Obtaining true transverse relaxation time distributions in high-field NMR measurements of saturated porous media: Removing the influence of internal gradients

2010 ◽  
Vol 132 (24) ◽  
pp. 244705 ◽  
Author(s):  
J. Mitchell ◽  
T. C. Chandrasekera ◽  
L. F. Gladden
Keyword(s):  
Porous Media ◽  
Relaxation Time ◽  
High Field ◽  
Transverse Relaxation Time ◽  
Saturated Porous Media ◽  
Transverse Relaxation

scholarly journals Effect of Mineral Composition on Transverse Relaxation Time Distributions and MR Imaging of Tight Rocks from Offshore Ireland

Minerals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 232
Author(s):  
Stian Almenningen ◽  
Srikumar Roy ◽  
Arif Hussain ◽  
John Georg Seland ◽  
Geir Ersland
Keyword(s):  
Magnetic Field ◽  
Relaxation Time ◽  
Mr Imaging ◽  
Field Strength ◽  
High Field ◽  
Transverse Relaxation Time ◽  
Transverse Relaxation ◽  
The Core ◽  
Low Field ◽  
Field Strengths

In this paper, we investigate the effect of magnetic field strength on the transverse relaxation time constant (T2) in six distinct core plugs from four different rock types (three sandstones, one basalt, one volcanic tuff and one siltstone), retrieved from offshore Ireland. The CPMG pulse-sequence was used at two different magnetic field strengths: high-field at 4.70 T and low-field at 0.28 T. Axial images of the core plugs were also acquired with the RAREst sequence at high magnetic field strength. Thin-sections of the core plugs were prepared for optical imaging and SEM analysis, and provided qualitative information on the porosity and quantification of the elemental composition of the rock material. The content of iron varied from 4 wt. % to close to zero in the rock samples. Nevertheless, the effective T2 distributions obtained at low-field were used to successfully predict the porosity of the core plugs. Severe signal attenuations from internal magnetic gradients resulted in an underestimation of the porosity at high-field. No definitive trend was identified on the evolution of discrete relaxation time components between magnetic field strengths. The low-field measurements demonstrate that NMR is a powerful quantitative tool for petrophysical rock analysis as compared to thin-section analysis. The results of this study are of interest to the research community who characterizes natural gas hydrates in tight heterogeneous core plugs, and who typically relies on MR imaging to distinguish between solid hydrates and fluid phases. It further exemplifies the importance of selecting appropriate magnetic field strengths when employing NMR/MRI for porosity calculation in tight rock.

scholarly journals Estimation of the permeability of hydrocarbon reservoir samples using induced polarization and nuclear magnetic resonance methods

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. MR73-MR84 ◽  
Author(s):  
Fatemeh Razavirad ◽  
Myriam Schmutz ◽  
Andrew Binley
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Relaxation Time ◽  
Magnetic Resonance ◽  
Mechanistic Model ◽  
Transverse Relaxation Time ◽  
Induced Polarization ◽  
Permeability Model ◽  
Transverse Relaxation ◽  
Hydrocarbon Reservoir ◽  
Nuclear Magnetic

We have evaluated several published models using induced polarization (IP) and nuclear magnetic resonance (NMR) measurements for the estimation of permeability of hydrocarbon reservoir samples. IP and NMR measurements were made on 30 samples (clean sands and sandstones) from a Persian Gulf hydrocarbon reservoir. We assessed the applicability of a mechanistic IP-permeability model and an empirical IP-permeability model recently proposed. The mechanistic model results in a broader range of permeability estimates than those measured for sand samples, whereas the empirical model tends to overestimate the permeability of the samples that we tested. We also evaluated an NMR permeability prediction model that is based on porosity [Formula: see text] and the mean of the log transverse relaxation time ([Formula: see text]). This model provides reasonable permeability estimations for the clean sandstones that we tested but relies on calibrated parameters. We also examined an IP-NMR permeability model, which is based on the peak of the transverse relaxation time distribution, [Formula: see text] and the formation factor. This model consistently underestimates the permeability of the samples tested. We also evaluated a new model. This model estimates the permeability using the arithmetic mean of log transverse NMR relaxation time ([Formula: see text]) and diffusion coefficient of the pore fluid. Using this model, we improved estimates of permeability for sandstones and sand samples. This permeability model may offer a practical solution for geophysically derived estimates of permeability in the field, although testing on a larger database of clean granular materials is needed.

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