Usungedo, Aniedi B. and Akpabio, Julius U. (2020) Evaluating the Challenges in Pressure – Volume – Temperature (PVT) Analysis of Gas Condensate Reservoirs. Journal of Engineering Research and Reports, 16 (3). pp. 13-18. ISSN 2582-2926
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Abstract
Aims: The variations in production performances of the Black oil and compositional simulation models can be evaluated by simulating oil formation volume factor (Bo), gas formation volume factor (Bg), gas-oil ratio (Rs) and volatilized oil-gas ratio (Rv). The accuracy of these two models could be assessed.
Methodology: To achieve this objective some basic parameters were keyed into matrix laboratory (MATLAB) using the symbolic mathematical toolbox to obtain accurate Pressure Volume Temperature (PVT) properties which were used in a production and systems analysis software to generate the production performance and hydrocarbon recovery estimation. Standard black oil PVT properties for a gas condensate reservoir was simulated by performing a series of flash calculations based on compositional modeling of the gas condensate fluid at the prescribed conditions through a constant volume depletion (CVD) path. These series of calculations will be carried out using the symbolic math toolbox. PVT property values obtained from both compositional modeling and black oil PVT prediction algorithm are incorporated to determine the production performance of each method for comparison.
Results: The absolute open flow for the black oil PVT algorithm and the compositional model for the Rs value of 500 SCF/STB and Rs value of 720SCF/STB were 130,461 stb/d and 146,028 stb/d respectively showing a 10.66% incremental flow rate.
Conclusion: In analyzing PVT properties for complex systems such as gas condensate reservoirs, the use of compositional modeling should be practiced. This will ensure accurate prediction of the reservoir fluid properties.
Item Type: | Article |
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Subjects: | Library Keep > Engineering |
Depositing User: | Unnamed user with email support@librarykeep.com |
Date Deposited: | 11 Mar 2023 06:31 |
Last Modified: | 24 Apr 2024 09:23 |
URI: | http://archive.jibiology.com/id/eprint/343 |