Temperature Dependence of Nuclear Magnetic Resonance Relaxation Time in Carbonate Reservoirs

2021 ◽  
pp. 1-16
Author(s):  
Wei Shao ◽  
Songhua Chen ◽  
Gabor Hursan ◽  
Shouxiang Ma

Summary Nuclear magnetic resonance (NMR)-based interpretation models are commonly calibrated using laboratory ambient core NMR measurements. For applying the core calibrated models to downhole NMR logging interpretation, the difference between the NMR responses measured at ambient and reservoir temperature needs to be evaluated. The temperature dependence of NMR relaxation time in high-quality (HQ) carbonate reservoirs has been studied, and NMR temperature dependence models were established using data analytic methods. In this paper, we extend our early studies on temperature dependence of NMR relaxation time to low-quality (LQ) carbonate formations. For more than 95% of the LQ samples investigated, NMR relaxation time shows a positive correlation with temperature. The correlation is similar to that observed in HQ carbonate rocks but slightly less significant. Temperature-dependent correlations for predicting the geometric mean of NMR transverse relaxation time (T2,GM) from a measured temperature to any other temperature were derived from HQ to LQ carbonate rocks independently first, then a unified T2,GM correlation was derived including both the HQ and LQ carbonate reservoirs. Predicting NMR transverse relaxation time T2 distribution from one temperature to other temperatures was achieved using a dimension reduction approach involving the principal component analysis (PCA) technique. It was found that the T2 distributions at any given temperature for both HQ and LQ carbonate reservoirs can be predicted robustly from the T2 distributions at the ambient temperature by representing the T2 distributions with principal components (PCs) at the ambient temperature and then using these PCs to predict the PCs at a different temperature. The optimal number of PC components depends on the multimodality of the T2distribution. This work extends the validity range of the data analytic methods, in particular parameter and dimension reduction methods, that quantify the temperature dependence of carbonate NMR properties. The new NMR temperature model enables the integration of NMR laboratory studies and downhole measurements for advanced petrophysical analyses in a wide range of carbonate reservoirs.

2021 ◽  
Author(s):  
Wei Shao ◽  
Songhua Chen ◽  
Gabor Hursan ◽  
Shouxiang Ma

Abstract NMR-based carbonate interpretation models are commonly calibrated using laboratory ambient core NMR measurements. For applying the core calibrated models to downhole NMR logging interpretation, the difference between the NMR responses measured at ambient and reservoir conditions needs to be evaluated. The temperature dependence of NMR relaxation time in high-quality carbonate reservoirs was investigated, and NMR temperature dependence models were determined using data analytic methods (Hursan et al, 2019). This paper focuses on temperature dependence of NMR relaxation time in low-quality carbonate formations. For more than 95% of the samples investigated, NMR relaxation time shows a positive correlation with temperature. The correlation is similar to that observed in high-quality carbonate rocks but slightly less significant. Temperature dependent correlations for predicting T2GM from a measured temperature to any other temperature are derived from high- and low-quality carbonate rocks independently first, then a unified T2GM correlation is derived including both the high- and low-quality carbonate reservoirs. Predicting T2 distribution from one temperature to other temperatures is achieved using dimension reduction approach involving principal component analysis (PCA) technique. It is found that the T2 distributions at any given temperature for both the high- and low-quality carbonate reservoirs can be predicted robustly from the T2 distributions at the ambient temperature by representing the T2 distributions with principal components (PCs) at the ambient temperature then using these PCs to predict the PCs at a different temperature. The optimal number of PC components depends on the multimodality of the T2 distribution. This work extends the validity range of a data analytic method that quantifies the temperature dependence of carbonate NMR properties. The new NMR temperature model enables the integration of NMR laboratory studies and dowhole measurements for advanced petrophysical analyses in a wide range of carbonate reservoirs.


Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. MR73-MR84 ◽  
Author(s):  
Fatemeh Razavirad ◽  
Myriam Schmutz ◽  
Andrew Binley

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.


2019 ◽  
Vol 2 (2) ◽  

The quality of a reservoir can be described in details by the application of transverse relaxation time of nuclear magnetic resonance fractal dimension. The objective of this research is to calculate fractal dimension from the relationship among transverse relaxation time of nuclear magnetic resonance, maximum transverse relaxation time of nuclear magnetic resonance and wetting phase saturation and to confirm it by the fractal dimension derived from the relationship among capillary pressure and wetting phase saturation. In this research, porosity was measured on real collected sandstone samples and permeability was calculated theoretically from capillary pressure profile measured by mercury intrusion techniques. Two equations for calculating the fractal dimensions have been employed. The first one describes the functional relationship between wetting phase saturation, transverse relaxation time of nuclear magnetic resonance, maximum transverse relaxation time of nuclear magnetic resonance and fractal dimension. The second equation implies to the wetting phase saturation as a function of capillary pressure and the fractal dimension. Two procedures for obtaining the fractal dimension have been developed. The first procedure was done by plotting the logarithm of the ratio between transverse relaxation time of nuclear magnetic resonance and maximum transverse relaxation time of nuclear magnetic resonance versus logarithm wetting phase saturation. The slope of the first procedure = 3-Df (fractal dimension). The second procedure for obtaining the fractal dimension was completed by plotting logarithm of capillary pressure versus the logarithm of wetting phase saturation. The slope of the second procedure = Df -3. The results show similarities between transverse relaxation time of nuclear magnetic resonance and capillary pressure fractal dimension.


2018 ◽  
Vol 51 (2) ◽  
pp. 74-80 ◽  
Author(s):  
Rongsheng Lu ◽  
Penkun Lei ◽  
Xinlong Zhou ◽  
Yun Jiang ◽  
Xiaowen Jiang ◽  
...  

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