AbstractThis research aims to develop a synthetic model of a petroleum reservoir. The model will be used to estimate how petroleum reservoirs perform under the effect of various oil production scenarios such as natural oil production, high and low salinity water injection. The application of these scenarios will help in investigating the best options for increasing the oil recovery factor from existing oil wells by reducing the amount of residual oil in reservoirs rather than drilling new oil production wells.
The process of conducting this research involved the use of the reservoir simulation software, ECLIPSE, to build the reservoir model and to predict its performance. Microsoft Excel was also used to generate correlations from the simulation outputs. The simulation was initially conducted to investigate the performance of the developed reservoir model for the case of natural oil production where an oil recovery factor of 4.45% was achieved for a small reservoir model that has one oil production well. Later, an improved model with five water injection wells and one production well was developed and used for the next stage of the simulation. The oil recovery factor from this model reached 28% when injecting high salinity water into the reservoir. Various other simulation options, such as changing the depth of perforations and injecting water with lower salinity, were subsequently performed. After completing the planned simulation scenarios, the developed model was modified to match the size of an actual reservoir, and the simulation was run for various water salinity scenarios ranging from high (100,000 ppm) to low salinity (0 ppm). The results showed that the oil recovery factor could be improved from 41% for the case of high salinity water injection to 76% when injecting low salinity water, which represents an increase of 35% in the oil produced. These results were implemented in a model with actual reservoir data and the simulation results showed that the oil recovery factor was improved from 31% for the case of injecting high salinity water to 57% when injecting low salinity water.
|Date of Award||31 Aug 2018|
|Supervisor||Sina Rezaei Gomari (Supervisor), Munir Ahmad (Supervisor) & Nashwan Dawood (Supervisor)|