Consistency study of mercury intrusion and nuclear magnetic resonance in pore structure characterization for tight oil –A case study in Sichuan Basin, China

2017 ◽  
Author(s):  
Yunlong Liu* ◽  
Yuanzhong Zhang
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Pore Structure ◽  
Sichuan Basin ◽  
Structure Characterization ◽  
Tight Oil ◽  
Mercury Intrusion ◽  
Nuclear Magnetic

scholarly journals FRACTAL CHARACTERIZATION OF TIGHT OIL RESERVOIR PORE STRUCTURE USING NUCLEAR MAGNETIC RESONANCE AND MERCURY INTRUSION POROSIMETRY

Fractals ◽  
2018 ◽  
Vol 26 (02) ◽  
pp. 1840017 ◽  
Author(s):  
FUYONG WANG ◽  
KUN YANG ◽  
JIANCHAO CAI
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Pore Structure ◽  
Pore Size ◽  
Mercury Intrusion Porosimetry ◽  
Fractal Dimensions ◽  
Structure Characterization ◽  
Tight Oil ◽  
Petrophysical Properties ◽  
Mercury Intrusion

Tight oil sandstones have the characteristics of narrow pore throats, complex pore structures and strong heterogeneities. Using nuclear magnetic resonance (NMR) and mercury intrusion porosimetry (MIP), this paper presents an advanced fractal analysis of the pore structures and petrophysical properties of the tight oil sandstones from Yanchang Formation, Ordos Basin of China. Firstly, nine typical tight oil sandstone core samples were selected to conduct NMR and MIP test for pore structure characterization. Next, with the pore size distribution derived from MIP, it was found that the relationships between NMR transverse relaxation time [Formula: see text] and pore size are more accordant with the power function relations, which were applied to derive pore size distribution from NMR rather than the linear relation. Moreover, fractal dimensions of micropores, mesopores and macropores were calculated from NMR [Formula: see text] spectrum. Finally, the relationships between the fractal dimensions of different size pores calculated from NMR [Formula: see text] spectrum and petrophysical properties of tight oil sandstones were analyzed. These studies demonstrate that the combination of NMR and MIP can improve the accuracy of pore structure characterization and fractal dimensions calculated from NMR [Formula: see text] spectrum are effective for petrophysical properties analysis.

Determination of nuclear magnetic resonance T2 cutoff value based on multifractal theory — An application in sandstone with complex pore structure

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. D11-D21 ◽  
Author(s):  
Xinmin Ge ◽  
Yiren Fan ◽  
Xuejuan Zhu ◽  
Yiguo Chen ◽  
Runze Li
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Pore Structure ◽  
Water Saturation ◽  
Influential Factors ◽  
Structure Characterization ◽  
Cutoff Value ◽  
Irreducible Water Saturation ◽  
Multifractal Theory ◽  
Nuclear Magnetic

The cutoff value of nuclear magnetic resonance (NMR) transversal relaxation time [Formula: see text] is vital for pore structure characterization, permeability prediction, and irreducible water saturation calculation. Conventional default values often lead to inaccurate results for rocks with complex pore structure. Based on NMR experiments and multifractal theory, we have developed an effective statistical method to predict [Formula: see text] cutoff values without other petrophysical information. The method is based on multifractal theory to analyze the NMR [Formula: see text] spectrum with the assumption that the [Formula: see text] spectrum is an indicator of pore size distribution. Multifractal parameters, such as multifractal dimension, singularity strength, and mass exponent, are calculated to investigate the multifractal behavior of [Formula: see text] spectrum via NMR experiments and a dyadic scaling-down algorithm. To obtain the optimal [Formula: see text] cutoff value, the rotation speed and time of centrifugation are enlarged increasingly to optimal centrifugal state. A predicating model for [Formula: see text] cutoff value based on multiple linear regressions of multifractal parameters was proposed after studying the influential factors. On the basis of the multifractal analysis of NMR [Formula: see text] spectrum, a reasonable predication model for [Formula: see text] cutoff value was rendered. Upon testing, the predicted results were highly consistent with the experimental results.

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