Cover
Vol. 2 No. 2 (2026)

Published: June 30, 2026

Pages: 22-32

Research Article

Development of new models for predicting the oil recovery of sandstone reservoirs

Dunya Jankiz Murad 1 Tarek M. Aboul-Fotouh 2 Abu Zied Emer Trends in Eng and Ahmed 2 Sayed Gomaa 2
1 Department of Petroleum Engineering, the Institute of Science and Modern Technology, Rojava University, Qahtaniye, Syrian Arab Republic
2 Mining and Petroleum Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt
History
  • Received: May 16, 2026
  • Revised: June 11, 2026
  • Accepted: June 13, 2026
  • Available Online: June 30, 2026
DOI

https://doi.org/10.65505/ETES-26-0006

Abstract

In this paper, a new correlation was developed (139 data sets) in this study to predict the oil recovery for sandstone solution gas drive reservoirs (SGDR) using NLMR with a coefficient of determination, R2 of 0.90 (compared to 0.87 for Gulstad correlation). An artificial neural network (ANN) model was developed for this reservoir giving an R2 of 0.92. A correlation was developed (111 data sets) in this study to predict the oil recovery for sandstone water drive reservoirs (SWDR) using NLMR with a coefficient of determination, R2 of 0.93 (compared to 0.91 for American Petroleum Institute, API correlation). The developed ANN model for this reservoir gives an R2 of 0.94.

Keywords

References

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