A New Method to Identify Reservoirs in Tight Sandstones Based on the New Model of Transverse Relaxation Time and Relative Permeability

Relative permeability and transverse relaxation time are both important physical parameters of rock physics. In this paper, a new transformation model between the transverse relaxation time and the wetting phase’s relative permeability is established. The data shows that the cores in the northwest of China have continuous fractal dimension characteristics, and great differences existed in the different pore size scales. Therefore, a piece-wise method is used to calculate the fractal dimension in our transformation model. The transformation results are found to be quite consistent with the relative permeability curve of the laboratory measurements. Based on this new model, we put forward a new method to identify reservoir in tight sandstone reservoir. We focus on the Well M in the northwestern China. Nuclear magnetic resonance (NMR) logging is used to obtain the point-by-point relative permeability curve. In addition, we identify the gas and water layers based on new T2-Kr model and the results showed our new method is feasible. In the case of the price of crude oil being low, this method can save time and reduce the cost.

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Transverse Relaxation Time Fractal Dimension of Nuclear Magnetic Resonance for Characterizing Shajara Reservoirs of the Permo-Carboniferous Shajara Formation, Saudi Arabia

Petroleum and Chemical Industry International ◽

10.33140/pcii.02.02.06 ◽

2019 ◽

Vol 2 (2) ◽

Keyword(s):

Nuclear Magnetic Resonance ◽

Fractal Dimension ◽

Relaxation Time ◽

Magnetic Resonance ◽

Capillary Pressure ◽

Transverse Relaxation Time ◽

Transverse Relaxation ◽

Phase Saturation ◽

Second Procedure ◽

Nuclear Magnetic

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.

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An inter-vendor study of scan-rescan and left-right knee asymmetry variability of cartilage T2 transverse relaxation time and morphometry assessed simultaneously using a single rapid 4-minute MRI scan

Osteoarthritis and Cartilage ◽

10.1016/j.joca.2020.02.432 ◽

2020 ◽

Vol 28 ◽

pp. S269-S270

Author(s):

A.S. Chaudhari ◽

Q. Lu ◽

A. Wisser ◽

W. Wirth ◽

G.E. Gold ◽

...

Keyword(s):

Relaxation Time ◽

Transverse Relaxation Time ◽

Mri Scan ◽

Transverse Relaxation

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Two-photon echo method to determine the transverse relaxation time of excitonic molecules

Solid State Communications ◽

10.1016/0038-1098(81)91131-5 ◽

1981 ◽

Vol 38 (3) ◽

pp. 179-182 ◽

Cited By ~ 3

Author(s):

T. Takagahara

Keyword(s):

Relaxation Time ◽

Transverse Relaxation Time ◽

Photon Echo ◽

Transverse Relaxation ◽

Two Photon

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A study on water saturation predictions in igneous reservoirs based on the relationship between the transverse relaxation time and the resistivity index

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2021.109519 ◽

2021 ◽

pp. 109519

Author(s):

Yuhang Guo ◽

Baozhi Pan ◽

Lihua Zhang ◽

Jian Lei ◽

Yufei Fan ◽

...

Keyword(s):

Relaxation Time ◽

Water Saturation ◽

Transverse Relaxation Time ◽

Transverse Relaxation ◽

Resistivity Index ◽

The Relationship

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

Geophysics ◽

10.1190/geo2017-0745.1 ◽

2019 ◽

Vol 84 (2) ◽

pp. MR73-MR84 ◽

Cited By ~ 1

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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