翁定为, 蒋廷学, 胥云, 申坤, 张昊, 吕旭. 安塞油田重复压裂选井选层研究[J]. 石油钻采工艺, 2008, 30(4): 58-62.
引用本文: 翁定为, 蒋廷学, 胥云, 申坤, 张昊, 吕旭. 安塞油田重复压裂选井选层研究[J]. 石油钻采工艺, 2008, 30(4): 58-62.
WENG Dingwei, JIANG Tingxue, XU Yun, SHEN Kun, ZHANG Hao, LV Xu. Study on well and layer selection for refracturing in Ansai Oilfield[J]. Oil Drilling & Production Technology, 2008, 30(4): 58-62.
Citation: WENG Dingwei, JIANG Tingxue, XU Yun, SHEN Kun, ZHANG Hao, LV Xu. Study on well and layer selection for refracturing in Ansai Oilfield[J]. Oil Drilling & Production Technology, 2008, 30(4): 58-62.

安塞油田重复压裂选井选层研究

Study on well and layer selection for refracturing in Ansai Oilfield

  • 摘要: 为了提高安塞油田重复压裂的效果,进行了选井选层的深入研究。通过对安塞油田以往重复压裂效果的分析,挑选出对重复压裂效果影响明显的参数作为安塞油田重复压裂选井选层样本库参数,在此基础之上建立了各样本库参数的评价方法,进而最终建立了安塞油田重复压裂选井选层样本库。最后用模糊模式识别模型、多因素非线性生产统计模型和人工神经网络模型分别分析了安塞油田重复压裂选井选层样本库,并对3种分析结果取交集确定最优井层。通过测试样本检验,所用方法的选井选层结果与实际增产效果结果符合较好。该方法能为安塞油田下一步的重复压裂选井选层工作提供指导性意见。

     

    Abstract: Deep research on well and layer selection was performed to improve refracturing effect in Ansai Oilfield. Starting with a review of previous refracturing effect, this paper selected these parameters having obvious influence on refracturing effect as the parameters of sample database.Then evaluation method for various parameters in sample database.was presented. Finally sample database of well and layer selection for refracturing was set up in Ansai Oilfield. By the use of fuzzy pattern recognition model, multivariate non-linear statistics method and artificial neural network model, the paper analyzed the sample database separately, and intersection of three results was selected as optimal well and layer. Checked by the testing data, the optimization results are consistent with the actual effect, so the method can be used to direct the well and layer selection for refracturing in the future in Ansai Oilfield.

     

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