回采工作面递进式煤厚动态预测试验研究
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摘要
煤矿井下回采工作面的已知煤厚点主要分布在回风巷、运输巷与开切眼构成的"U"型巷道上,煤厚数据点分布疏密不均,除了克里格空间估值技术外,常用的钻孔煤层厚度插值方法难以适应,基于煤厚变化的准确预测对煤矿回采工作面高效开采的重要性,采用克里格空间估值技术,以"U"型巷道实际控制的煤厚"静态数据"为基础,构建煤厚预测的初始模型,开展第一阶段的煤厚预测;在回采工作面递进式推采过程中,不断融入回采新揭露的煤厚"动态数据",建立煤厚预测的优化模型,对未采区段开展递进式煤厚预测。选取某矿完成回采的S1工作面,以其"U"型巷道控制的306个煤厚点作为已知数据,以回采揭露的204个煤厚点为验证点,每50 m作为一个推采阶段,将S1工作面分为29个推采阶段,进行递进式煤厚预测的精度测试与误差分析。结果表明:(1)仅采用"U"型巷道已知煤厚点的静态数据建立预测模型,预测误差绝对值小于0.10、0.50、1.00 m的煤厚点数量分别占25.98%、74.50%和90.73%;(2)综合利用"U"型巷道与工作面递进式回采揭露的煤厚信息,构建煤厚动态预测模型,预测误差绝对值小于0.10、0.50、1.00 m的煤厚点数量,分别占48.01%、85.51%和94.86%。可见,回采工作面递进式煤厚动态预测方法,可以显著提高煤厚预测的精度。
The known coal thickness points are mainly distributed in"U"type roadway for coal mine working face,such as tail gate,head gate and starting cut. Because of the coal thickness points' uneven density,the commonly used interpolation method of seam thickness is difficult to be used except the Kriging space valuation techniques. Due to accurate prediction of coal thickness variation is very important for efficient mining of coal mining face,based on the"U"type's coal thickness"static data"to establish the initial model,it can be done for coal thickness prediction in first stage; with the development of working face,the initial model can be updated and optimized because more and more new coal thickness points is added during the mining stage,so the progressive prediction of coal thickness can be done for the unmined area.The No.S1 working face is selected as an example which has 306 known coal thickness points in"U"type roadway and204 coal thickness points exposed by mining as the verification points. Taking 50 m as a mining stage,S1 working face can be divided into29 mining stage. The result of precision test and error analysis for coal thickness progressive prediction include:(1) On the basis of the known points in"U"type roadway to establish a static prediction model,when the coal thickness absolute prediction error is less than 0.10、0.50、1.00 m,the rates of measurement points in working face are 25.98%,74.50%,90.73% in S1 working face.(2)For the progressive prediction model by collaborative coal thickness data from"U"type roadway and new data by mining,when the coal thickness absolute prediction error is less than 0.10、0.50、1.00 m,the percent of measurement points in working face are 48.01%,85.51%,94.86%respectively. It had shown that the coal thickness prediction accuracy was greatly improved by progressive prediction.
The known coal thickness points are mainly distributed in"U"type roadway for coal mine working face,such as tail gate,head gate and starting cut. Because of the coal thickness points' uneven density,the commonly used interpolation method of seam thickness is difficult to be used except the Kriging space valuation techniques. Due to accurate prediction of coal thickness variation is very important for efficient mining of coal mining face,based on the"U"type's coal thickness"static data"to establish the initial model,it can be done for coal thickness prediction in first stage; with the development of working face,the initial model can be updated and optimized because more and more new coal thickness points is added during the mining stage,so the progressive prediction of coal thickness can be done for the unmined area.The No.S1 working face is selected as an example which has 306 known coal thickness points in"U"type roadway and204 coal thickness points exposed by mining as the verification points. Taking 50 m as a mining stage,S1 working face can be divided into29 mining stage. The result of precision test and error analysis for coal thickness progressive prediction include:(1) On the basis of the known points in"U"type roadway to establish a static prediction model,when the coal thickness absolute prediction error is less than 0.10、0.50、1.00 m,the rates of measurement points in working face are 25.98%,74.50%,90.73% in S1 working face.(2)For the progressive prediction model by collaborative coal thickness data from"U"type roadway and new data by mining,when the coal thickness absolute prediction error is less than 0.10、0.50、1.00 m,the percent of measurement points in working face are 48.01%,85.51%,94.86%respectively. It had shown that the coal thickness prediction accuracy was greatly improved by progressive prediction.
