A computer-implemented method for reservoir production optimization, the method comprising: obtaining historical production data associated with production of a hydrocarbon product in a reservoir; obtaining historical tracer test data associated with the production; performing history matching using the historical production data and the historical tracer test data to generate improved geological models, wherein performing history matching comprises generating each of a plurality of vectors of model parameters based on data vectors comprising oil production rates, water production rates, and tracer concentrations for a number of history data assimilation time-steps, wherein the vectors of model parameters are written as m j a = m j f + C MD f C DD f + α i C D − 1 d uc , j − d j f , wherein j = 1,2, ...,N e , where N e denotes a number of ensemble members, C MD f is a cross-covariance matrix between a prior vector of model parameters, m f , and a vector of predicted data, d f , C DD f is a N d × N d auto-covariance matrix of the predicted data, N d denotes a total number of measurements assimilated, d uc ~N(d obs ,C D ) is a vector of perturbed observations, d obs denotes observed data, C D denotes a user defined N d × N d auto-covariance matrix of observed data measurement errors, α i , i=1,2, ...,N a are predefined inflation coefficients that satisfy ∑ i = 1 N a 1 α i = 1 , and N a denotes a number of data assimilation iterations; performing production optimization using the improved geological models, including predicting optimized controls and updating, using the predicted optimized controls, water injection rates and fluid production rates for individual injectors and producers; and applying the predicted optimized controls to the reservoir to optimize future production. obtaining historical production data associated with production of a hydrocarbon product in a reservoir; obtaining historical tracer test data associated with the production; performing history matching using the historical production data and the historical tracer test data to generate improved geological models, wherein performing history matching comprises generating each of a plurality of vectors of model parameters based on data vectors comprising oil production rates, water production rates, and tracer concentrations for a number of history data assimilation time-steps, wherein the vectors of model parameters are written as m j a = m j f + C MD f C DD f + α i C D − 1 d uc , j − d j f , wherein j = 1,2, ...,N e , where N e denotes a number of ensemble members, C MD f is a cross-covariance matrix between a prior vector of model parameters, m f , and a vector of predicted data, d f , C DD f is a N d × N d auto-covariance matrix of the predicted data, N d denotes a total number of measurements assimilated, d uc ~N(d obs ,C D ) is a vector of perturbed observations, d obs denotes observed data, C D denotes a user defined N d × N d auto-covariance matrix of observed data measurement errors, α i , i=1,2, ...,N a are predefined inflation coefficients that satisfy ∑ i = 1 N a 1 α i = 1 , and N a denotes a number of data assimilation iterations; performing production optimization using the improved geological models, including predicting optimized controls and updating, using the predicted optimized controls, water injection rates and fluid production rates for individual injectors and producers; and applying the predicted optimized controls to the reservoir to optimize future production. <EOS>