PREDICTION OF TWO-PHASE PRESSURE DROP USING ARTIFICIAL NEURAL NETWORK | ||||
| ERJ. Engineering Research Journal | ||||
| Article 4, Volume 42, Issue 2, April 2019, Page 99-114 PDF (1.52 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2019.66275 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| M.A. El-Kadi1; M.A. Husien1; S.M. El-Behery2; and H. Farouk3 | ||||
| 1Mechanical Power Engineering Dept., Faculty of Engineering, Menoufia University, Shebin Elkom, Egypt. | ||||
| 2Mechanical Power Engineering Dept., Faculty of Engineering, Menoufia University, Shebin Elkom, Egypt | ||||
| 3MAGAPETCO - Magawish Petroleum Co., Cairo, Egypt | ||||
| Abstract | ||||
| In the present paper an Artificial Neural Network (ANN) model is proposed to predict the two-phase pressure drop in oil and gas field. In this model, the effect of number of hidden layers and number of neurons in each layer is selected to generate independent results. In addition, the selected database contains 7581 data sets selected from four different sources from which 1165 data sets are collected from the flowing wells of Magapetco at East Esh Mallaha Marine (EEMM) field. The comparison between ANN predictions and other popular models reveals that the ANN model can predict the pressure drop with fair accuracy. Furthermore, the proposed model is used to predict the pressure distribution along the wall of flowing wells as well as the bottom hole flowing pressure and good accuracy was obtained. | ||||
| Keywords | ||||
| Neural network; Pressure drop; two-phase; oil and gas | ||||
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