Applications of nuclear magnetic resonance (NMR) logging in tight sandstone reservoir pore structure characterization

Zhang, Haitao; Li, Gao‐Ren; Guo, Hu; Zhang, Wenjing; Wang, Yanmei; Li, Weibing; Zhou, Jian; Wang, Changsheng

doi:10.1007/s12517-020-05590-6

Cited by 11 publications

(10 citation statements)

References 25 publications

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“…Based on eq , some researchers have proposed the following PFT method , where A 1 and B 1 are model coefficients.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, some researchers have proposed the construction of MICP curves using the power function transformation (PFT) method. 17,22 However, while the PFT method provides higher prediction accuracy than the LFT method, it still cannot meet the accuracy requirements of the actual exploration of unconventional reservoirs. 15 To solve this problem, this paper proposes a novel method based on the classified piecewise multi-parameter power function transformation (CPMPFT) model to predict the MICP curves.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, with the development of new exploration technologies, unconventional reservoirs have become the research focus in the field of petroleum exploration. − Conventional methods are no longer applicable to the evaluation of unconventional reservoirs, like sandstone reservoirs. Therefore, to improve the evaluation of unconventional reservoirs, it is necessary to quantitatively characterize their pore structures. − Because pore structure parameters are obtained using mercury injection capillary pressure (MICP) curves, based on which the type of reservoir can be determined, − the accurate determination of MICP curves is of great importance. − Currently, MICP curves are generally obtained through MICP experiments. However, in actual exploration, it is difficult to obtain a large number of core samples, which are then destroyed by mercury injection measurements. , Therefore, non-destructive methods by which to continuously obtain reservoir MICP curves for reservoir evaluation have become a key subject of oil and gas exploration. , …”

Section: Introductionmentioning

confidence: 99%

“…As a result, the prediction error when using the LFT method for unconventional reservoirs is relatively large. Therefore, some researchers have proposed the construction of MICP curves using the power function transformation (PFT) method. , However, while the PFT method provides higher prediction accuracy than the LFT method, it still cannot meet the accuracy requirements of the actual exploration of unconventional reservoirs …”

Section: Introductionmentioning

confidence: 99%

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Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Xie

et al. 2021

Energy Fuels

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In this research, mercury injection capillary pressure (MICP) experiments and nuclear magnetic resonance (NMR) experiments were carried out on 19 reservoir core samples. Based on the experimental results, the relationships between the capillary pressure (P c ) and NMR transverse relaxation time (T 2 ) were established. A novel classified piecewise multi-parameter power function transformation (CPMPFT) method is proposed to predict the MICP curves using the NMR T 2 distributions and is described as follows. First, the multi-parameter power function transformation model is established, after which the reservoir is classified and the appropriate pore segmentation point is selected. Then, for each type of reservoir, the coefficients of the transformation model for large and small pores are calculated based on the simulated annealing and genetic algorithm combined with non-linear programming, and the models for predicting the MICP curves are ultimately obtained. Using these models, the MICP curves can be predicted continuously based on the NMR T 2 distribution, based on which the pore structure parameters, including the displacement pressure (P d ), median pressure (P c50 ), and so forth, can be precisely extracted. 19 core samples and well data were processed using the proposed method, and the predicted results were compared with the measured results; the results were found to match well, thereby proving the reliability of the proposed method.

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“…Based on eq , some researchers have proposed the following PFT method , where A 1 and B 1 are model coefficients.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Xie

et al. 2021

Energy Fuels

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show abstract

“…In recent years, many researchers have investigated the methods for reservoir classification based on the NMR T 2 distribution. The main idea of reservoir classification methods based on NMR logging is to convert the NMR T 2 distribution to capillary pressure curves based on HPMI experiments and, thereby, obtain the pore structure parameters (e.g., displacement pressure and median radius) for pore structure evaluation and reservoir classification. − On the basis of the correlation between the NMR T 2 distribution and pore-throat size distribution, a method for pore structure identification was established, where NMR was used to investigate the characteristics of pore structures . This method provides a basis for the evaluation of tight sandstone reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Classification of Tight Sandstone Reservoirs Based on the Nuclear Magnetic Resonance T₂ Distribution: A Case Study on the Shaximiao Formation in Central Sichuan, China

