Reservoir behavior and complexity brings lot of uncertainties in Production Optimization modeling, used to assess:
– the confidence level of the optimized plant configuration
– the uncertainty impact of the inputs on the increased production expected
kwantis defined statistical distributions of these uncertainties, from field data and production tests analysis.

A two stages analysis has been added to the optimization cycle:
– generate an “optimized field configuration” based on “Most Likely” data for all uncertain parameters (mostly curve pressure / flow rate);
– combine the probabilistic distributions of each uncertain parameter using a Monte Carlo simulator keeping “locked” the configuration of the plant (“optimized field configuration”).
The analysis quality has been significantly improved by a statistical definition of the inputs distributions, fitting the input variables on past field data and production tests.

“Enhance simulation accuracy through statistical fitting of input variables”

Finally, correlation coefficients between the variables have been calculated to establish the relationship between them.