Application of multivariate Regression Analysis in Coal Seam Gas Content Prediction
LIU Zheng
DENG Guangzhe
LIU Xiaojun
Abstract：Based on a large number of parameters of coal seam gas content in a mine and by using the mathematical model of multivariate regression analysis, a multivariate regression equation for the prediction of seam gas content was established, the significance of the equation and its coefficient were tested and the studentized residual analysis was carried out. This equation can objectively reflect the influence relation of the buried depth and thickness of coal seams, the geological structure, the roof and floor lithology of the seam and the metamorphic grade of coal with the seam gas content. The results indicated that this method has very high accuracy and can provide an effective way for the prediction of seam gas content in a mine.
Keywords：coal seam gas contentmultivariate regression analysisstudentized residualprediction
Publication Date：2013-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 52-55 )