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Coal Geology & Exploration

Abstract

Nalinhe No.2 coal mine is the first pair of large-scale mines in the Nalinhe mining area. The water inrush events occur from time to time due to its own complex hydrogeological conditions and strong disturbance of excavation in the initial stage of production, which has caused serious threat to the mining activity safety. Finding the source of gushing water quickly and effectively is the key to control the mine water disaster. Based on the water quality analysis of main aquifers and goaf water samples in Nalinhe No.2 coal mine, and drawing the piper trilinear nomograph water samples, the hydrogeochemical characteristics of the groundwater in each aquifer and goaf water were revealed. Then eight indexes, snch as Ca2+, Mg2+, Na++K+, HCO3-, Cl-, SO42-, pH and salinity, were counted as the original data of water source discrimination. After the principal component analysis, four principal components F1, F2, F3 and F4 were obtained. Taking the values of these four principal components as the discriminant of the Logistic regression model, a discriminant model for gushing water sources in the Nalinhe mining area was established. Using 36 groups of standard water samples as training samples, the resubstitution accuracy was 97.22%. The established model was used to discriminate 4 groups of water samples. The research results showed that the method of principal component analysis and disordered multi-class logistic regression could eliminated redundant information effectively between the original data of the samples, and made the results of water source discrimination more rapid and accurate. It could meet the needs of mine production, and provide decision-making and basis for prevention and controlling of water inrush.

Keywords

hydrogeochemistry, principal component analysis, logistic regression method, water source judgment, Nalinhe No.2 coal mine

DOI

10.3969/j.issn.1001-1986.2020.06.012

Reference

[1] BALCH A H. Color sonagrams:A new dimension in seismic data interpretation[J]. Geophysics,1973,36(6):232-238.

[2] COLÉOU T,POUPON M,AZBEl K. Unsupervised seismic facies classification:A review and comparison of techniques and implementation[J]. The Leading Edge,2012,22(10):942-953.

[3] DE MATOS M C,OSORIO P L M,JOHANN P,et al. Unsupervised seismic facies analysis using wavelet transform and self-organizing maps[J]. Geophysics,2007,72(1):9-21.

[4] WALLET B C, DE MATOS M C, KWIATKOWSKI J T,et al. Latent space modeling of seismic data:An overview[J]. Leading Edge,2009,28(12):1454-1459.

[5] 逯宇佳,曹俊兴,刘哲哿,等. 波形分类技术在缝洞型储层流体识别中的应用[J]. 石油学报,2019,40(2):182-189. LU Yujia,CAO Junxing,LIU Zhege,et al. Application of waveform classification technology in fluid identification of fractured-vuggy reservoirs[J]. Acta Petrolei Sinica,2019,40(2):182-189.

[6] 佘刚,周小鹰,戴明刚,等. 波形分类技术在鄂北薄砂岩储层预测中的应用[J]. 石油与天然气地质,2012,33(4):536-540. SHE Gang,ZHOU Xiaoying,DAI Minggang,et al. Application of seismic waveform classification technique in thin sandstones reservoir prediction in northern Ordos Basin[J]. Oil & Gas Geology,2012,33(4):536-540.

[7] 邓传伟,李莉华,金银姬,等. 波形分类技术在储层沉积微相预测中的应用[J]. 石油物探,2008,47(3):262-265. DENG Chuanwei,LI Lihua,JIN Yinji,et al. Application of seismic waveform classification technique in prediction reservoir sedimentary microfacies[J]. Geophysical Prospecting for Petroleum,2008,47(3):262-265.

[8] COLEOU T,POUPON M,AZBEL K. Unsupervised seismic facies classification:A review and comparison of techniques and implementation[J]. The Leading Edge,2003,22(10):942-953.

[9] 石战战,王元君,唐湘蓉,等. 一种基于时频域波形分类的储层预测方法[J]. 岩性油气藏,2018,30(4):98-104. SHI Zhanzhan,WANG Yuanjun,TANG Xiangrong,et al. Reservoir detection based on seismic waveform classification in time-frequency domain[J]. Lithologic Reservoirs,2018,30(4):98-104.

