基于多元逐步回归分析的煤储层含气量预测模型——以沁水盆地为例

A predictive model of gas content in coal reservoirs based on multiple stepwise regression analysis: a case study from Qinshui Basin

  • 摘要: 以沁水盆地为例,运用多元逐步回归分析方法,建立了以Langmuir体积和含气饱和度为参数的含气量预测模型;复相关系数、F检验、t检验结果表明,该模型满足线性与方差齐性的假设,拟合效果较好。运用此模型,结合多因素权重分析确定的含气饱和度和实测的Langmuir体积数据,实现了沁水盆地山西组主煤层含气量预测。对比分析显示,该含气量预测模型有一定的可行性。

     

    Abstract: Taken Qinshui Basin as an example a predictive model of gas content is established by multiple stepwise regression analysis, using Langmuir volume and gas saturation as its parameters. The result of multiple correlation coefficient testing, F-testing and t-testing indicates that the model meets the hypothesis testing of linearity and its matching effect is preferable. Based on the model and combined with gas saturation determined by the multifactor weight analysis and tested Langmuir volume data the gas content of main coal from the Shanxi Formation in the Qinshui Basin is predicted successfully. The comparative result indicates that the model is feasible to some extent.

     

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