Fractal Characterization of Tight Oil Reservoir Pore Structure Using Nuclear Magnetic Resonance and Mercury Intrusion Porosimetry

Wang, Fuyong; Yang, Kun; Cai, Jianchao

doi:10.1142/s0218348x18400170

Cited by 78 publications

(62 citation statements)

References 28 publications

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“…According to the results of this work, a lower viscosity and lighter components of oil can facilitate the mass transfer process.Energies 2018, 11, 1495 2 of 20 methods for the quantitative determination of the gas (N 2 , CO 2 , CH 4 [28], C 2 H 6 , C 3 H 8 , or a mixture gas) diffusion coefficient in crude oil. These methods include the pressure decay method, X-ray computer-assisted tomography (CAT) method, magnetic resonance imaging (MRI) method [29,30], dynamic drop volume analysis (DPDVA), and pore-scale network modeling method. All of these methods have advantages and flaws:Direct testing method.…”

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confidence: 99%

The Effect of Oil Properties on the Supercritical CO2 Diffusion Coefficient under Tight Reservoir Conditions

Zhang

Qiao

et al. 2018

Energies

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In this paper, a generalized methodology has been developed to determine the diffusion coefficient of supercritical CO 2 in cores that are saturated with different oil samples, under reservoir conditions. In theory, a mathematical model that combines Fick's diffusion equation and the Peng-Robinson equation of state has been established to describe the mass transfer process. In experiments, the pressure decay method has been employed, and the CO 2 diffusion coefficient can be determined once the experimental data match the computational result of the theoretical model. Six oil samples with different compositions (oil samples A to F) are introduced in this study, and the results show that the supercritical CO 2 diffusion coefficient decreases gradually from oil samples A to F. The changing properties of oil can account for the decrease in the CO 2 diffusion coefficient in two aspects. First, the increasing viscosity of oil slows down the speed of the mass transfer process. Second, the increase in the proportion of heavy components in oil enlarges the mass transfer resistance. According to the results of this work, a lower viscosity and lighter components of oil can facilitate the mass transfer process.Energies 2018, 11, 1495 2 of 20 methods for the quantitative determination of the gas (N 2 , CO 2 , CH 4 [28], C 2 H 6 , C 3 H 8 , or a mixture gas) diffusion coefficient in crude oil. These methods include the pressure decay method, X-ray computer-assisted tomography (CAT) method, magnetic resonance imaging (MRI) method [29,30], dynamic drop volume analysis (DPDVA), and pore-scale network modeling method. All of these methods have advantages and flaws:Direct testing method. Hill and Lacey [31] tested the diffusion coefficient of CH 4 in isopentane with a constant pressure method in a Pressure-Volume-Temperature (PVT) system. Sigmund [32] also used this method to study the binary dense gas diffusion coefficients under reservoir conditions. Islas-Juarez et al. [33] set up an experimental device to determine the effective diffusion coefficient of N 2 in a sandpack model. They devised a special setting to sample crude oil that was dissolved with N 2 in their porous model. The samples were then analyzed by gas chromatograph, and the gas concentration in the oil phase was determined. The corresponding diffusion coefficient was determined by matching the mathematical diffusion model with the experimentally measured concentration curve. The main shortcomings of the direct testing method for the solvent diffusion coefficient are that it is both time and labor consuming, which results in an expensive process.Pressure decay method. Riazi [34] proposed a technique known as the pressure decay method based on the fact that the pressure of the gas phase in a closed diffusion cell decreases with the migration of the gas phase into the liquid phase. One of the remarkable features of this method is that it does not require costly component measurements. In the following two decades, many scholars adopted this method to test the diffus...

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confidence: 99%

The Effect of Oil Properties on the Supercritical CO2 Diffusion Coefficient under Tight Reservoir Conditions

Zhang

Qiao

et al. 2018

Energies

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“…However, the actual pore structures are more complex than those of the ideal formation. Several scholars have found that an exponential relationship, rather than a linear relationship, exists between the T2 spectrum (ms) and the pore radius (µ m) [23,27,42]: this finding is also supported by Figure 2b,c; the relationship can be expressed as follow:…”

Section: Combining Nmr and Hpmi Methodsmentioning

confidence: 53%

“…Thus, micron-scale pores remain difficult to describe [25,26]. High-pressure mercury injection (HPMI) is often integrated with NMR to reflect tight sandstone PSD [24,27], due to the resultant relatively full range of PSD characterization, although the relationship between T 2 spectrums and pore radii directly influences the accuracy of the NMR-HPMI-integrated PSD.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Quantitative Characterization of Pore Distribution Networks in Tight Sandstone by integrating FE-SEM, HPMI, and NMR with the Constrained Least Squares Algorithm

