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作 者:庄益明 宋利虎[2] 刘镜竹 ZHUANG Yiming;SONG Lihu;LIU Jingzhu(Exploration and Research Institute,CNACG,Beijing 100039,China;Geophysical Prospecting and Research Institute,CNACG,Zhuozhou 072750,China)
机构地区:[1]中国煤炭地质总局勘查研究总院,北京100039 [2]中国煤炭地质总局地球物理勘探研究院,河北涿州072750
出 处:《煤田地质与勘探》2018年第2期173-176,共4页Coal Geology & Exploration
摘 要:煤矿安全高效开采对小断层、小陷落柱等解释精度的要求越来越高,基于蚂蚁算法的地震属性分析技术能够较好地识别落差3~5 m的小断层。以淮北祁南煤矿82采区三维地震数据为例,采用蚂蚁追踪技术增强异常边界特征,从蚂蚁体沿层切片和剖面上综合分析,提高了对小断层的识别能力。利用蚂蚁追踪技术解释的18条断层异常,其中15条与实际揭露的相比,吻合率较高,验证率达83.3%。Interpretation accuracy of the small faults and collapse columns is very important in coal mine safety and efficient mining,the seismic attribute analysis technology based on ant algorithm can improve the interpretation accuracy of small faults with 3~5 m throw.In this paper,we use the 3D seismic data of the mining district No.82 in Huaibei Qinan coal mine as an example,using ant tracking technology to enhance the characteristics of abnom al boundary,the recognition ability of the small fault is improved according to the comprehensive analysis of the slice and section of the ant attributes.Compared with the actual faults in the mining district,the faults explained by the ant tracking technology revealed a relatively high coincidence rate.
分 类 号:P631[天文地球—地质矿产勘探]
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