An Experimental Study on Stress Sensitivity of Tight Sandstones with Different Microfractures

Zhao, Xinli; Yang, Zhengming; Wang, Zhiyuan; Lin, Wei; Xiong, Shengwu; Luo, Yutian; Niu, Zhongkun; Xia, Debin

doi:10.1155/2020/1865464

Cited by 6 publications

(5 citation statements)

References 35 publications

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“…At present, some scholars have conducted a series of studies on the strong stress sensitivity of reservoirs. From 2019 to 2022, based on core displacement experiments of fractured shale [69], pressure pulse attenuation experiments [69,70], and triaxial core compression experiments [71], the damage mechanism of stress sensitivity of the reservoir was explored by Xue et al In addition, in 2019, the effect of stress sensitivity on material permeability under different pressures and gas compositions was explored by Singh et al [72,73]. From 2019 to 2022, the influence of stress sensitivity coefficients of matrix [74,75], microfractures [74], and hydraulic fractures [74,75] on gas production was analyzed by Liu et al Based on the above research, stress sensitivity is an important characteristic of shale reservoir, which has a great influence on the permeability field.…”

Section: Strong Stress Sensitivity Characteristics Of Shale Matrix An...mentioning

confidence: 99%

Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs

Yang

Qiao

et al. 2023

Energies

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With the continuous development of conventional oil and gas resources, the strategic transformation of energy structure is imminent. Shale condensate gas reservoir has high development value because of its abundant reserves. However, due to the multi-scale flow of shale gas, adsorption and desorption, the strong stress sensitivity of matrix and fractures, the abnormal condensation phase transition mechanism, high-speed non-Darcy seepage in artificial fractures, and heterogeneity of reservoir and multiphase flows, the multi-scale nonlinear seepage mechanisms are extremely complicated in shale condensate gas reservoirs. A certain theoretical basis for the engineering development can be provided by mastering the percolation law of shale condensate gas reservoirs, such as improvement of productivity prediction and recovery efficiency. The productivity evaluation method of shale condensate gas wells based on empirical method is simple in calculation but poor in reliability. The characteristic curve analysis method has strong reliability but a great dependence on the selection of the seepage model. The artificial intelligence method can deal with complex data and has a high prediction accuracy. Establishing an efficient shale condensate gas reservoir development simulation technology and accurately predicting the production performance of production wells will help to rationally formulate a stable and high-yield mining scheme, so as to obtain better economic benefits.

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Section: Strong Stress Sensitivity Characteristics Of Shale Matrix An...mentioning

confidence: 99%

Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs

Yang

Qiao

et al. 2023

Energies

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“…e size and distribution of pore radius can be roughly reflected by the pressure and saturation of mercury withdrawal [16,17]. It is not only a function of pore throat radius distribution and pore volume but also a function of porosity, permeability, and saturation.…”

Section: Study On Heterogeneity In Layers With Pore Structurementioning

confidence: 99%

Prediction of Intraformational Remaining Oil Distribution Based on Reservoir Heterogeneity: Application to the J‐Field

Zhang

Fang

Wang

et al. 2021

Advances in Civil Engineering

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At high water cut stage, the study of remaining oil distribution in water-flooding reservoir is the basis of implementing potential-tapping measures and enhancing oil recovery. At present, most of the oilfields in China have entered the stage of ultrahigh water cut. The reserves of the oilfields are highly developed, the situation of water flooding is extremely complex, and it is difficult to predict the distribution of the remaining oil, which seriously restricts the adjustment of the production measures, tapping the potential and improving the ultimate recovery rate. In view of aforementioned difficulties, this study puts forward a research approach to predict remaining oil distribution based on reservoir heterogeneity, which can quantitatively characterize reservoir heterogeneity. In order to avoid the drawback that a single parameter cannot fully describe the characteristics of pore structure, the composite index of pore structure (SQRT(K/Φ)) is introduced to study the pore microstructure. The composite index of pore structure is used to predict the distribution of remaining oil in the formation, and the results are basically consistent with those calculated by numerical simulation. It is concluded that the larger the fractal dimension of the composite index of pore structure is, the stronger the heterogeneity of reservoir is; the smaller the composite index of pore structure is, the smaller the recovery degree is. The composite index of pore structure is used to analyze and predict the distribution of remaining oil in the layer, which provides a new direction for the prediction method of remaining oil.

