Semi-analytical model to predict the performance of cyclic steam stimulation oil wells

Abstract Prediction of the performance oil wells under Cyclic Steam Stimulation (CSS) is challenging in complex and heterogeneous reservoirs, especially with limited data. Analytical numerical simulation models do not usually give accurate predictions such conditions. In this work, a semi-analytical model was developed to determine consistent mathematical relationships between injected steam some effective production parameters for more prediction rates. Field investigation indicates that change Cumulative Oil Ratio (COSR) days related group parameters. This includes cumulative relative drainage volume, net pay thickness gross thickness, vertical permeability thermal diffusivity. These were arranged two dimensionless groups. It found plotting these groups on Log–Log scale any reservoir yields straight line (correlation). For CSS, measurements cycles are sufficient identify constants proposed correlation. method has been applied validated six reservoirs different characterizations. Six total 43 from analyzed same approach. The calculated, plot constructed each well using data first cycles. Then, correlation used predict starting third cycle. At end, predicted compared corresponding actual measurements. results showed average absolute percentage deviation through lifetime less than 5% wells. addition, instantaneous individual cycle all cases (1) 15% about 42% tested CSS cycles, (2) 15 25% 39% (3) higher 19% work considered an original contribution develop can be operations required historical rate, injection basic petrophysical