Reducing the Uncertainty of Static Reservoir Model in a Carbonate Platform, Through the Implementation of an Integrated Workflow: Case A-Field, Abu Dhabi, UAE

摘要

The prediction of the spatial distribution of petrophysical properties within heterogeneous reservoirs are affected by significant uncertainties when based only on well information. However, integrating additional constraints such as 3D seismic data and sedimentary concepts can significantly improve the accuracy of reservoir models and help reduce uncertainties on predictions away from wells. The aim of this study is to build a reliable 3D geological static model through an integrated workflow using petrographic and sedimentary reports and the current understanding of the sedimentary conceptual model for the field in order to reduce the uncertainty. These core interpretations provide a clear description of the facies architecture across the A-Field, serving as excellent reference during seismic stratigraphy interpretations and lead into a geological distribution of the petrophysical properties in the reservoir through the facies models. An integrated approach for facies modeling was implemented in order to generate stochastic models of the facies associations capable to reproduce the natural transition through the sequences. This method was adopted to model the high-resolution prograding pulses in the carbonate platform that were interpreted through cores description and facies association interpretation for both reservoirs. The final 3D sedimentary-stratigraphic architecture is used as main constrain to model the petrophysical properties for each reservoirs. Under this approach, these models can account for varying the spatial continuity of reservoir properties honoring the different sedimentary facies. Facies-based property models preserve the facies-specific statistical distribution of the property, as well as its depositional direction. The facies-based 3D petrophysical models provide an improved prediction of petrophysical properties distribution and reservoir heterogeneity. The permeability simulation based on facies and the cloud transform between porosity and permeability allows better control of spatial connectivity patterns across the reservoir that could be used for improving reservoir performance predictions as it was carried out in the present static model.