Zhou

Shi

et al. 2019

Energies

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The goal of this study was to investigate the impacts of various sedimentary-diagenetic conditions on the macroscopic petrophysical parameters and microscopic pore structures of tight sandstones from the Lower Jurassic Badaowan Formation in the Southern Junggar Basin, China. Based on the traditional methods for establishing pore size distribution, including integrating the results of high-pressure mercury injection, nuclear magnetic resonance, and scanning electron microscopy, the constrained least squares algorithm was employed to automatically determine the porosity contributions of pore types with different origins. The results show that there are six genetic pore types: residual intergranular pores (RIPs), feldspar dissolution pores (FDPs), rock fragment dissolution pores (RFDPs), clay mineral intergranular pores (CIPs), intercrystalline pores of kaolinite (IPKs), and matrix pores (MPs). Four lithofacies were identified: the quartz cemented-dissolution facies (QCDF), carbonate cemented facies (CCF), authigenic clay mineral facies (ACMF), and matrix-caused tightly compacted facies (MCTF). Modified by limited dissolution, the QCDF with a high proportion of macropores (RIPs, FDPs, and RFDPs) exhibited a slightly higher porosity and considerably higher permeability than those of others. A large number of micropores (MPs, CIPs, and IPKs) in MCTF and ACMF led to slightly lower porosities but considerably lower permeabilities. Due to the tightly cemented carbonates in the CCF, its porosity reduced sharply, but the permeability of the CCF remained much higher those of the MCTF and ACMF. The results highlight that a high proportion of macropores with large radii and regular shapes provide more effective percolation paths than storage spaces. Nevertheless, micropores with small radii and complex pore structures have a limited contribution to flow capability. The fractal dimension analysis shows that a high proportion of MPs is the major reason for the heterogeneity in tight sandstones. The formation of larger macropores with smooth surfaces are more conductive for oil and gas accumulation.

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“…The core samples were collected from the outcrop of the tight sandstone formation. Tables 1 and 2 present the detailed oil and core sample properties used respectively. Energies 2018, 11,2667 3 of 17 mature standard reference in the experimental study of tight oil depletion in China, hence few reports on experimental evaluation have been published [51]. Therefore, further research needs to be done experimentally in order to fully grasp the factors affecting recovery of tight oil and how recovery factor can be improved significantly before a decision whether or not to exploit specific tight oil reservoir can be made.…”

Section: Methodsmentioning

confidence: 99%

Experimental Investigation of Oil Recovery from Tight Sandstone Oil Reservoirs by Pressure Depletion

et al. 2018

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Oil production by natural energy of the reservoir is usually the first choice for oil reservoir development. Conversely, to effectively develop tight oil reservoir is challenging due to its ultra-low formation permeability. A novel platform for experimental investigation of oil recovery from tight sandstone oil reservoirs by pressure depletion has been proposed in this paper. A series of experiments were conducted to evaluate the effects of pressure depletion degree, pressure depletion rate, reservoir temperature, overburden pressure, formation pressure coefficient and crude oil properties on oil recovery by reservoir pressure depletion. In addition, the characteristics of pressure propagation during the reservoir depletion process were monitored and studied. The experimental results showed that oil recovery factor positively correlated with pressure depletion degree when reservoir pressure was above the bubble point pressure. Moreover, equal pressure depletion degree led to the same oil recovery factor regardless of different pressure depletion rate. However, it was noticed that faster pressure drop resulted in a higher oil recovery rate. For oil reservoir without dissolved gas (dead oil), oil recovery was 2–3% due to the limited reservoir natural energy. In contrast, depletion from live oil reservoir resulted in an increased recovery rate ranging from 11% to 18% due to the presence of dissolved gas. This is attributed to the fact that when reservoir pressure drops below the bubble point pressure, the dissolved gas expands and pushes the oil out of the rock pore spaces which significantly improves the oil recovery. From the pressure propagation curve, the reason for improved oil recovery is that when the reservoir pressure is lower than the bubble point pressure, the dissolved gas constantly separates and provides additional pressure gradient to displace oil. The present study will help engineers to have a better understanding of the drive mechanisms and influencing factors that affect development of tight oil reservoirs, especially for predicting oil recovery by reservoir pressure depletion.

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Fractal Characterization of Tight Oil Reservoir Pore Structure Using Nuclear Magnetic Resonance and Mercury Intrusion Porosimetry

Cited by 78 publications

References 28 publications

The Effect of Oil Properties on the Supercritical CO2 Diffusion Coefficient under Tight Reservoir Conditions

The Effect of Oil Properties on the Supercritical CO2 Diffusion Coefficient under Tight Reservoir Conditions

Multi-Scale Quantitative Characterization of Pore Distribution Networks in Tight Sandstone by integrating FE-SEM, HPMI, and NMR with the Constrained Least Squares Algorithm

Experimental Investigation of Oil Recovery from Tight Sandstone Oil Reservoirs by Pressure Depletion

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