Evaluation of Low-Field NMR T2 Methods for Residual Oil Saturation Estimation in Carbonate Core Plugs

Nuclear magnetic resonance (NMR) relaxometry is widely used to characterize pore systems and estimate fluid saturations in reservoir rocks. This study evaluates the use of low-field NMR transverse relaxation time (T2) as a standalone method for estimating residual oil saturation in Indiana limestone core plugs following brine flooding. Three core plugs were first saturated with dead light crude oil and then subjected to brine core-flooding experiments at different injection rates to establish different post-flood residual oil saturations. Two NMR T2-based approaches were investigated: (i) a volumetric method based on a calibrated T2 cutoff and (ii) a mathematical method based on the logarithmic mean T2 response. Independent saturation estimates were obtained using X-ray computed tomography (XCT). Overall, the volumetric approach showed closer agreement with XCT than the logarithmic mean approach. However, appropriate cutoff calibration and sensitivity analysis are essential because rock wettability, desaturation conditions, fluid properties, and pore-size distribution can influence cutoff selection and the resulting saturation estimates. At a T2 cutoff of 90 ms, the cutoff-based oil saturation estimates were 42.0%, 38.8%, and 40.1% for Ind03, Ind08, and Ind09, respectively. Increasing the cutoff from 70 to 100 ms increased the estimated saturations by 4.4–5.0 percentage points across the three plugs, highlighting the sensitivity of quantitative saturation estimates to cutoff selection.

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Publication Details

Journal
Applied Sciences
Published
2026-10-29
DOI
https://doi.org/10.3390/app162110710
Primary Topic
NMR spectroscopy and applications
Type
article
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article

Evaluation of Low-Field NMR T2 Methods for Residual Oil Saturation Estimation in Carbonate Core Plugs

Ausama A. Giwelli, Lionel Esteban, Alireza Kazemi, Mustafa Sari et al.
1 links
Applied Sciences
NMR spectroscopy and applications
article

Evaluation of Low-Field NMR T2 Methods for Residual Oil Saturation Estimation in Carbonate Core Plugs

Ausama A. Giwelli, Lionel Esteban, Alireza Kazemi, Mustafa Sari, Lamees Al-Siyabi
article en

Abstract

Nuclear magnetic resonance (NMR) relaxometry is widely used to characterize pore systems and estimate fluid saturations in reservoir rocks. This study evaluates the use of low-field NMR transverse relaxation time (T2) as a standalone method for estimating residual oil saturation in Indiana limestone core plugs following brine flooding. Three core plugs were first saturated with dead light crude oil and then subjected to brine core-flooding experiments at different injection rates to establish different post-flood residual oil saturations. Two NMR T2-based approaches were investigated: (i) a volumetric method based on a calibrated T2 cutoff and (ii) a mathematical method based on the logarithmic mean T2 response. Independent saturation estimates were obtained using X-ray computed tomography (XCT). Overall, the volumetric approach showed closer agreement with XCT than the logarithmic mean approach. However, appropriate cutoff calibration and sensitivity analysis are essential because rock wettability, desaturation conditions, fluid properties, and pore-size distribution can influence cutoff selection and the resulting saturation estimates. At a T2 cutoff of 90 ms, the cutoff-based oil saturation estimates were 42.0%, 38.8%, and 40.1% for Ind03, Ind08, and Ind09, respectively. Increasing the cutoff from 70 to 100 ms increased the estimated saturations by 4.4–5.0 percentage points across the three plugs, highlighting the sensitivity of quantitative saturation estimates to cutoff selection.

Applied SciencesVol. 16(21)
Commonwealth Scientific and Industrial Research Organisation (AU), Sultan Qaboos University (OM)
Openalex Percentile: Top 18%
NMR spectroscopy and applications
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Evaluation of Low-Field NMR T2 Methods for Residual Oil Saturation Estimation in Carbonate Core Plugs — Ausama A. Giwelli, Lionel Esteban, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS