Review of Information Engineering and Applications

Published by: Conscientia Beam
Online ISSN: 2409-6539
Print ISSN: 2412-3676
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Current Approaches in Prediction of PVT Properties of Reservoir Oils

Pages: 31-40
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Current Approaches in Prediction of PVT Properties of Reservoir Oils

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DOI: 10.18488/journal.79.2018.52.31.40

Hajirahimova Mаkrufa , Aliyeva Aybeniz

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Hajirahimova Mаkrufa , Aliyeva Aybeniz (2018). Current Approaches in Prediction of PVT Properties of Reservoir Oils. Review of Information Engineering and Applications, 5(2): 31-40. DOI: 10.18488/journal.79.2018.52.31.40
PVT (pressure-volume-temperature) properties of reservoir fluids in the oil and gas industry constitute an integral part of the required data for a thorough study of the reservoir, optimally compilation of oil production and operation schemes. In the absence of PVT data that measured in laboratory conditions, empirical correlation is used to evaluate these properties. These correlations cannot be applied universally due to the differences of crude oil composition, the working condition of geographical and oil environment. In the article widespread correlations and models was investigated in the field of prediction of PVT properties of reservoir oil from different regions. Their accuracy and productivity was thoroughly analyzed too.
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Creation of Algoritms for Recommendation System Based on Users Data on Internet Advertisement Marketing

Pages: 41-48
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Creation of Algoritms for Recommendation System Based on Users Data on Internet Advertisement Marketing

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DOI: 10.18488/journal.79.2018.52.41.48

Kamala K. Hashimova

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Kamala K. Hashimova (2018). Creation of Algoritms for Recommendation System Based on Users Data on Internet Advertisement Marketing. Review of Information Engineering and Applications, 5(2): 41-48. DOI: 10.18488/journal.79.2018.52.41.48
Nowadays, products are offered to buyers in different varieties and qualities on the Internet environment. Recommedation systems are needed to make the right choices and make effective decisions. The article offers a new method and algorithm based on data obtaned through different ways and by creating hybrid recommendation systems. Estimation method is given based on information about objects and users for proper development of the algorithm. The proposed method can identify the proximity between the users group and the objects the users are interested in.
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