基于聚类的煤矿井下钻孔瞬变电磁异常响应边界成像方法  

Imaging method of borehole transient electromagnetic anomaly response boundary in coal mines based on clustering

作　　者：范涛 李萍 张幼振 赵睿 房哲 樊依林 刘磊 王程 李宇腾 FAN Tao;LI Ping;ZHANG Youzhen;ZHAO Rui;FANG Zhe;FAN Yilin;LIU Lei;WANG Cheng;LI Yuteng(Xi’an Research Institute Co.Ltd.,China Coal Technology and Engineering Group Corp.,Xi’an 710077,China;Key Scientific and Technological Innovation Team of Shaanxi Province(Geophysical Exploration Technology and Equipment Innovation Team),Xi’an 710077,China;Coal Industry Engineering Research Center(Physical Prospecting Technology and Equipment),Xi’an 710077,China)

机构地区：[1]中煤科工集团西安研究院有限公司,陕西西安710077 [2]陕西省重点科技创新团队(地球物理探测技术与装备创新团队),陕西西安710077 [3]煤炭行业工程研究中心(物探技术与装备),陕西西安710077

出　　处：《煤田地质与勘探》2022年第7期63-69,共7页Coal Geology & Exploration

基　　金：陕西省自然科学基础研究计划重点项目(2022JZ-16);天地科技股份有限公司科技创新创业资金专项项目顶层设计重点项目(2020-TD-ZD003);陕西省自然科学基础研究计划项目青年基金项目(2020JQ-994)。

摘　　要：为了提高煤矿井下钻孔瞬变电磁反演成像结果中的异常响应边界识别和解译能力,完成掘进工作面前方隐伏水害精准刻画、隐蔽致灾因素精细分析等地球物理解释,提出应用无监督机器学习中的聚类方法分析钻孔瞬变电磁处理成果。根据电阻率数值分布特征和2种聚类方法的特点,选择K-Means聚类算法对电阻率成像结果进行聚合分类;在聚类计算过程中,应用最远距离原则确定类簇的初始质心,选用欧氏距离作为距离计算方法,采用基于组内平方误差和的肘部法则确定聚类数目。针对掘进工作面前方的隐伏水害,分别采用三维数值模拟和井下现场应用实例进行了实用性和有效性验证。研究结果表明:该方法可自动识别最佳类簇数目,对电阻率实现准确聚类,聚类成像结果能改善原始成像模型的光滑过渡问题,突出异常响应边界,清晰显示异常响应形状和位置,有效帮助对钻孔瞬变电磁超前探测反演结果中的隐蔽致灾水体进行识别和归类。In order to improve the ability to recognize and interpret the abnormal response boundary in the transient electromagnetic inversion imaging results of boreholes in coal mines,and to complete geophysical interpretation such as an accurate description of hidden water disasters in front of the heading face and a fine analysis of hidden disaster-causing factors,this paper proposes the application of apply clustering method of unsupervised machine learning to analyze the borehole transient electromagnetic processing results.According to the numerical distribution characteristics of resistivity and the characteristics of the two clustering methods,the K-Means clustering algorithm is selected to aggregate and classify the resistivity imaging results.In the process of clustering calculation,the maximum distance principle is used to determine the initial centroid of the cluster,the Euclidean distance is selected as the distance calculation method,and the elbow method based on the sum of square errors is used to determine the number of clusters.In view of the hidden water disaster in the heading face,three-dimensional numerical simulation and underground field application examples are used to verify the practicability and effectiveness of this method.The results show that the method can automatically identify the optimal number of clusters and realize accurate clustering of resistivity.The clustering imaging results can improve the smooth transition problem of the original imaging model,highlight the boundary of abnormal response,clearly display the shape and position of abnormal response,and help to identify and classify hidden disaster-causing water bodies in the inversion results of borehole transient electromagnetic advanced detection.

关 键 词：钻孔瞬变电磁法 K-MEANS聚类 异常体边界 组内平方误差和 肘部法则 超前探测 

分 类 号：TD745[矿业工程—矿井通风与安全] P631.3[天文地球—地质矿产勘探]