积越大,兰格缪尔压力越小,无因次产量递减积分导数曲线出现下凹时间越晚。上述成果对认识页岩气藏压裂水平井产能递减规律、评价预测产能及优化压裂参数具有一定的借鉴意义。

A shale gas reservoir productivity model considering stress sensitivity and non-Darcy flow

Shale gas in the reservoir is under the interaction of desorption, diffusion and seepage; meanwhile, due to its special permeability characteristics, the effects of stress sensitivity caused by crack closure and high-speed non-Darcy flow near the wellbore on the shale gas reservoir deliverability should not be neglected. Therefore, a productivity model was established for fractured horizontal wells in shale gas reservoirs based on a block model, with comprehensive consideration of the desorption, diffusion and seepage of shale gas, stress sensitivity, and non-Darcy flow. Then, the fully implicit finite difference method and Newton-Raphson iteration method were used to work out specific production values, and a curve was drawn of shale gas dimensionless production vs. dimensionless production derivative. The analysis results demonstrate that shale gas flow will experience four main stages: linear flow, bilinear flow, cross flow, and edge-conducted flow. The stress sensitivity mainly occurs in the stages of bilinear flow and edge-conducted flow. Meanwhile, with the increase of stress sensitivity coefficient, the shale gas productivity will be decreased. The influence of non-Darcy flow will reduce the shale gas productivity; on the other hand, that will be more remarkable with the increase of productivity. The greater Langmuir volume is, the smaller Langmuir pressure is, which delays the occurrence of concave at the derivative curve of dimensionless production decline integral. These results are greatly significant for understanding the principles of production decline, predicting shale gas production and optimizing fracturing parameters.