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“…Shale oil is widely distributed in the world, and the statistics of resource potential evaluation results from 116 basins worldwide reveal that the total technically recoverable resources of shale oil are about 251.2 billion tons, with huge development potential. − The development process of such tight reservoir is subject to the coupling effect of multiple factors, resulting in the deformation of nanopores. − Shale oil reservoir nanoscale pore deformation is mainly under the coupling effect of stress motivation and adsorption motivation deformation. − The indoor experimental analysis, numerical simulation methods, and micromechanical analytical equation analysis are the stress motivation pore deformation research field. − The experimental analysis method is mainly based on the results of experiments. Moreover, the empirical mathematical model of porosity and permeability variation with pore pressure at the macroscopic scale is obtained by fitting the data. − However, such models still contain certain empirical parameters and have a relatively poor applicability for microscopic scales.…”

Section: Introductionmentioning

confidence: 99%

“… 4 − 6 Shale oil reservoir nanoscale pore deformation is mainly under the coupling effect of stress motivation and adsorption motivation deformation. 7 − 9 The indoor experimental analysis, numerical simulation methods, and micromechanical analytical equation analysis are the stress motivation pore deformation research field. 10 − 13 The experimental analysis method is mainly based on the results of experiments.…”

Section: Introductionmentioning

confidence: 99%

Study on the Nanopore Deformation Mechanisms in Shale Oil Reservoir: Insights from the Molecular Simulation

Lei,

Dou,

Hong

et al. 2023

ACS Omega

Self Cite

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The stress and adsorption motivation deformation during shale oil production directly affect its development dynamics. First, a mathematical simulation of pore deformation in shale oil under stress motivation is established. We analyzed the impact of factors including the reservoir pressure, Biot coefficient, bulk modulus, and tortuosity on the deformation characteristics of nanopores. Second, a pore deformation model under multifactor synergistic effect is derived by combining the molecular dynamics, which takes into account the influence of adsorption deformation on the total adsorption of shale oil reservoir. Finally, a shale oil pore deformation model under multifactor synergistic effect is obtained. The results show that the current pore diameter shows a trend of decreasing with the decrease of current formation pressure and the difference with original reservoir pressure increases. The pore shows a trend of less deformation with a decrease in the effective stress coefficient. When the Biot coefficient is 0.8, the pore diameter under 5 MPa is 4.01 nm. When the Biot coefficient decreases to 0.3, the pore diameter under 5 MPa becomes 9.12 nm, an increase of 127.43% compared to 4.01 nm. The bulk modulus affects the magnitude of pore deformation under the same pressure, which means that the pore diameter shows a tendency to deform more easily as the bulk modulus increases. Meanwhile, the pore diameter decreases with increasing tortuosity. In addition, the pore deformation is subject to both stress and adsorption motivation deformation synergistically. The stress motivation deformation leads to a decrease of pore diameter with pressure decrease, while, in contrast, the adsorption motivation leads to an increase of pore diameter. The pore diameter under synergy is influenced by the coupling effect, and the deformation under synergy tends to decrease as the pore diameter decreases. When the rock mechanical parameters are changed so that the pores are not easily deformed by stress, the adsorption motivation deformation plays a dominant role in synergy. The amount of synergistic deformation decreases with increasing temperature, while the change in the component ratio of multicomponent fluid mainly affects the corresponding adsorption and the amount of synergistic deformation. Interestingly, when the proportion of CO 2 is the largest, the corresponding maximum deformation is higher than the other proportions (43.77%). It not only enhances the recovery rate of shale oil reservoirs by utilizing CO 2 but also provides the possibility of geological CO 2 burial.

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An Experimental Study on Stress Sensitivity of Tight Sandstones with Different Microfractures

Cited by 6 publications

References 35 publications

Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs

Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs

Prediction of Intraformational Remaining Oil Distribution Based on Reservoir Heterogeneity: Application to the J‐Field

Study on the Nanopore Deformation Mechanisms in Shale Oil Reservoir: Insights from the Molecular Simulation

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