Much has been written about carbonate reservoir complexities, heterogeneity, and data integration at different scales. However, there are not many published examples that show a comparison of producibility modeling predictions and actual field results that include data from core, advanced openhole well logs, formation testers, and drillstem tests.
In this study, we present the integration of data and measurements from advanced technologies to evaluate reservoir heterogeneity of carbonate formations on multiple scales. Quantitative textural analyses based on a comprehensive suite of petrophysical logging measurements were integrated with core data and formation testing data to characterize hydrocarbon/water transition zones and formation permeability and producibility. The offshore carbonate reservoir studied is composed of limestones and dolomites. Despite the inherent chemical complexities and hidden modes of origin, dolomites often exhibit favorable reservoir quality with high porosity and permeability properties. For this reason, E&P companies continue to predict where drilling targets are most likely to encounter these sweet spots.
Traditional permeability correlations are not effective in these systems, leading to overdependence on porosity-based reservoir descriptions to predict fluid flow. Using nonparametric regression, we have established a relationship between permeability and porosity from logs that are available fieldwide. Subsequent integration of this data with interval pressure transient test data in zones selected based on the observed rock heterogeneity enables further optimization of the final permeability correlation. The descriptions of the field examples confirm the success of this integrated approach and include the planning, real-time monitoring, and final validation of permeability and anisotropy at different scale during the exploration phase of a field.
Selecting the well locations for development using the proposed approach has proved valuable for improving field development practices. The results have led to enhanced reservoir characterization based on flow (permeability) and storage-capacity analyses (porosity partitioning), and a better understanding of the reservoir heterogeneity at different scales; the results have been used to improve drillstem test designs and reservoir production strategies.
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