Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficien...Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficiency. A designed unilateral Nuclear Magnetic Resonance （NMR） sensor with a Larmor frequency of 20 MHz and a well-defined constant gradient of 23.25 T/m was employed to acquire three- dimensional （3D） data for three heavy oil samples. The highly-constant gradient is advantageous for diffusion coefficient measurement of heavy oil. A fast data-implementation procedure including specially designed 3D pulse sequence and Inversion Laplace Transform （ILT） algorithm was adopted to process the data and extract 3D T1-D-T2 probability function. It indicates that NMR relaxometry and diffusometry are useful to characterize the components of heavy oil samples. NMR results were compared with independent measurements of fractionation and gas chromatography analysis.展开更多
基金financial supports from the National Science Foundation of China (Grant No.41074102 and 41130417)"111 Program,Supported by the Programme of Introducing Talents of Discipline to Universities"(B13010)Program for Changjiang Scholars and Innovative Research Team in University
文摘Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficiency. A designed unilateral Nuclear Magnetic Resonance （NMR） sensor with a Larmor frequency of 20 MHz and a well-defined constant gradient of 23.25 T/m was employed to acquire three- dimensional （3D） data for three heavy oil samples. The highly-constant gradient is advantageous for diffusion coefficient measurement of heavy oil. A fast data-implementation procedure including specially designed 3D pulse sequence and Inversion Laplace Transform （ILT） algorithm was adopted to process the data and extract 3D T1-D-T2 probability function. It indicates that NMR relaxometry and diffusometry are useful to characterize the components of heavy oil samples. NMR results were compared with independent measurements of fractionation and gas chromatography analysis.
