Agradecimentos: This work was carried out in association with the ongoing Project registered under number 20372-9 ANP the “Development of integration between reservoir simulation and seismic 4D - Phase 2" (University of Campinas [UNICAMP]/Shell Brazil/ANP) funded by Shell Oil Brazil Ltda. Under the...

Agradecimentos: This work was carried out in association with the ongoing Project registered under number 20372-9 ANP the “Development of integration between reservoir simulation and seismic 4D - Phase 2" (University of Campinas [UNICAMP]/Shell Brazil/ANP) funded by Shell Oil Brazil Ltda. Under the R & D ANP levy the “Investment Commitment to Research and Development.” The authors are grateful for the support of the Center of Petroleum Studies (CEPETRO-UNICAMP/Brazil), the Department of Energy (DE-FEM-UNICAMP/Brazil), the Research Group in Reservoir Simulation and Management (UNISIM-UNICAMP/Brazil) and Energi Simulation. In addition, a special thanks to Schlumberger and CMG for software licenses

The current work introduces an automatized process coupled with geological modeling to reduce uncertainty in reservoir properties. The method assimilates dynamic data of wells interactively, and applies the deviations to constrain uncertainties. The methodology deals with scalar (e.g. rock...

The current work introduces an automatized process coupled with geological modeling to reduce uncertainty in reservoir properties. The method assimilates dynamic data of wells interactively, and applies the deviations to constrain uncertainties. The methodology deals with scalar (e.g. rock compressibility) and spatial (e.g. porosity) attributes at same time, employing specialized uncertainty reduction procedures. The procedure reduces the uncertainty of scalar attributes through Iterative Discrete Latin HyperCube method (IDLHC). To reduce uncertainties of spatial attributes, we worked on an extension of a regionalized co-simulation (co-DSS) method. The main contributions regard the proposition of update, at same time, both kinds of uncertainties (spatial and scalar); the definition of sequential rules, that simplify the process execution and avoiding subjectivities on the coupling of the geological modeling on data assimilation, as well as the automation of the process. The procedure was validated under a siliciclastic black-oil benchmark field (UNISIM-I-M), established based on Namorado Field, Campos Basin, Brazil. The procedure reduced the range of uncertainty of the scalar attributes, centralizing final PDFs with the values presented in the reference model, without collapse to a particular level, as well as preserved the geological consistency throughout data assimilation, obtaining porosity responses in agreement with the reference porosity distribution. The potential of the procedure is supported by the consistent production forecast observed in the outcomes

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