- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network | ||
| Iraqi Journal of Chemical and Petroleum Engineering | ||
| Article 1, Volume 13, Issue 3, 2012, Pages 9-16 | ||
| Authors | ||
| Nada. S. Ahmedzeki; Iqdam. M. Ridha; Yazan. M. Ali; Zainab. T. AbidAlwahab | ||
| Abstract | ||
| 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%. | ||
|
Statistics Article View: 188 PDF Download: 61 |
||