多元逐步回归分析法在煤层含气量预测中的应用
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摘要
煤层含气量是煤层气选区评价的重要指标,也是煤层气储量计算的重要参数。以大佛寺井田4#煤层为例,依据井田勘探阶段测试资料和煤层气井钻孔测试资料,通过相关性分析从诸多影响含气量因素中筛选出主控因素,优选运用多元逐步回归法结合主控因素建立了4#煤层含气量的预测模型,其预测值与实测值基本相符。在此基础上对未知含气量钻孔进行预测并编制出大佛寺井田4#煤层含气量等值线图,为研究区煤层气资源评价和开发选区提供重要的指导。
Coal seam gas content is an important indicator for the evaluation of CBM constituency,and is also an important parameter for the calculation of CBM reserves. We take the 4#coal seam of Dafosi Minefield as an example,according to the test data of well field and borehole test data of CBM wells,through the correlation analysis to screen out the main control factors from many factors affecting gas content,the optimization by using the multiple stepwise regression method to combine the main control. The factors established the prediction model for coal gas content of the 4#coal seam,and the predicted values are basically consistent with the measured values. On this basis, the prediction of unknown gas-bearing boreholes and the preparation of the contour map of gas content of the 4#coal seam in Dafosi Minefield provide important guidance for the evaluation and development of CBM resources in the study area.
Coal seam gas content is an important indicator for the evaluation of CBM constituency,and is also an important parameter for the calculation of CBM reserves. We take the 4#coal seam of Dafosi Minefield as an example,according to the test data of well field and borehole test data of CBM wells,through the correlation analysis to screen out the main control factors from many factors affecting gas content,the optimization by using the multiple stepwise regression method to combine the main control. The factors established the prediction model for coal gas content of the 4#coal seam,and the predicted values are basically consistent with the measured values. On this basis, the prediction of unknown gas-bearing boreholes and the preparation of the contour map of gas content of the 4#coal seam in Dafosi Minefield provide important guidance for the evaluation and development of CBM resources in the study area.
引文
[1]孟召平,田永东,雷旸.煤层含气量预测的BP神经网络模型与应用[J].中国矿业大学学报,2008,37(4):456-461.
[2] Wang Y. Coal resource evaluation and management information sys-tem in underground mines[J]. Computer Application in the Min-eral Industries,Netherlands,2011,65(1):155-158.
[3]连承波,赵永军,李汉林,等.煤层含气量的主控因素及定量预测[J].煤炭学报,2005,30(6):726-729.
[4]胡亚斐,张遂安,吴峙颖.基于地质多元统计分析的煤层气含量建模方法———以沁水盆地南部某区块3号煤层为例[J].煤田地质与勘探,2013,41(2):33-36.
[5]李静,李小彦,杨利军,等.煤层含气量预测方法[J].煤田地质与勘探,1998,26(2):31-33.
[6]秦勇,刘焕杰,范秉恒,等.山西南部上古生界煤层含气性研究:Ⅱ.推断区及预测区煤层含气性预测[J].煤田地质与勘探,1997,25(6):18-22.
[7]吴财芳,曾勇,张子戌,等.瓦斯含量地质预测的自适应神经网络技术研究[J].矿业安全与环保,2003,30(3):17-19.
[8]连承波,赵永军,渠芳,等.影响煤层含气量地质因素的定量分析[J].特种油气藏,2008,15(3):33-36.
[9]田敏,赵永军,颛孙鹏程,等.灰色系统理论在煤层气含气量预测中的应用[J].煤田地质与勘探,2008,36(2):24-27.
[10]聂怀耀,李俊生,张俊,等.焦作煤田深部煤层含气量预测[J].煤矿安全,2009(6):79-82.
[11]四达公司矿业开发部.矿井煤层气储量计算方法[A]//中国煤层气(第二届全国煤层气学术研讨会论文专辑)[C].北京,1996.
[12]连承波,赵永军,李汉林,等.基于支持向量机回归的煤层含气量预测[J].西安科技大学学报,2008,28(4):707-710.
[13]李贵红,张泓,崔永君,等.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[J].煤田地质与勘探,2005,33(6):22-25.
[14]李智学,冯勤科.大佛寺井田4煤层地质技术经济评价[J].中国煤田地质,2001,13(2):107-108.
[15]陈龙,徐建民,张河,等.大佛寺区块煤层气勘探开发现状及建议[J].中国煤层气,2017,14(6):33-37.
[16]罗凤明,邱劲飚,李明华,等.如何使用统计软件SPSS进行回归分析[J].电脑知识与技术,2008,1(2):293-294.
[2] Wang Y. Coal resource evaluation and management information sys-tem in underground mines[J]. Computer Application in the Min-eral Industries,Netherlands,2011,65(1):155-158.
[3]连承波,赵永军,李汉林,等.煤层含气量的主控因素及定量预测[J].煤炭学报,2005,30(6):726-729.
[4]胡亚斐,张遂安,吴峙颖.基于地质多元统计分析的煤层气含量建模方法———以沁水盆地南部某区块3号煤层为例[J].煤田地质与勘探,2013,41(2):33-36.
[5]李静,李小彦,杨利军,等.煤层含气量预测方法[J].煤田地质与勘探,1998,26(2):31-33.
[6]秦勇,刘焕杰,范秉恒,等.山西南部上古生界煤层含气性研究:Ⅱ.推断区及预测区煤层含气性预测[J].煤田地质与勘探,1997,25(6):18-22.
[7]吴财芳,曾勇,张子戌,等.瓦斯含量地质预测的自适应神经网络技术研究[J].矿业安全与环保,2003,30(3):17-19.
[8]连承波,赵永军,渠芳,等.影响煤层含气量地质因素的定量分析[J].特种油气藏,2008,15(3):33-36.
[9]田敏,赵永军,颛孙鹏程,等.灰色系统理论在煤层气含气量预测中的应用[J].煤田地质与勘探,2008,36(2):24-27.
[10]聂怀耀,李俊生,张俊,等.焦作煤田深部煤层含气量预测[J].煤矿安全,2009(6):79-82.
[11]四达公司矿业开发部.矿井煤层气储量计算方法[A]//中国煤层气(第二届全国煤层气学术研讨会论文专辑)[C].北京,1996.
[12]连承波,赵永军,李汉林,等.基于支持向量机回归的煤层含气量预测[J].西安科技大学学报,2008,28(4):707-710.
[13]李贵红,张泓,崔永君,等.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[J].煤田地质与勘探,2005,33(6):22-25.
[14]李智学,冯勤科.大佛寺井田4煤层地质技术经济评价[J].中国煤田地质,2001,13(2):107-108.
[15]陈龙,徐建民,张河,等.大佛寺区块煤层气勘探开发现状及建议[J].中国煤层气,2017,14(6):33-37.
[16]罗凤明,邱劲飚,李明华,等.如何使用统计软件SPSS进行回归分析[J].电脑知识与技术,2008,1(2):293-294.