In integrated models, reservoirs and production systems have many variables that make problems difficult to solve. This work complements a suggested methodology to reduce the number of design and operational parameters to obtain a good performance of the field production. We evaluated and validated...

In integrated models, reservoirs and production systems have many variables that make problems difficult to solve. This work complements a suggested methodology to reduce the number of design and operational parameters to obtain a good performance of the field production. We evaluated and validated the applied methodology for a different benchmark case, checking possibilities of extension to other cases. The case study considered a carbonate reservoir benchmark similar to a Brazilian pre-salt case. We evaluated the combination of several parameters through a decoupled sensitivity analysis for production system, selecting those which promoted greater impacts on production to be evaluated and selected in an integrated sensitivity analysis leading to an improvement in the field productivity and net present value. Sensitivity analyses were relevant to reduce the number of variables for robust optimisation problems through the reduction of the search space, favouring the decrease of the computational time and discontinuity problems

Fechado