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A fractally fractional diffusion model of composite dual-porosity for multiple fractured horizontal wells with stimulated reservoir volume in tight gas reservoirs

机译:多重裂缝水平井复合双孔隙率的分形分数扩散模型,具有刺激储层储层储层储层

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摘要

Based on fractal theory (FT) and fractional calculus (FC), a new fractally fractional diffusion model (FFDM) of composite dual-porosity has been developed to evaluate performance of multiple fractured horizontal wells (MFHWs) with stimulated reservoir volume (SRV) in tight gas reservoirs (TGRs). More specifically, FT is used to characterize the complex and heterogeneous fracture network (FN) both inside and outside of SRV, while anomalous behavior of diffusion processes both inside and outside of SRV is quantified by applying the temporal fractional derivatives. The FFDM is then solved by the Laplace transformation, line source function, the numerical discrete method, and superposition principle. The transient pressure responses are then inversely converted from Laplace domain into real time domain with the Stehfest algorithm, and the FFDM is also validated, and type curves are generated as well. Flow stages are subsequently identified together with analysis on characteristics of the type curves, especially the anomalous features different with those generated from the conventional Euclidean model. Sensitivity analyses of some related parameters have also been discussed as well. And the FFDM is then also matched with the real field well-testing data of a MFHW with SRV in a TGR. The proposed FFDM provides a new understanding of the performance of MFHWs with SRV in TGRs, which can be used to interpret the field pressure data more accurately and appropriately.
机译:基于分形理论(FT)和分数微积分(FC),已经开发了一种具有复合双孔隙率的新的分形分数扩散模型(FFDM),以评估具有刺激的储存量(SRV)的多个断裂水平孔(MFHW)的性能紧燃气藏(TGRS)。更具体地,FT用于表征SRV内部和外部的复合物和异质断裂网络(FN),而通过施加时间分数衍生物来量化SRV内部和外部的扩散过程的异常行为。然后通过拉普拉斯变换,线源功能,数值离散方法和叠加原理来解决FFDM。然后将瞬态压力响应从LAPLACE域转换为具有克菲斯特算法的实时域,并且还验证了FFDM,也产生了型曲线。随后与类型曲线的特性分析一起识别流量阶段,尤其是与传统欧几里德模型产生的那些不同的异常特征。还讨论了一些相关参数的敏感性分析。然后,FFDM也与TGR中具有SRV的MFHW的实场阱测试数据匹配。拟议的FFDM对TGR中具有SRV的MFHWS性能的新了解,可用于更准确且适当地解释现场压力数据。

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