Multi-Scale Insights on the Threshold Pressure Gradient in Low-Permeability Porous Media

Wang, Huimin; Wang, Jianguo; Wang, Xiaolin; Chan, Andrew

doi:10.3390/sym12030364

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…Ke et al [9] studied the effect of the starting pressure gradient on the remaining oil distribution in the heavy-oil reservoirs, and Tian et al [10] addressed the different factors that affect the starting pressure gradient in the tight sandstone gas reservoirs with high water saturation. Wang et al [11] provided the multi-scale insights on the starting pressure gradient in the low-permeability porous media. As known, the flow of fluids in these reservoirs disobeys to the traditional Darcy's law.…”

Section: Introductionmentioning

confidence: 99%

Determination of Starting Pressure Gradient of Oil and Water in Low-Permeability Reservoirs Using Genetic Algorithm

Kim¹,

Hong²,

Song³

2023

Frontiers in Artificial Intelligence and Applications

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We consider a method for the determination of the starting pressure gradients of oil and water in two-phase flow in low-permeability reservoirs. Moreover, we obtain the relative permeability curves of oil and water according to water saturation for the interpretation of oil-water two-phase flow. In the case of two-phase Darcy flow in reservoirs, in order to obtain the relative permeability curves of oil and water according to water saturation, the JBN (Johnson, Bossler and Naumann) method is improved universally which is based on the analysis of data of two-phase unsteady displacement. The method may be improved in the case of low velocity non-Darcy flow in the low-permeability reservoirs, too. Therefore, in the context, we present a new method by which we can determine the starting pressure gradient of oil and water in two-phase non-Darcy flow in the low-permeability reservoirs. Based on these starting pressure gradients, we obtain relative permeability curves of oil and water according to water saturation by the process of data from two-phase unsteady displacement experiment using the Genetic Algorithm. In order to do for this, when oil and water flow simultaneously, the water content function in the condition of oil-water two-phase flow is obtained from the equations of motion of oil and water, and the equation of determining relative permeabilities using experimental data is presented. Based on this, the starting pressure gradients of oil and water are determined using search method of the Genetic Algorithm with powerful self-adaptability, and the curve of the relative permeability is plotted. The method can be improved effectively to determine the starting pressure gradients and relative permeabilities of oil and water in two-phase seepage in the low-permeability reservoirs and to study the numerical simulation and the reservoir engineering in these reservoirs.

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Section: Introductionmentioning

confidence: 99%

Determination of Starting Pressure Gradient of Oil and Water in Low-Permeability Reservoirs Using Genetic Algorithm

Kim¹,

Hong²,

Song³

2023

Frontiers in Artificial Intelligence and Applications

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“…Wu et al [5] established a multistage fractured horizontal well multi-linear transient pressure model which applied the TPG and permeability modulus to characterize the low-velocity non-Darcy flow and stress sensitivity, respectively. Wang et al [22] established the TPG formula by combining permeability, water saturation and pore pressure, which benefit from multi-scale insights on the determination of the TPG. Fluid will flow in the pseudo threshold pressure gradient model only when the displacement pressure gradient is greater than the pseudo threshold pressure gradient, which reduces the fluid movable range and amplifies flow resistance.…”

Section: Introductionmentioning

confidence: 99%

Well Test Analysis of Inclined Wells in the Low-Permeability Composite Gas Reservoir Considering the Non-Darcy Flow

Zhang²,

Keying³

et al. 2022

Energies

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The application of traditional well test interpretation methods cannot comprehensively consider characteristics of stress sensitivity and non-Darcy flow for low-permeability composite gas reservoirs, which makes it difficult to obtain real reservoir parameters. Based on the micro-mechanism analysis of stress sensitivity and non-Darcy flow in low-permeability gas reservoirs, the flow motion equation was improved. Thus, a mathematical model was established which belongs to the inclined well in the composite gas reservoir with a conventional internal zone and low-permeability external zone. Applying the finite element method to solve the flow model through Matlab programming, the equivalent pressure point was selected to research the pressure distribution of the inclined well. On this basis, the bottom hole pressure dynamic curve was drawn, the flow process was divided into seven stages, and the parameter sensitivity analysis was carried out. Finally, the advanced nature of the new model applied to the interpretation of the well test model is compared by conventional methods. The non-Darcy flow can cause the gradual upward warping of the bottom hole pressure dynamic curve in the later stage, and non-linear enhancement leads to an increase in the upturn through the simulation test. When the inclination angle is greater than 60°, early vertical radial flow and mid-term linear flow gradually appear. A decrease leads to a shorter duration of the pseudo radial flow in the internal zone and the radius of the internal zone. The conduction coefficients ratio of internal and external zones affects the pseudo pressure derivative curve slope in transition phase of pseudo radial flow in the internal and external zones. A comprehensive consideration of the low-permeability composite gas reservoir flow characteristics can improve the fitting degree of the pressure curves. Not only that, but it can also solve the strong diversification of reservoir parameters. Results have a guiding significance for low-permeability composite gas reservoir development and pressure dynamic evaluation in inclined wells.

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“…The fluid flow behavior in shale reservoirs does not conform to the classic Darcy’s law, as shown in Figure , and it needs to overcome the threshold pressure to start the movement. , The threshold pressure is an important parameter to characterize the nonlinear flow behavior of fluid; however, its underlying physical mechanism is not well-understood, and its value is usually simplified to a constant in the percolation model. , …”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effect of Wetting Hysteresis on Fluid Flow in Shale Oil Reservoirs

Gao

Chen

et al. 2021

Energy Fuels

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Wetting hysteresis is an important factor affecting the production of oil reservoirs, especially in the nanopores of shale, and it has an important practical significance to study the influence of wetting hysteresis on fluid flow in shale oil reservoirs. The threshold pressure model and flow resistance model after the movement of the droplet in two-phase fluid systems were established on the basis of the static wetting hysteresis equation and dynamic contact angle equation, respectively. Combining the proposed models and experimental data in the literature, the threshold pressure and flow resistance with the varying flow velocity were obtained for different hydrocarbons in pores with different sizes. The results show that the threshold pressure and flow resistance both increase with the decrease of the pore size, and they cannot be ignored in nanoscale pores of shale oil reservoirs. Moreover, the flow resistance caused by the dynamic wetting hysteresis is greater than the threshold pressure caused by the static wetting hysteresis, and the flow resistance increases with the increase of the flow velocity. This work provides mathematical models for accurately characterizing the threshold pressure and flow resistance of two-phase fluid systems in nanopores, which will pave a way for the accurate numerical simulation of shale oil reservoirs.

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Multi-Scale Insights on the Threshold Pressure Gradient in Low-Permeability Porous Media

Cited by 5 publications

References 36 publications

Determination of Starting Pressure Gradient of Oil and Water in Low-Permeability Reservoirs Using Genetic Algorithm

Determination of Starting Pressure Gradient of Oil and Water in Low-Permeability Reservoirs Using Genetic Algorithm

Well Test Analysis of Inclined Wells in the Low-Permeability Composite Gas Reservoir Considering the Non-Darcy Flow

Effect of Wetting Hysteresis on Fluid Flow in Shale Oil Reservoirs

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