et al. 2022

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The classification of tight sandstone reservoirs is of significance for hydrocarbon exploration and production. Different from conventional reservoirs, tight sandstone reservoirs are characterized by a complex pore structure and strong heterogeneity. Tight sandstone reservoir classification may not be reliable with conventional reservoir classification methods. In this paper, a classification method of tight sandstone reservoirs was proposed on the basis of the nuclear magnetic resonance (NMR) transverse relaxation (T 2 ) distribution, and it was employed for reservoir classification on the Shaximiao Formation in central Sichuan, China. As a result of the complex pore structure of a tight sandstone reservoir, the NMR T 2 distribution is characterized by the presence of multiple peaks. Therefore, the three-peak Gaussian function was used to fit the T 2 distribution and obtain the characteristic parameters. On the basis of high-pressure mercury intrusion (HPMI) experiments, the correlation between the characteristic parameters of the NMR T 2 distribution and pore structure parameters and petrophysical properties was analyzed, and then the optimal characteristic parameters of the NMR T 2 distribution were selected according to the results of correlation analysis and used to establish the pore structure index. In combination of petrophysical properties with the pore structure index, the model for classification of tight sandstone reservoirs was established by the naive Bayesian method based on hierarchical clustering, and the accuracy of the model was verified by k-fold cross-validation. Finally, the effectiveness of the proposed method was verified using the actual NMR logging data in conjunction with the oil test data. The results showed that the method for classification of tight sandstone reservoirs based on the NMR T 2 distribution can provide effective guidance for production capacity evaluation.

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Research on pore structure and classification evaluation of tight oil reservoirs based on fractal theory

Li,

Bian,

Zhang

et al. 2024

Acta Geophys.

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Chang 8 section of Yanchang Group in Yuancheng area of Ordos Basin is a typical tight oil reservoir in China, which is characterised by low porosity and low permeability, strong non-homogeneity and high difficulty in evaluating reservoir parameters. In order to clarify the microscopic pore structure characteristics of the Chang 8 section, this study uses cast thin section, scanning electron microscope, combined with the core physical properties test data, to analyse the basic characteristics of the reservoir rock mineralogy, pore permeability and other basic characteristics, and uses the shape of piezo-mercury curves to study the pore structure characteristics of the 17 samples. Based on the fractal dimension of the NMR T2 spectrum, the reservoir is classified into four categories, and a conversion model for the relationship between the NMR T2 spectrum and the capillary pressure curve is established by using the segmented power function method, which is applied to the interpretation of the NMR logging to obtain the continuous pseudo-capillary pressure curve for the whole well section. Three effective parameters reflecting the microscopic pore structure, namely, the expulsion pressure, median pressure, and sorting coefficient of the core samples, were extracted, and the relationship between the reservoir parameters and the reservoir category was established by using the generalised regression neural network. The pseudo-capillary pressure curve reservoir parameters of the whole well section were processed to obtain the classification profile of the reservoir, and the classification results were consistent with the results of the mercury pressure experiment with good results. The study shows that this method can provide an important basis for the study of pore structure of tight oil reservoirs and the evaluation of reservoir classification.

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Applications of nuclear magnetic resonance (NMR) logging in tight sandstone reservoir pore structure characterization

Cited by 11 publications

References 25 publications

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Classification of Tight Sandstone Reservoirs Based on the Nuclear Magnetic Resonance T₂ Distribution: A Case Study on the Shaximiao Formation in Central Sichuan, China

Research on pore structure and classification evaluation of tight oil reservoirs based on fractal theory

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Applications of nuclear magnetic resonance (NMR) logging in tight sandstone reservoir pore structure characterization

Cited by 11 publications

References 25 publications

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T2 Distributions

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T2 Distributions

Classification of Tight Sandstone Reservoirs Based on the Nuclear Magnetic Resonance T2 Distribution: A Case Study on the Shaximiao Formation in Central Sichuan, China

Research on pore structure and classification evaluation of tight oil reservoirs based on fractal theory

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Product

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Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Novel Method for Predicting Mercury Injection Capillary Pressure Curves of Tight Sandstone Reservoirs Using NMR T₂ Distributions

Classification of Tight Sandstone Reservoirs Based on the Nuclear Magnetic Resonance T₂ Distribution: A Case Study on the Shaximiao Formation in Central Sichuan, China