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Predicating reservoir sensitivity rapidly with single-correlation analysis and multiple regression

机译:用单相关分析和多元回归迅速探测储层敏感性

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Sensitivity analysis is the premise of studying reservoir-damage mechanism, meanwhile it is also extremely significant to optimize each work link during exploratory boring and development process, and to formulate systemic reservoir-protection technology solutions. After discussing various reservoir-sensitivity prediction methods developed in recent years, we have found that it's an ideal, fast, new method to use single-correlation analysis and multiple regression to predicate reservoir sensitivity. On the basis of conventional core analysis and sensitive mineral analysis, we extract information relevant to every sensitivity, and use the new method above mentioned to predict reservoir-sensitivity, the accuracy of forecasting results can reach 85%, basically meet the needs of reservoir sensitivity predicted. Compared with single methods, the method combined single-correlation analysis and multiple regression is obviously improved when predicate reservoir sensitivity, and it is simple, widely applicable and with explicit physical significance.
机译:敏感性分析是研究水库损伤机制的前提,同时优化探索性镗孔和开发过程中的每个工作链接也非常重要,并制定全身储层保护技术解决方案。在讨论近年来开发的各种储层灵敏度预测方法之后,我们发现它是使用单相关分析和多元回归到谓词储层灵敏度的理想,快速,新的方法。在常规核心分析和敏感矿物分析的基础上,我们提取与每个灵敏度相关的信息,并使用上述新方法预测储层敏感性,预测结果的准确性可达85%,基本上满足储层灵敏度的需求预料到的。与单个方法相比,当谓式储层灵敏度时,该方法组合单相关分析和多元回归明显改善,并且简单,广泛适用,具有明确的物理意义。

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