×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerIn 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.
The aim of this study is to optimize ESP performance by evaluating the current conditions and the performance optimization of the electrical submersible pump (ESP) for six oil wells in the Rmelan oil field. fluid and reservoir properties (API = 23, T = 78 C°, pressure of reservoir = 160 atm and the WC is 70%). This paper presents a sensitivity assay conducted by Nodal Analysis (Using PIPESIM Software) on the pump frequency and wellhead pressure. The outflow tubing performance and inflow performance relationship were generated and plotted for each well. The curves are investigated, indicating problems in some wells (W-12R, W-21KH, and W-21SH). The results of this study show that we can increase the flow rate by optimizing the ESP performance by decreasing the wellhead pressure to 71.58 psi and raising the frequency of ESP to a specific value of about 65 Hz based on the limites of production of each types pump capacity . Increasing the frequency from 55 to 65 Hz resulted in increasing the production from 634 to 1092 bb/day for W-12R, from 1928 to 2806 bbl/day for W-21KH, and from 1722 to 2279 bbl/day for W-21SH.