scholarly journals Magnetic Resonance Microimaging and Numerical Simulations of Velocity Fields Inside Enlarged Flow Cells Used for Coupled NMR Microseparations

2005 ◽  
Vol 77 (5) ◽  
pp. 1338-1344 ◽  
Author(s):  
Xiaofeng Zhang ◽  
Andrew G. Webb
Keyword(s):  
Magnetic Resonance ◽  
Numerical Simulations ◽  
Velocity Fields ◽  
Flow Cells ◽  
Magnetic Resonance Microimaging

Quantifying the Mechanisms Contributing to Nuclear-Magnetic-Resonance Surface Relaxation of Protons in Kerogen Pores of Organic-Rich Mudrocks

SPE Journal ◽  
2019 ◽  
Vol 24 (06) ◽  
pp. 2438-2457 ◽  
Author(s):  
Saurabh Tandon ◽  
Zoya Heidari
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Numerical Simulations ◽  
Dipolar Coupling ◽  
Surface Relaxation ◽  
Pore Scale ◽  
New Model ◽  
Surface Relaxivity ◽  
Coupling Mechanisms ◽  
Organic Pores

Summary The evaluation of nuclear–magnetic–resonance (NMR) measurements can be challenging in organic–rich mudrocks because of their heterogeneity, tight pores, presence of kerogen, and the lack of understanding regarding the relaxation mechanism on the kerogen surface. Numerical simulation of NMR responses in the pore–scale domain in such complex rocks is also not very useful because most of the inputs are derived from conventional surface–relaxivity models. The conventional grain/fluid–interaction models for quantifying surface relaxivity do not account for any dipolar coupling in kerogen pores. The objectives of this paper are to develop a new surface–relaxivity model that accurately accounts for homonuclear dipolar coupling in kerogen pores; to introduce a pore–scale simulation method for reliable modeling of NMR response; and to quantify the effects of applying the new relaxivity model on simulated NMR responses and phase saturations. We start by considering the generalized Langmuir adsorption (GLA) theory for the adsorption of hydrocarbons on the surfaces of organic pores in mudrock samples. We used this adsorption model and the anisotropic rotation of molecules to develop a new surface–relaxivity model that accurately quantifies both transverse (T2) and longitudinal (T1) relaxation of protons in kerogen pores. The new model was used to simulate NMR responses in ellipsoidal pores and segmented focused–ion–beam scanning–electron–microscope (FIB–SEM) images of organic–rich mudrock samples using a pore–scale finite–volume simulation technique. The inputs to the simulator are the previously discussed pore geometries and the bulk and surface properties of different fluids present in the pore space. The outputs from the simulator were T2 and T1 decay constants in the previously mentioned pore geometries. The results of NMR simulations are then used to quantify the sensitivity of NMR responses to surface relaxivities computed using different models and NMR–based estimates of adsorbed–hydrocarbon volume. The results obtained from the new model verified that intramolecular coupling dominates the T1 and T2 surface relaxivities at high correlation times (greater than 1×10–7 seconds), which are usually observed for hydrocarbons in kerogen pores. The new model also confirmed the observation that NMR responses in mudrocks are not a function of kerogen thermal maturity but strongly depend on kerogen type. The results of numerical simulations demonstrated that dominant T2 peaks, T1–T2 ratios, and estimated adsorbed fractions are functions of molecular correlation time. Numerical simulations of NMR responses in organic–rich mudrock demonstrated that misidentifying coupling mechanisms could cause errors of up to 40.9 and 57.3% in estimates of adsorbed–hydrocarbon volume calculated using T2 and T1–T2 measurements, respectively. The surface–relaxivity model developed in this paper is more reliable than the previously published relaxivity models because it includes the effects of different coupling mechanisms on surface relaxation in organic pores. The new model can be reliably extended for quantifying surface relaxivity at higher temperatures and for different fluids, which enables interpretation of NMR logs at in-situ conditions. Enhanced quantification of surface relaxivity also enhances NMR–based reservoir characterization and helps to improve the estimates of hydrocarbon reserves in organic–rich mudrocks.

Application of Magnetic Resonance Microimaging to the Study of Dental Caries

1999 ◽  
Vol 34 (1) ◽  
pp. 53-58 ◽  
Author(s):  
C.H. Lloyd ◽  
S.N. Scrimgeour ◽  
J.A. Chudek ◽  
G. Hunter ◽  
R.L. MacKay
Keyword(s):  
Magnetic Resonance ◽  
Dental Caries ◽  
Magnetic Resonance Microimaging

Nuclear magnetic resonance microimaging of mouse spinal cord in vivo

2004 ◽  
Vol 15 (3) ◽  
pp. 474-482 ◽  
Author(s):  
Jean-Marie Bonny ◽  
Manuel Gaviria ◽  
Jean-Pierre Donnat ◽  
Beatrix Jean ◽  
Alain Privat ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Mouse Spinal Cord ◽  
Magnetic Resonance Microimaging ◽  
Nuclear Magnetic Resonance Microimaging ◽  
Nuclear Magnetic
Sign in / Sign up

Export Citation Format

Share Document