首页|基于小波变换的铀矿测井岩性自动识别方法研究

基于小波变换的铀矿测井岩性自动识别方法研究

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无岩心钻探是铀矿勘查发展的必然趋势.提出一种基于小波变换的铀矿测井岩性自动识别方法,可为无岩心钻探的铀矿勘查提供完整的钻孔资料,满足地层岩性的精细化识别以及野外实际生产的需求.该方法首先通过标准化处理绘画不同岩性不同测井曲线的交会图,确定三侧向电阻率曲线为对岩性识别反映最敏感测井曲线;然后将归一化后的三侧向电阻率曲线进行不同小波函数相同分解尺度的小波变换和相同小波函数不同分解尺度的小波变换,与调心后的地质编录岩性对比分析,确定Haar小波函数和5层分解为对岩性识别最优的小波函数和分解尺度;最后,利用Haar小波函数和5层分解对归一化后三侧向电阻率曲线进行小波变换,得到5层分解后的低频小波系数,结合研究区块的地层和岩性资料,对不同岩性设置不同的加权系数,自动识别地层岩性.以某盆地钻孔的测井数据和地质岩性编录资料为实例,验证此方法的有效性和准确性.
Research on the automatic identifying method for sedimentary rocks in uranium logging based on wavelet transform
Core free drilling is an inevitable trend in the development of uranium exploration.This article focused on the method of lithology identification with logging uranium based on wavelet transform,which can provide complete lithology data for geology study and meet the needs of precise interpretation for practical production in the field.Firstly,the intersecting plots of different logging curves was depicted for different lithology so as to determine the most sensitive logging curve of different lithology with three lateral resistivity curve;then the wavelet transforms was preformed on the three normalized lateral resistivity logging curves with different wavelet functions and decomposition scales,and the Haar wavelet function and 5-layer decomposition were found the optimal by comparing its result with geological documentation record;next,the Haar wavelet function and 5-layer decomposition were used to process the normalized three lateral resistivity curve and obtain the low-frequency wavelet coefficients after 5-layer decomposition.Finally,the stratigraphic and lithological data of the study block were used to calculate the different weighting coefficients for different lithology and automatically identify the stratigraphic lithology.The effectiveness and accuracy of this method were verified by the drilling and logging data of a basin.

wavelet transformsandstone-type uranium depositlithological identificationlogging curvewavelet coefficient

李冬伟、李猛、李光辉、喻哲

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中核内蒙古矿业有限公司,内蒙古呼和浩特,010020

铀资源探采与核遥感全国重点实验室,北京 100029

核工业北京地质研究院,北京 100029

中核集团铀资源勘查与评价技术重点实验室,北京 100029

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小波变换 砂岩型铀矿 岩性识别 测井曲线 小波系数

2024

世界核地质科学
核工业北京地质研究院

世界核地质科学

CSTPCD
影响因子:0.463
ISSN:1672-0636
年,卷(期):2024.41(6)