翁定为, 付海峰, 卢拥军, 郑力会, 马建军. 储层改造体积预测模型的研究与应用[J]. 石油钻探技术, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018
引用本文: 翁定为, 付海峰, 卢拥军, 郑力会, 马建军. 储层改造体积预测模型的研究与应用[J]. 石油钻探技术, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018
WENG Dingwei, FU Haifeng, LU Yongjun, ZHENG Lihui, MA Jianjun. A Model for Predicting the Volume of Stimulated Reservoirs[J]. Petroleum Drilling Techniques, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018
Citation: WENG Dingwei, FU Haifeng, LU Yongjun, ZHENG Lihui, MA Jianjun. A Model for Predicting the Volume of Stimulated Reservoirs[J]. Petroleum Drilling Techniques, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018

储层改造体积预测模型的研究与应用

A Model for Predicting the Volume of Stimulated Reservoirs

  • 摘要: 为进一步明确储层改造体积内涵,完善体积改造技术及提高改造体积预测的准确性,采用物理模拟试验分析了声波事件与裂缝形态的关系,并基于物理模拟试验结果建立了储层改造体积预测模型。利用建立的模型计算了不同导流能力、不同压裂液黏度以及不同缝内净压力下的储层改造体积,计算结果表明:储层改造体积与压裂液黏度呈反比关系,与裂缝导流能力和缝内净压力呈线性关系;压裂液黏度对储层改造体积的影响最大,裂缝导流能力次之,缝内净压力最小。利用所建模型对国内某油田7口压裂井的致密储层改造体积进行了预测,并拟合了预测储层改造体积与压裂后试油产量的关系,两者呈线性关系,相关系数为0.840。这表明,所建模型预测的储层改造体积与压裂后试油产量具有较好的相关性,可以利用其指导体积压裂。

     

    Abstract: In order to better understand the stimulated reservoir volume (SRV), to improve the SRV technology and predict it more accurately, large-scale physical simulation tests were deployed to analyze the relationship between acoustic events and fracture morphology. Based on the results of the physical simulation tests, a SRV predicting model was built for calculating the stimulated reservoir volumes with different fracture conductivity, the viscosity of fracturing fluid and net pressure. The result showed that calculated SRV is in inverse proportion to fracturing fluid viscosity, and in linear relationship with both fracture conductivity and net pressure. The SRV is the most sensitive to fracturing fluid viscosity, followed by fracture conductivity, and then the least to net pressure. The SRV model has been used to predict the stimulated reservoir volume in 7 fractured wells in a domestic tight oil field, the fitting curve for SRVs and post-fracturing oil production rate was made to be a linear relationship, with the coefficient of correlation 0.840. It is indicated that the SRV predicting model was in better correlation with the post-fracturing oil production rate, which, in the future, can be taken as the guidance of SRV fracturing.

     

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