Heavy oil component characterization with multidimensional unilateral NMR
| Autor: | Baoxin Guo, Feng Deng, Huabing Liu, Vladimir Anferov, Lizhi Xiao, Zongfu Zhang, Sofia Anferova, Huijun Yu, Fangrong Zong |
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| Rok vydání: | 2013 |
| Předmět: |
Larmor precession
Relaxometry Laplace transform Chemistry Diffusion Analytical chemistry Energy Engineering and Power Technology Geology Probability density function Pulse sequence Fractionation Geotechnical Engineering and Engineering Geology Geophysics Fuel Technology Geochemistry and Petrology Economic Geology Gas chromatography |
| Zdroj: | Petroleum Science. 10:402-407 |
| ISSN: | 1995-8226 1672-5107 |
| Popis: | 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 T1D-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. |
| Databáze: | OpenAIRE |
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