EMD滤波方法在NMR测井中的应用  

Application of EMD Filtering Method in NMR Logging

作　　者：程诚[1] 程晶晶[1] 王光伟[2] 薛志波[2] 

机构地区：[1]华中科技大学控制科学与工程系,湖北武汉430074 [2]中海油田服务股份有限公司,北京101149

出　　处：《武汉理工大学学报（信息与管理工程版）》2014年第2期176-179,206,共5页Journal of Wuhan University of Technology：Information & Management Engineering

基　　金：教育部博士点专项科研基金资助项目(20130142120065)

摘　　要：核磁共振测井中,回波信号的信噪比对T2谱反演及后续地层解释评价过程有重要影响。基于核磁共振测井信号与噪声的分析,提出了一种采用自适应性较强的经验模态分解(EMD)算法对核磁共振测井原始数据作消噪处理。结果表明,采用该滤波算法,实验室回波数据信噪比由22 dB提高到46 dB,标准油井回波数据信噪比由11 dB提高到31 dB,反演得到的T2分布更加精确,多次重复测量中孔隙度结果有较高的一致性。The signal-to-noise ratio of the echo signal has an important impact on the T2 spectrum inversion and subsequent stratigraphic interpretation evaluation process in the nuclear magnetic resonance logging （ NMRL） .Based on the analysis of NMRL signals and noise , the empirical mode de-composition （ EMD） algorithm with strong adaptive was used to de -noising the NMR logging raw data .The results show that using the designed filtering algorithm , the signal-to-noise ratio of the laboratory echo data is increased from 22 dB to 46 dB, the signal-to-noise ratio of the standard wells echo data is increased from 11 dB to 31 dB.The T2 inversion results are more accurate , and the porosity results in the repeated measurements have higher consistency .

关 键 词：经验模态分解( EMD) 回波串 T2谱 核磁共振测井 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]