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Source publication
Gas injection has already proven to be an efficient shale oil recovery method successfully tested all around the world. However, gas-enhanced oil recovery methods have never been implemented or tested for the greatest Siberian shale oil formation yet. This article proposes numerical simulation of a hydrocarbon gas injection process into a horizonta...
Contexts in source publication
Context 1
... areal grid was made non-uniform with the thinnest cells close to the fracture plane and the cell size in the X direction was increased from 0.1 to 5 m. The cell sizes in the Y direction were kept uniform and equal to 5 m ( Figure 1). The main properties of the model are shown in Table 1. ...
Context 2
... distribution at the same time step of the main molar fraction of the N2 + C1 component for all three (five-, eight-, and nine-component) models is shown in Figure 10. Figure 10 shows that the 60.34% component in the main component composition N2 + C1 of the injected associated gas increases the degree of sweep by the gas reservoir. ...
Context 3
... distribution at the same time step of the main molar fraction of the N2 + C1 component for all three (five-, eight-, and nine-component) models is shown in Figure 10. Figure 10 shows that the 60.34% component in the main component composition N2 + C1 of the injected associated gas increases the degree of sweep by the gas reservoir. ...
Context 4
... results of cumulative oil production and pressure dynamics for the selected optimal model in terms of modes are shown in Figures 11-13. The obtained results of calculations showed a negligible effect of diffusion both on the cumulative oil production and on such development indicators as the dynamics of oil production and reservoir pressures compared to the model without diffusion. ...
Citations
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.
