Steamflooding has been widely applied as an effective way to improve oil recovery not only in heavy oil reservoirs, but also in light oil reservoirs. Its efficiency comes from its influential rule to enhance oil displacement by flourishing the reservoir and fluid properties. Also, it has been investigated that Steamflooding is a good way to handle the formation's heterogeneity by decrease the degree of fluid spread and distortion. The reservoir under study is a sandstone formation in South Rumaila oil field located in Iraq. This field, with a 59-years production history, has 40 production wells and is surrounded by an infinite active edge water aquifer from the east and the west flanks. The east flank is much less effective than the west one because there are some discontinuous amounts of bitumen close to the oil-water contact that impedes the aquifer water approaching into the reservoir. The formation depth is 10350 ft. sub-sea with a maximum vertical oil column of 350 ft. The average bubble point pressure is 2660 psi and the average reservoir temperature is 210°F while oil density is 34°API. In this study, a comparative thermodynamic simulation study has been conducted to investigate the feasibility of Steamflooding to extract the bitumen and improve oil recovery and also to determine the optimal future reservoir performance with comparative designs of experiments considering the recovery factor as a response function.

Firstly, the thermodynamic reservoir simulator (CMG-STARS) has been used to figure out the feasibility of steam flooding to increase the recovery factor by the end of 12 years future prediction period in comparison with the base case of primary production. Then, nine different experiments within three-levels & four-factors have been set within the orthogonal arrays design (OAD) to get some idea about the factors controlling the reservoir performance. The factors are steam injection rate, steam quality, steam temperature, and number of steam injectors. The regression model of Orthogonal Arrays Design (OAD) has shown that the recovery factor is sensitive only to steam injection rate and number of injectors and the optimal scenario has the highest steam injection rate and the lowest injectors to get the highest recovery factor. Then, the Full Factorial Design (FFD) has been adopted for the same factors, but with distinct levels to formulate 36 high dispersion experiments. The levels of injectors have been selected based on the high connectivity with the producers based on the streamlines-based simulation results after construction such a connectivity matrix between the injectors and producers. The regression analysis of FFD has shown that all the four factors and some interaction among them have a significant effect on the response and the optimal scenario that has the highest recovery factor, has the same levels of the four parameters as what has been obtained from the OAD approach. This reflects the feasibility of Orthogonal Arrays Design to handle the Steamflooding process and determine the optimal future reservoir performance with optimal scenario at small number of experiments.

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