Low-field nuclear magnetic resonance for petroleum distillate characterization

被引:22
|
作者
Barbosa, Lucio L. [1 ]
Kock, Flavio V. C. [1 ]
Almeida, Vinicius M. D. L. [1 ]
Menezes, Sonia M. C. [2 ]
Castro, Eustaquio V. R. [1 ]
机构
[1] Univ Fed Espirito Santo, Dept Chem, Vitoria, ES, Brazil
[2] Petrobras Cenpes QM, Ilha Fundao, BR-21941598 Rio De Janeiro, RJ, Brazil
关键词
Low-field NMR; Petroleum; Petroleum fractions; Distillates; POROUS-MEDIA; CRUDE-OIL; NMR; DIFFUSION; TRANSVERSE; GRADIENT;
D O I
10.1016/j.fuproc.2015.05.027
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Low field nuclear magnetic resonance (LF-NMR) has several applications in the oilfield industry such as in predicting the viscosity and evaluating porosity, permeability, fluid saturation of reservoir rocks, and the water content in fluids. However, the studies to determine the physical and chemical properties of petroleum distillates are uncommon. So, the aim of this study was to determine the physical and chemical properties of distillates using the transverse relaxation time (T-2) in the range from 73.43 to 1810.74 ms. LF-NMR was employed in this research, due to its rapid and non-destructive analytical method. From LF-NMR data, it was possible to estimate the molar mass, correlation index, characterization factor, API gravity, relative hydrogen index, and number of hydrogen in distillates obtained up to 350 degrees C. T-2 and the properties determined by standard methodologies (ASTM D-1218, D-445-06, D-664-06, D-2892, and D-4052) were strongly correlated. So, low field NMR constitutes an interesting alternative to ASTM methods. The results also show that changes in the chemical and physical properties depend on boiling point and molecular mobility. Besides, LF-NMR enabled the classification of the fractions into gasoline, kerosene, and light and heavy gas oil. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:202 / 209
页数:8
相关论文
共 50 条
  • [31] A field study of nuclear magnetic resonance logging to quantify petroleum contamination in subsurface sediments
    Fay, Emily L.
    Knight, Rosemary J.
    Grunewald, Elliot D.
    GEOPHYSICS, 2017, 82 (04) : EN81 - EN92
  • [32] LOW-FIELD NUCLEAR-MAGNETIC-RESONANCE RELAXATION STUDY OF STORED OR PROCESSED COD
    LAMBELET, P
    RENEVEY, F
    KAABI, C
    RAEMY, A
    JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, 1995, 43 (06) : 1462 - 1466
  • [33] A new fractal model for porous media based on low-field nuclear magnetic resonance
    Qiu, Shuxia
    Yang, Mo
    Xu, Peng
    Rao, Binqi
    JOURNAL OF HYDROLOGY, 2020, 586 (586)
  • [34] On-line monitoring of polyhydroxyalkanoate extraction by low-field nuclear magnetic resonance spectroscopy
    Thiele, Isabel
    Weiske, Bjoern
    Riedel, Sebastian L.
    Meyer, Klas
    POLYMER DEGRADATION AND STABILITY, 2025, 233
  • [35] Rapid detection of waste cooking oil using low-field nuclear magnetic resonance
    Jin, Haoquan
    Tu, Leyi
    Wang, Yuxuan
    Zhang, Kexin
    Lv, Bowen
    Zhu, Zhe
    Zhao, Di
    Li, Chunbao
    FOOD CONTROL, 2023, 145
  • [36] Monitoring of engine oil aging by diffusion and low-field nuclear magnetic resonance relaxation
    Foerster, E.
    Fraenza, C. C.
    Kuestner, J.
    Anoardo, E.
    Nirschl, H.
    Guthausen, G.
    MEASUREMENT, 2019, 137 : 673 - 682
  • [37] A low-field Nuclear Magnetic Resonance dataset of whole milk during coagulation and syneresis
    Curti, E.
    Pardu, A.
    Del Vigo, S.
    Sanna, R.
    Anedda, R.
    DATA IN BRIEF, 2019, 26
  • [38] Study of the interaction between polysaccharides and liposomes based on low-field nuclear magnetic resonance
    Zhang, Tingting
    Yu, Heng
    Li, Chenping
    Wang, Yanping
    Zheng, Chenxi
    Hu, Yingli
    Han, Jianzhong
    Liu, Jianhua
    Liu, Weilin
    FOOD BIOSCIENCE, 2025, 66
  • [39] Development of an Earth-Field Nuclear Magnetic Resonance Spectrometer: Paving the Way for AI-Enhanced Low-Field Nuclear Magnetic Resonance Technology
    Viciana, Eduardo
    Martinez-Lao, Juan Antonio
    Lopez-Lao, Emilio
    Fernandez, Ignacio
    Arrabal-Campos, Francisco Manuel
    SENSORS, 2024, 24 (17)
  • [40] Low-Field Nuclear Magnetic Resonance and Magnetic Resonance Imaging Using a High-Tc SQUID for Tumor Detection
    Huang, Kai-Wen
    Liao, Shu-Hsien
    Yang, Hong-Chang
    Chen, Hsin-Hsien
    Horng, Herng-Er
    Chen, M. J.
    Yang, Shieh-Yueh
    IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2011, 21 (03) : 461 - 464