Scale dependent dynamic capillary pressure effect for two-phase flow in porous media

Abidoye, Luqman K.; Das, Diganta Bhusan

doi:10.1016/j.advwatres.2014.09.009

Cited by 56 publications

(37 citation statements)

References 36 publications

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“…Relative permeability responds to the change of capillary pressure 9,11 and also reflects the stability of the displacement front. The quick decrease in the oil relative permeability demonstrates the more nonuniform front during the displacement process with the viscous oil.…”

Section: Relative Permeabilitymentioning

confidence: 99%

“…Several equations have been proposed to quantitatively demonstrate the dynamic effect on the P c -S w relationship, [9][10][11] and a widely used equation has been proposed by Hassanizadeh and Gray as follows 12,13 : where P d c represents the dynamic capillary pressure, MPa, dependent on flow dynamics; P s c is the steady capillary pressure at equilibrium conditions, MPa, an intrinsic property of the porous medium-fluid system; S w ∕ t is the time derivative of the wetting fluid phase saturation, s −1 ; τ is the dynamic coefficient, Pa·s; and P w and P nw denote the wetting and nonwetting phase pressure, respectively, MPa.…”

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confidence: 99%

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Dynamic capillarity during displacement process in fractured tight reservoirs with multiple fluid viscosities

Luo

et al. 2019

Energy Science & Engineering

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Dynamic capillarity commonly exists for multiphase flow in porous media, during which fluid viscosity varies and has strong influence. Displacement experiments are conducted on water-wet, fractured tight rock at in situ pressure and temperature of an oil reservoir via a specially designed apparatus to investigate the effects of fluid viscosity on the dynamic capillarity. The dynamic effect in the matrix is examined through the measurement and calculation of capillary pressure, the dynamic coefficient, and the fluid flow behavior. The results show that with a higher oil viscosity:(a) both the steady and the dynamic capillary pressures reverse their directions more quickly and behave as larger resistances in the matrix; (b) the difference between the steady and the dynamic capillary pressures becomes around 5%-19% more significant; (c) water saturation changes more slowly corresponding to the lower water relative permeability, while oil relative permeability quickly becomes lower than that during the basic displacement process; and (d) the dynamic coefficient becomes 2-3 times higher, and the dynamic contact angle becomes 10%-25% larger, showing a more variable interface. A contact angle advancement coefficient is proposed to identify the significance of contact angle advancement and the competition between capillary pressure and viscous force. The findings of this study can help for better understanding of multiphase flow in tight reservoirs and enhancing oil recovery.

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Section: Relative Permeabilitymentioning

confidence: 99%

mentioning

confidence: 99%

Dynamic capillarity during displacement process in fractured tight reservoirs with multiple fluid viscosities

Luo

et al. 2019

Energy Science & Engineering

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“…However, a brief explanation of the s determination is included for completeness of the discussion. Furthermore this will throw light at the approach employed in this work [57]. Different approaches have been reported in the literature for this purpose.…”

Section: Dynamic Coefficient (S) Calculationmentioning

confidence: 99%

“…The TDR probe (CS640) with rod length 7.5 cm and diameter 0.159 cm, was used to determine the water content of the porous medium sample locally. Calibration of the PTs was done with a portable pressure calibrator, DPI 610 (Druck Limited, Leicester, UK) as discussed by Abidoye and Das [57]. Using the outflow weight of water obtained on weighing balance, average domain saturation was determined using a graduated glass cylinder placed on an accurate weighing balance which was connected to the computer and data logged in real time by the weighing balance software (A&D Company Limited, San Jose, USA).…”

Section: Instrumentation and Column Preparationmentioning

confidence: 99%

Scale dependency of dynamic relative permeability–satuartion curves in relation with fluid viscosity and dynamic capillary pressure effect

et al. 2016

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Capillary pressure-saturation-relative permeability relationships (P c -S w -K r ) are functions of importance in modeling and simulations of the hydrodynamics of two-phase flow in porous media. These relationships are found to be affected by porous medium and fluid properties but the manner in which they are affected is a topic of intense discussion. For example, reported trends in fluid viscosity and boundary conditions effects have been found to be contrary to each other in different studies. In this work, we determine the dependency of dynamic K r -S w relationships (averaged data) on domain scale in addition to investigating the effects of fluid viscosity and boundary pressure using silicone oil (i.e. 200 and 1000 cSt) and water as the respective non-wetting and wetting fluids with a view to eliminating some of the uncertainties reported in the literature. Water relative permeability, K rw , was found to increase with increasing wetting phase saturation but decreases with the increase in viscosity ratio. On the other hand, the oil relative permeability, K rnw , was found to increase with the increasing non-wetting phase saturation in addition to the increase in viscosity ratio. Also, it was found that with the increasing boundary pressure K rw decreases while K rnw increases. The influence of scale on relative permeability was slightly indicated in the non-wetting phase with K rnw decreasing as domain size increases. Effect of measurement location on dynamic relative permeability was explored which is rarely found in the literature. Comparison was also made between K r -S w relationships obtained under static and dynamic condition. Finally, mobility ratio (m) and dynamic coefficient (s) were plotted as a function of water saturation (S w ), which showed that m decreases as s increases at a given saturation, or vice versa.

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“…As discussed extensively in the literature, the properties of the two-phase system (e.g., interfacial tension, capillary pressure, density and viscosity of each fluid phase) and porous medium (e.g., porosity, permeability, pore size distribution, heterogeneity) are important in determining the flow behavior and, hence, the P c -S w relationships (Bear 1972;Corey 1994;Das et al 2004;Das et al 2007; Mirzaei 2012, 2013;Abidoye and Das 2014). In most cases, empirical data for the P c -S w relationships are obtained by means of laboratory experiments carried out on porous samples that are up to 10-12 cm long, and it is often assumed that the porous sample is homogeneous at that scale.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network to Determine Dynamic Effect in Capillary Pressure Relationship for Two-Phase Flow in Porous Media with Micro-Heterogeneities

et al. 2014

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An artificial neural network (ANN) is presented for computing a parameter of dynamic two-phase flow in porous media with water as wetting phase, namely, dynamic coefficient (τ), by considering micro-heterogeneity in porous media as a key parameter. τ quantifies the dependence of time derivative of water saturation on the capillary pressures and indicates the rates at which a two-phase flow system may reach flow equilibrium. Therefore, τ is of importance in the study of dynamic two-phase flow in porous media. An attempt has been made in this work to reduce computational and experimental effort by developing and applying an ANN which can predict the dynamic coefficient through the "learning" from available data. The data employed for testing and training the ANN have been obtained from computational flow physics-based studies. Six input parameters have been used for the training, performance testing and validation of the ANN which include water saturation, intensity of heterogeneity, average permeability depending on this intensity, fluid density ratio, fluid viscosity ratio and temperature. It is found that a 15 neuron, single hidden layer ANN can characterize the relationship between media heterogeneity and dynamic coefficient and it ensures a reliable prediction of the dynamic coefficient as a function of water saturation.

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Scale dependent dynamic capillary pressure effect for two-phase flow in porous media

Cited by 56 publications

References 36 publications

Dynamic capillarity during displacement process in fractured tight reservoirs with multiple fluid viscosities

Dynamic capillarity during displacement process in fractured tight reservoirs with multiple fluid viscosities

Scale dependency of dynamic relative permeability–satuartion curves in relation with fluid viscosity and dynamic capillary pressure effect

Artificial Neural Network to Determine Dynamic Effect in Capillary Pressure Relationship for Two-Phase Flow in Porous Media with Micro-Heterogeneities

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