During the last decade, some problems have appeared and being affecting the oil production of the mature giant oil field such as: flow boundaries, by pass zones, fractures, etc. hence, the characterization of the reservoir by the integration of static and dynamic data acquired along the field life is required. The new generation of static model is justified in the need to involve the lessons learnt from the previous static/dynamic models with the incorporation of the recent studies and well data.

The aim of this article is to integrate the structural seismic interpretation and results of pressure transient analysis obtained from well test, such as distance to potential flow boundaries, average permeability, among others, into the workflow of the new geological static model, through the validation with the conceptual geological understanding of the reservoir. Such workflow not only considers different sources for the reservoir characterization but also reduce the alternative solutions of the well test data to the best-fit solution for the integration.

In a typical geological modeling workflow, structural framework is built first, based on the zones definition that include well information, well log data, structural seismic interpretation and the stratigraphic characterization that allow capturing the vertical heterogeneity. Subsequently, the sedimentary-stratigraphic architecture is used as main constrain together with geostatistical methods to distribute the petrophysical properties for each zones.

The well test results independently are a punctual dynamic response of the reservoir in a portion of the time and within a certain tested area around the well. However, the integration with the conceptual geological model can resolve the uncertainty that alone cannot respond enable a more robust interpretation of main reservoir heterogeneities.

The study proposes the inclusion of the well test data to support and validate, firstly the structural connectivity of the zones through the well test interpretation (validation of faults, dual porosity zones, dense zones, etc.), and secondly calibrate the permeability model with additional dataset than only from cores, which, even though derived from dynamic data, are incorporated in the static model workflow. Implementation of workflow allowed modeling of 48 zones with different petrophysical properties and 122 faults in the static model, which were ranked in three confidence categories. Faults observed by only seismic interpretation were ranked as low, faults calibrated by one of the 57 borehole images logs (BHI) were ranked as mid confidence, and finally, faults that were validated with best-fit result of well test, where interpretation suggest the presence of a boundary as fault and is consistent with the seismic and/or BHI interpretation, is ranked as the highest confidence, inasmuch as the fault is validated statically and dynamically.

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