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核磁共振测井流体识别方法综述
引用本文:李鹏举,张智鹏,姜大鹏.核磁共振测井流体识别方法综述[J].测井技术,2011,35(5):396-401.
作者姓名:李鹏举  张智鹏  姜大鹏
作者单位:东北石油大学地球科学学院,黑龙江 大庆,163318
摘    要:核磁共振测井流体识别方法分为3类.常规识别方法包括差谱法(DSM)和时域分析方法(TDA),利用流体的纵向弛豫时间T1的差异识别评价流体,适合于含轻质油和天然气储层的识别;移谱法(SSM)和扩散分析法(DIFAN)利用流体扩散系数的差异识别评价流体,适合于含中等黏度油和天然气储层的识别;MRF、GIFT和SIMET方法...

关 键 词:核磁共振测井  储层  流体识别  一维谱分离  二维谱  扩散系数

Review on Fluid Identification Methods with NMR Logging
LI Pengju,ZHANG Zhipeng,JIANG Dapeng.Review on Fluid Identification Methods with NMR Logging[J].Well Logging Technology,2011,35(5):396-401.
Authors:LI Pengju  ZHANG Zhipeng  JIANG Dapeng
Affiliation:(Earth Science Institute,Northeast Petroleum University,Daqing,Heilongjiang 163318,China)
Abstract:This article classifies NMR logging fluid identification methods into three:the first is the conventional methods,including DSM,TDA,SSM,DIFAN,EDM and MRIAN;the second is separation of one-dimension spectrum,including MRF,FET,GIFT,MGTE,SIMET;The DSM and TDA use T\ difference to identify fluids and are suitable for reservoirs with light oil and gas.The SSM and DIFAN use fluid diffusion coefficient difference to recognize fluids and are suitable for the reservoirs having medium viscous oil and gas.The MRF,GIFT and SIMET use multi-fluids relaxation models to inverse echo series/signals with multiple different acquisition pa- rameters(e.g.,number of the echo waves,echo intervals and waiting time,etc.) to get each fluid’s saturation and oil viscosity,and the kike.The EDM may determine movable water volume and detect light oil.The last is two-dimension spectrum method,which is a novel method based on the two dimensions such as(T\,D) and(T2,D),etc.,and the inversed two dimensional spec- trum from this method may visually and effectively identify the reservoir fluids.The basic princi- ple,advantages and applicable conditions of these methods are described and the trend of NMR fluid identification is pointed out.
Keywords:NMR logging  reservoir  fluid identification  separation of one-dimension spectrum  two-dimension spectrum  diffusion coefficient
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