您的位置:首页  > 论文页面

小波变换在测井曲线识别划分岩性中的应用

发表时间:2019-08-30  浏览量:170  下载量:45
全部作者: 李亮,陈同俊,张雅雯,姜思雨
作者单位: 中国矿业大学资源与地球科学学院;中国矿业大学计算机科学与技术学院
摘 要: 以芦岭矿区L43井测井数据为样本,选取视电阻率、自然伽马射线(gamma ray,GR)、声波(acoustic,AC)时差、密度(density,DEN)测井数据,进行小波变换(wavelet transform,WT)处理。结果表明,对于此区,选用sym8小波基7 级分解后重构测井曲线,其对选段岩性响应最为明显。煤层表现为两高(高声波时差值、高视电阻率值)、两低(低密度值、低自然伽马射线值)特征,泥岩表现为两高(高密度值、高自然伽马射线值)特征。基于测井曲线小波变换的岩性识别方法,提高了测井曲线纵向分辨率和岩性识别的可靠性。
关 键 词: 固体地球物理学;测井曲线;小波多尺度变换;岩性识别
Title: Application of wavelet transform in the identification and classification of lithology in logging curves
Author: LI Liang, CHEN Tongjun, ZHANG Yawen, JIANG Siyu
Organization: School of Resources and Geosciences, China University of Mining and Technology; School of Computer Science and Technology, China University of Mining and Technology
Abstract: Taking logging data of well L43 in Luling mining area as samples, logging data of apparent resistivity, natural gamma ray (GR), acoustic (AC) time difference and density (DEN) are selected for wavelet transform (WT) processing in this paper. The results show that, for this area, the response to lithology of selected sections is the most obvious when the sym8 wavelet basis is selected and the log curve is reconstructed after 7-level decomposition. The coal seam is characterized by two high (high AC value, high apparent resistivity value) and two low (low DEN value, low natural GR value), and the mudstone is characterized by two high (high DEN value, high natural GR value). The lithology identification method based on logging curve wavelet transform improves the longitudinal resolution of logging curve and the reliability of lithology identification.
Key words: solid earth geophysics; logging curve; wavelet multi-scale transform; lithology identification
发表期数: 2019年8月第4期
引用格式: 李亮,陈同俊,张雅雯,等. 小波变换在测井曲线识别划分岩性中的应用[J]. 中国科技论文在线精品论文,2019,12(4):697-702.
 
2 评论数 0
暂无评论
友情链接