引文
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[9]李红,吕进英,王宏友.波阻抗约束反演技术预测煤层厚度[J].煤田地质与勘探,2007,35(1):74-77.LI Hong,LYU Jinying,WANG Hongyou.Exploration logging-constrained inversion technique predicting coal-thickness[J].Coal Geology&Exploration,2007,35(1):74-77.
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[11]陈优阔,杨永国,张鑫,等.基于粗糙集及最小二乘支持向量机的煤层厚度预测[J].地球物理学进展,2015,30(5):2136-2141.CHEN Youkuo,YANG Yongguo,ZHANG Xin,et al.Forecasting of coal thickness based on rough set and LS-SVM[J].Progress in Geophysics,2015,30(5):2136-2141.
[12]王伟,高星,李松营,等.槽波层析成像方法在煤田勘探中的应用:以河南义马矿区为例[J].地球物理学报,2012,55(3):1054-1062.WANG Wei,GAO Xing,LI Songying,et al.Channel wave tomography method and its application in coal mine exploration:an example from Henan Yima Mining Area[J].Chinese Journal of Geophysics,2012,55(3):1054-1062.
[13]程建远,江浩,姬广忠,等.基于节点式地震仪的煤矿井下槽波地震勘探技术[J].煤炭科学技术,2015,43(2):25-28.CHENG Jianyuan,JIANG Hao,JI Guangzhong,et al.Channel wave seismic exploration technology based on node digital seismograph in underground mine[J].Coal Science and Technology,2015,43(2):25-28.
[14]李松营,廉洁,滕吉文,等.基于槽波透射法的采煤工作面煤厚解释技术[J].煤炭学报,2017,42(3):719-725.LI Songying,LIAN Jie,TENG Jiwen,et al.Interpretation technology of coal seam thickness in mining face by ISS transmission method[J].Journal of China Coal Society,2017,42(3):719-725.
[15]冯磊,杜艳艳,李松营,等.煤层厚度地震槽波层析成像分辨率分析[J].地球物理学进展,2018,33(1):197-203.FENG Lei,DU Yanyan,LI Songying,et al.Resolution analysis of in-seam seismic tomographic inversion for coal thickness[J].Progress in Geophysics,2018,33(1):197-203.
[16]宋庆军.综放工作面放煤自动化技术的研究与应用[D].徐州:中国矿业大学,2015.
[17]陈欢欢,李星,丁文秀.Surfer 8.0等值线绘制中的十二种插值方法[J].工程地球物理学报,2007,4(1):52-57.CHEN Huanhuan,LI Xing,DING Wenxiu.Twelve kinds of gridding methods of Surfer 8.0 in isoline drawing[J].Chinese Journal of Engineering Geophysics,2007,4(1):52-57.
[18]靳国栋,刘衍聪,牛文杰.距离加权反比插值法和克里金插值法的比较[J].长春工业大学学报,2003,24(3):53-57.JIN Guodong,LIU Yancong,NIU Wenjie.Comparison between inverse distance weighting method and Kriging[J].Journal of Changchun University of Technology,2003,24(3):53-57.
[19]张艳伟,屠世浩,王沉,等.基于趋势面分析的煤层厚度变化规律研究[J].西安科技大学学报,2015,35(1):21-27.ZHANG Yanwei,TU Shihao,WANG Chen,et al.Research on coal seam thickness changing law based on trend surface analysis[J].Journal of Xi’an University of Science and Technology,2015,35(1):21-27.
[20]李晓军,胡金虎,朱合华,等.基于Kriging方法的煤层厚度估计及三维煤层建模[J].煤炭学报,2008,33(7):765-769.LI Xiaojun,HU Jinhu,ZHU Hehua,et al.The estimation of coal thickness based on Kriging technique and 3D coal seam modeling[J].Journal of China Coal Society,2008,33(7):765-769.
[21]刘俊杰.地质统计学在预测煤层冲刷带中的应用研究[J].煤炭学报,2004,29(1):49-52.LIU Junjie.Application study of geostatistics to predicate washout zone in coal seam[J].Journal of China Coal Society,2004,29(1):49-52.
