An efficient approach for the determination of oil production rate during the water-flooding recovery method

In this work, a mathematical methodology namely, least square support vector machine (LSSVM) is implemented to predict the variation of oil production rate as a function of oil water viscosity ratio and water injection rate for water-flooding. Furthermore, the coupled simulated annealing (CSA) optimization technique is coupled with LSSVM to find the optimal architecture and parameters of the LSSVM. The obtained results demonstrate that the CSA-LSSVM estimations are in a satisfactory agreement with literature-reported data and the previously published correlation. Consequently, the R² and average absolute relative deviation of CSA-LSSVM model in testing phase are reported 0.979 and 8.15, respectively.