Summary
Rock typing into flow units (FUs) plays a pivotal role in constructing static and dynamic models of petroleum reservoirs. Decisions made by asset teams mostly depend on predictions of how fluids will percolate through the subsurface during the reservoir life cycle. In carbonate settings, dealing with rock typing is complex and can generate a large quantity of units because of diagenetic processes such as dissolution, cementation, and silicification. Most rock‐typing methods in carbonates successfully classify small‐scale flow heterogeneity in well resolution but fail when interpolating those facies further away from the 1D domain, because of the lack of correlation between FUs and spatial data. Seismic data can be used to detect large‐scale FUs and assist the interpolation of small‐scale FUs in 3D reservoir volume, thus producing more‐realistic static and dynamic models.
We propose a modification of the classical rock‐typing methods that use permeability () vs. porosity (ϕ) plots and electrical properties, with a data set from the Mero Field, part of the giant Libra Field of presalt carbonate reservoirs in offshore Brazil. From the permeability cumulative S‐curve analysis, we established major large‐scale FUs that maintain part of the carbonate flow heterogeneity and correlate them with the elastic attributes: P‐impedance (PI) and S‐impedance (SI). In addition, we established a priori PI and SI correlations with the formation‐factor (FF) (F) parameter to categorize large‐scale FUs using the F vs. k methodology.
With the large‐scale FUs mapped in seismic data sets, core‐plug‐scale FUs can be populated into the 3D static and dynamic models using geostatistics tools, thus creating more‐realistic reservoir models and assisting asset teams in the decision‐making process.