Record Details

Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network

Iraqi Journal of Chemical and Petroleum Engineering


Field	Value

Title	Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network

Creator	S. Ahmedzeki, Nada. M. Ridha, Iqdam M. Ali, Yazan T. AbidAlwahab, Zainab

Description	Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability. Trend test was performed to ensure that the developed model would follow the physical laws. Results show that the developed model outperforms the published correlations in term of absolute average percent relative error of 6.5%, and correlation coefficient of 96%.

Publisher	University of Baghdad/ College of Engineering

Date	2012-09-30

Type	info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion

Format	application/pdf

Identifier	http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/337

Source	Iraqi Journal of Chemical and Petroleum Engineering; Vol 13 No 3 (2012): Iraqi Journal of Chemical and Petroleum Engineering; 9-16 المجلة العراقية للهندسة الكيمياوية وهندسة النفط; مجلد 13 عدد 3 (2012): Iraqi Journal of Chemical and Petroleum Engineering; 9-16 2618-0707 1997-4884

Language	eng

Relation	http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/337/336