High uncertainties associated with unknown fluids and pressure distributions could hamper the history matching process. Accordingly, efforts have been made to evaluate these properties distributions from static and dynamic seismic attributes. Nevertheless, these new methodologies aim to develop quantitatively seismic data integration, which require a suitable association between Petro-Elastic and Flux Models parameters dealing with the inherent inter-dependence between simulation and rock physics parameters.

In this paper it is presented an iterative workflow between two optimization processes. Firstly, a coupling between a Petro-Elastic Model and a reservoir simulator provides Acoustic Impedance (AI) values for two numerical models that have to be matched. The one that has to be honored provides the synthetic "observed" AI data and the other gives the calculated AI values. An objective function based on these is minimized through a Pre-Conditioned Conjugate-Gradient method under reservoir simulation constraints, in order to achieve saturation and pressure trends.

As a second step, a history matching procedure where the saturation/pressure values derived from the former one are now the models to be honored. Then, this information is combined with flux lines in the parameterization phase delineating reservoir heterogeneities to define regions where permeability objective functions are optimized. The saturation/pressure trends, evaluated by this last step, are used to update the initial inputs at the first one, providing history matching constraints to the overall processes.

This technique allowed to determine faults and permeability channels with less uncertainties and higher accuracy and decreasing in time-consuming of the history matching procedure was obtained. Moreover, this methodology improved the reservoir behavior predictions reliability, through quantitative seismic data integration in the history matching process.

Certainly the major goals are the integration aspects of this proposed methodology combined with the obtained improvements in the history matching process.

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