[22]崔洪庆,张振文,张平安.煤厚半变差函数的结构分析[J].辽宁工程技术大学学报,2003,22(3):310-312.CUI Hongqing,ZHANG Zhenwen,ZHANG Pingan.Structural analysis of half variation function of coal thickness[J].Journal of Liaoning Technical University,2003,22(3):310-312.
[23]科瓦列夫斯基E B.基于地质统计学的地质建模[M].刘应如,曹正林,郑红军,等,译.北京:石油工业出版社,2014.
[24]王家华,高海余,周叶.克里金地质绘图技术[M].北京:石油工业出版社,1999.
[2]孟凡刚,马亚杰,王国华,等.基于钻孔勘探数据的煤层厚度分布与构造预判[J].煤炭科学技术,2017,45(8):233-238.MENG Fangang,MA Yajie,WANG Guohua,et al.Seam thickness distribution and tectonic prediction based on exploration data from drilling[J].Coal Science and Technology,2017,45(8):233-238.
[3]杜文凤,彭苏萍.利用地质统计学预测煤层厚度[J].岩石力学与工程学报,2010,29(S1):2762-2767.DU Wenfeng,PENG Suping.Coal seam thickness prediction with geostatistics[J].Chinese Journal of Rock Mechanics and Engineering,2010,29(S1):2762-2767.
[4]何亚群,左蔚然,张书敏,等.基于地质统计学的煤田煤质插值方法比较[J].煤炭学报,2008,33(5):514-517.HE Yaqun,ZUO Weiran,ZHANG Shumin,et al.Comparison of interpolations for coal nature of coalfield based on geological statistics[J].Journal of China Coal Society,2008,33(5):514-517.
[5]张琳娜,樊隽轩,侯旭东,等.地层数据的常用空间插值方法介绍和比较分析:以上扬子区宝塔组厚度重建为例[J].地层学杂志,2016,40(4):420-428.ZHANG Linna,FAN Junxuan,HOU Xudong,et al.Comparison of common spatial interpolation methods in stratigraphic data analysis:a case study of the stratigraphic thickness of the Ordovician pagoda formation in the upper YANGZE region[J].Journal of Stratigraphy,2016,40(4):420-428.
[6]孟召平,郭彦省,王赟,等.基于地震属性的煤层厚度预测模型及其应用[J].地球物理学报,2006,49(2):512-517.MENG Zhaoping,GUO Yansheng,WANG Yun,et al.Prediction models of coal thickness based on seismic attributions and their applications[J].Chinese Journal of Geophysics,2006,49(2):512-517.
[7]李启成,郭雷,孙颍川,等.地震属性融合技术在煤层厚度预测中的研究[J].地球物理学进展,2017,32(5):2014-2020.LI Qicheng,GUO Lei,SUN Yingchuan,et al.Seismic attributes fusion and its research in predicting thickness of coal[J].Progress in Geophysics,2017,32(5):2014-2020.
[8]崔辉霞,杨文强,赵牧华.钻孔约束频域定量预测煤厚方法研究与应用[J].煤炭科学技术,2006,34(2):6-8.CUI Huixia,YANG Wenqiang,ZHAO Muhua.Research and application of seam thickness prediction method with borehole restrained frequency area quantified[J].Coal Science&Technology,2006,34(2):6-8.
[9]李红,吕进英,王宏友.波阻抗约束反演技术预测煤层厚度[J].煤田地质与勘探,2007,35(1):74-77.LI Hong,LYU Jinying,WANG Hongyou.Exploration logging-constrained inversion technique predicting coal-thickness[J].Coal Geology&Exploration,2007,35(1):74-77.
[10]师素珍,李赋斌,梁平,等.多井约束反演在煤层厚度定量预测中的应用[J].采矿与安全工程学报,2011,28(2):328-332.SHI Suzhen,LI Fubin,LIANG Ping,et al.Application of multiwell constrained seismic inversion in quantitative prediction of coal seam thickness[J].Journal of Mining&Safety Engineering,2011,28(2):328-332.