[10] 郑和忠. 基于支持向量机的地震波形分类方法的研究[D]. 青岛:青岛大学,2018. ZHENG Hezhong. Research on seismic waveform classification method based on support vector machine[D]. Qingdao:Qingdao University,2018.

[11] 刘豪杰,夏同星,周学锋,等. 基于模型正演的地震波形分类技术预测优质储层[C]//中国地球科学联合学术年会,2019:1112-1115. LIU Haojie,XIA Tongxing,ZHOU Xuefeng,et al. Prediction of high quality reservoir by seismic waveform classification based on model forward modeling[C]//China Geosciences Joint Annual Meeting,2019:1112-1115.

[12] 吴微,谭绍泉,王树华,等. 基于波形分类的层位自动追踪方法[C]//SPG/SEG南京2020年国际地球物理会议. 2020:975-978. WU Wei,TAN Shaoquan,WANG Shuhua,et al. Automatic horizon tracking method based on waveform classification[C]//SPG/SEG International Geophysical conference,Nanjing,2020:975-978.

[13] 孙学凯,崔若飞. 地震相分析在探测煤层中火成岩侵入范围的应用[J]. 煤田地质与勘探,2010,38(5):58-60. SUN Xuekai,CUI Ruofei. Application of seismic faces analysis in detecting the magmatic intrusion zones[J]. Coal Geology & Exploration,2010,38(5):58-60.

[14] 杨占龙,陈启林,沙雪梅,等. 关于地震波形分类的再分类研究[J]. 天然气地球科学,2008,19(3):377-380. YANG Zhanlong,CHEN Qilin,SHA Xuemei,et al. Reclassification research of seismic waveform classification[J]. Natural Gas Geoscience,2008,19(3):377-380.

[15] 林朋,彭苏萍,卢勇旭,等. 基于共轭梯度法的全波形反演[J]. 煤田地质与勘探,2017,45(1):131-136. LIN Peng,PENG Suping,LU Yongxu,et al. Full waveform inversion based on the conjugate gradient method[J]. Coal Geology & Exploration,2017,45(1):131-136.

[16] 刘明夫. 三维地震数据体的波形分类方法研究[D]. 成都:电子科技大学,2014. LIU Mingfu. Research on waveform classification method based on 3D seismic data[D]. Chengdu:University of Electronic Science and Technology of China,2014.

[17] 范洪军,范廷恩,王晖,等. 地震波形分类技术在河流相储层研究中的应用[J]. CT理论与应用研究,2014,23(1):71-80. FAN Hongjun,FAN Ting'en,WANG Hui,et al. Application of seismic waveform classification technique in the study of fluvial reservoir[J]. CT Theory and Applications,2014,23(1):71-80.

[18] 高阳,王春贤,冯西会,等. 地震相分析技术在煤田地震勘探中的应用[J]. 煤田地质与勘探,2016,44(1):107-111. GAO Yang,WANG Chunxian,FENG Xihui,et al. Application of seismic facies analysis technology in coal seismic exploration[J]. Coal Geology & Exploration,2016,44(1):107-111.

[19] 秦永军,马丽,薛海军,等. 地震波形分类技术在煤层分叉解释中的应用[J]. 中国煤炭地质,2016,28(10):76-80. QIN Yongjun,MA Li,XUE Haijun,et al. Application of seismic waveform classification technology in coal seam bifurcation interpretation[J]. Coal Geology of China,2016,28(10):76-80.

[20] 江青春,王海,李丹,等. 地震波形分类技术应用条件及其在葡北地区沉积微相研究中的应用[J]. 石油与天然气地质,2012,33(1):135-140. JIANG Qingchun,WANG Hai,LI Dan,et al. Application conditions of seismic waveform classification technique and its use in the study of sedimentary microfacies of Pubei area[J]. Oil & Gas Geology,2012,33(1):135-140.

[21] 杨文强. 孙疃矿中组煤层地震相分析与煤厚预测[D]. 徐州:中国矿业大学,2019. YANG Wenqiang. Seismic facies analysis and seam thickness prediction of the Middle Coal seam in Suntuan Mine[D]. Xuzhou:China University of Mining and Technology,2019.

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