Fluid flow in gas condensate reservoirs: the interplay of forces and their relative strengths

Ursin, Jann-Rune

doi:10.1016/j.profnurs.2003.09.005

Cited by 16 publications

(3 citation statements)

References 10 publications

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“…The flow of gas and oil is generally parallel, even though the fluids are located in different parts of the pore system or pore channels. The flow velocity, however, is quite different as the gas is flowing much faster than the oil Ursin (2004).…”

Section: A Two-phase Reservoir Production Modelmentioning

confidence: 99%

“…The interaction between gas and oil in the reservoir and the reservoir itself can possibly be broken down into a study of the relative strength between basic forces such as; viscous, capillary, gravitational and inertial forces. In principle it should be possible to relate the saturation profile S o (r, t) to the competition between the various forces acting inside the reservoir pore system, as indicated by Ursin (2004). This would certainly be an interesting project for further study.…”

Section: A Two-phase Reservoir Production Modelmentioning

confidence: 99%

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Linear dynamics of gas condensate well deliverability

Ursin

2007

Transp Porous Med

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The dynamics of fluid flow in gas condensate reservoirs are investigated by way of analytical description of radial two phase flow. Based on a single phase semi steady-state solution, the application of Kirchhoff's transformation and a simple dynamic model of reservoir oil saturation, revised calculations of the bottom hole pressures and additional production volumes from initially condensed oil, are performed. The above model is presented in great detail and various tests involving different parameters are performed. Tests with respect to critical oil saturation and saturation profiles are presented for both light and heavy gas condensates. Calculations are based on assumptions about shape and profile of the condensed oil saturation in the reservoir; S o (r, t). The model shows how pressure draw-down and oil/gas production can be revised given the information about this saturation profile. In the model is all condensed oil not contained within the saturation profile, produced to the surface. The model might be of interest in early well pressure and production forecast simulations and as a tool in analysis of well-pressure-test data. 376 J. R. Ursin Nomenclature B o , B g : Volume factors for oil and gas; [Rm 3 /Sm 3 ]

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Section: A Two-phase Reservoir Production Modelmentioning

confidence: 99%

Section: A Two-phase Reservoir Production Modelmentioning

confidence: 99%

Linear dynamics of gas condensate well deliverability

Ursin

2007

Transp Porous Med

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“…Near wellbore, at high velocities, two competing phenomena occurred; inertia and positive coupling [5]- [7]. The inertia effect happens in high fluid velocity and causes additional pressure drop during movement.…”

Section: Introductionmentioning

confidence: 99%

Enumeration Approach in Condensate Banking Study of Gas Condensate Reservoir

Fuad,

Lee,

Negash

et al. 2023

Unconventional Methods for Geoscience, Shale Gas and Petroleum in the 21st Century

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This paper presents Enumeration Method in gas condensate reservoir simulation to study the condensate banking complex physics phenomena. Initially, coarse scale grid is commonly used for gas condensate reservoir simulation study. Nevertheless, the coarse scale simulation disregards the condensate bank or it is not able to demonstrate the precise distribution and effects. By introducing Local Grid Refinement (LGR) in simulation model arguably brings a better representation of the condensate bank effect near wellbore but significantly increases the run time. This become severe especially in full field modeling with comingled production. Therefore, enumeration initialization approach was developed to divide the simulation explicitly in coarse scale simulation. During the stops, a region near wellbore was designed where condensate bank parameters were modified based on the history matching. Hence, the drastic change of well performance due to condensate banking could be captured. This drastic change could not physically described in conventional coarse scale simulation model, thus affect prediction accuracy. Comparison between enumeration ways with conventional approach were then investigated. It was found that enumeration method shows a better prediction in investigating the behavior. This is due to its ability to predict mobility changes due to condensate banking, consequently, improve the condensate bank characterization.

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