Production Performance of Gas Condensate Reservoirs: Compositional Numerical Model - A Case Study of Hai Thach - Moc Tinh Fields

Author(s):  
T.V. Tran ◽  
A. T. Ngo ◽  
H. M. Hoang ◽  
N. H. Tran
Author(s):  
Aniedi B. Usungedo ◽  
Julius U. Akpabio

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.


Buildings ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 276
Author(s):  
Nisar Ali Khan ◽  
Giorgio Monti ◽  
Camillo Nuti ◽  
Marco Vailati

Infilled reinforced concrete (IRC) frames are a very common construction typology, not only in developing countries such as Pakistan but also in southern Europe and Western countries, due to their ease of construction and less technical skills required for the construction. Their performance during past earthquakes has been in some cases satisfactory and in other cases inadequate. Significant effort has been made among researchers to improve such performance, but few have highlighted the influence of construction materials used in the infill walls. In some building codes, infills are still considered as non-structural elements, both in the design of new buildings and, sometimes, in the assessment of existing buildings. This is mainly due to some difficulties in modeling their mechanical behavior and also the large variety of typologies, which are difficult to categorize. Some building codes, for example, Eurocode, already address the influence of infill walls in design, but there is still a lack of homogeneity among different codes. For example, the Pakistan building code (PBC) does not address infills, despite being a common construction technique in the country. Past earthquake survey records show that construction materials and infill types significantly affect the seismic response of buildings, thus highlighting the importance of investigating such parameters. This is the object of this work, where a numerical model for infill walls is introduced, which aims at predicting their failure mode, as a function of some essential parameters, such as the friction coefficient between mortar and brick surface and mortar strength, usually disregarded in previous models. A comprehensive case study is presented of a three-story IRC frame located in the city of Mirpur, Pakistan, hit by an earthquake of magnitude 5.9 on 24 September 2019. The results obtained from the numerical model show good agreement with the damage patterns observed in situ, thus highlighting the importance of correctly modeling the infill walls when seismically designing or assessing Pakistani buildings that make use of this technology.


Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1288
Author(s):  
Husam Musa Baalousha ◽  
Bassam Tawabini ◽  
Thomas D. Seers

Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL allows more flexibility through assigning a degree of contribution without specific boundaries for various classes. This study compares the results of DRASTIC vulnerability approach with the FL approach, applying both on Qatar aquifers. The comparison was checked and validated against a numerical model developed for the same study area, and the actual anthropogenic contamination load. Results show some similarities and differences between both approaches. While the coastal areas fall in the same category of high vulnerability in both cases, the FL approach shows greater variability than the DRASTIC approach and better matches with model results and contamination load. FL is probably better suited for vulnerability assessment than the weighted overlay methods.


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