[11]陈优阔,杨永国,张鑫,等.基于粗糙集及最小二乘支持向量机的煤层厚度预测[J].地球物理学进展,2015,30(5):2136-2141.CHEN Youkuo,YANG Yongguo,ZHANG Xin,et al.Forecasting of coal thickness based on rough set and LS-SVM[J].Progress in Geophysics,2015,30(5):2136-2141.
[12]王伟,高星,李松营,等.槽波层析成像方法在煤田勘探中的应用:以河南义马矿区为例[J].地球物理学报,2012,55(3):1054-1062.WANG Wei,GAO Xing,LI Songying,et al.Channel wave tomography method and its application in coal mine exploration:an example from Henan Yima Mining Area[J].Chinese Journal of Geophysics,2012,55(3):1054-1062.
[13]程建远,江浩,姬广忠,等.基于节点式地震仪的煤矿井下槽波地震勘探技术[J].煤炭科学技术,2015,43(2):25-28.CHENG Jianyuan,JIANG Hao,JI Guangzhong,et al.Channel wave seismic exploration technology based on node digital seismograph in underground mine[J].Coal Science and Technology,2015,43(2):25-28.
[14]李松营,廉洁,滕吉文,等.基于槽波透射法的采煤工作面煤厚解释技术[J].煤炭学报,2017,42(3):719-725.LI Songying,LIAN Jie,TENG Jiwen,et al.Interpretation technology of coal seam thickness in mining face by ISS transmission method[J].Journal of China Coal Society,2017,42(3):719-725.
[15]冯磊,杜艳艳,李松营,等.煤层厚度地震槽波层析成像分辨率分析[J].地球物理学进展,2018,33(1):197-203.FENG Lei,DU Yanyan,LI Songying,et al.Resolution analysis of in-seam seismic tomographic inversion for coal thickness[J].Progress in Geophysics,2018,33(1):197-203.
[16]宋庆军.综放工作面放煤自动化技术的研究与应用[D].徐州:中国矿业大学,2015.
[17]陈欢欢,李星,丁文秀.Surfer 8.0等值线绘制中的十二种插值方法[J].工程地球物理学报,2007,4(1):52-57.CHEN Huanhuan,LI Xing,DING Wenxiu.Twelve kinds of gridding methods of Surfer 8.0 in isoline drawing[J].Chinese Journal of Engineering Geophysics,2007,4(1):52-57.
[18]靳国栋,刘衍聪,牛文杰.距离加权反比插值法和克里金插值法的比较[J].长春工业大学学报,2003,24(3):53-57.JIN Guodong,LIU Yancong,NIU Wenjie.Comparison between inverse distance weighting method and Kriging[J].Journal of Changchun University of Technology,2003,24(3):53-57.
[19]张艳伟,屠世浩,王沉,等.基于趋势面分析的煤层厚度变化规律研究[J].西安科技大学学报,2015,35(1):21-27.ZHANG Yanwei,TU Shihao,WANG Chen,et al.Research on coal seam thickness changing law based on trend surface analysis[J].Journal of Xi’an University of Science and Technology,2015,35(1):21-27.
[20]李晓军,胡金虎,朱合华,等.基于Kriging方法的煤层厚度估计及三维煤层建模[J].煤炭学报,2008,33(7):765-769.LI Xiaojun,HU Jinhu,ZHU Hehua,et al.The estimation of coal thickness based on Kriging technique and 3D coal seam modeling[J].Journal of China Coal Society,2008,33(7):765-769.
[21]刘俊杰.地质统计学在预测煤层冲刷带中的应用研究[J].煤炭学报,2004,29(1):49-52.LIU Junjie.Application study of geostatistics to predicate washout zone in coal seam[J].Journal of China Coal Society,2004,29(1):49-52.
[22]崔洪庆,张振文,张平安.煤厚半变差函数的结构分析[J].辽宁工程技术大学学报,2003,22(3):310-312.CUI Hongqing,ZHANG Zhenwen,ZHANG Pingan.Structural analysis of half variation function of coal thickness[J].Journal of Liaoning Technical University,2003,22(3):310-312.
[23]科瓦列夫斯基E B.基于地质统计学的地质建模[M].刘应如,曹正林,郑红军,等,译.北京:石油工业出版社,2014.
[24]王家华,高海余,周叶.克里金地质绘图技术[M].北京:石油工业出版社,1999.
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