Flow capacity evaluation in carbonate reservoirs is known to be challenging because of heterogeneity in the rock matrix. The original depositional texture and resulting pore structure is often altered by secondary diagenetic processes such as dissolution, leaching, cementation, and dolomitization, creating complicated pore systems with varying porosity to permeability relationship. Dolomitization in particular is known to be an important diagenetic process in carbonate reservoirs, typically enhancing porosity and permeability development and making the rock less susceptible to porosity reduction due to increasing effective stress during burial. Core data taken in deep carbonate reservoirs reveal a strong correlation between degree of dolomitization and reservoir quality.

Neutron-induced gamma-ray spectroscopy logging has proven to be a powerful tool for the evaluation of dolomite content, especially in wells drilled with barite-weighted mud where PhotoElectric Factor (PEF) is not reliable. Using methods developed on a core database, reservoir rock types can be identified and matrix permeability can be estimated from a combination of porosity and dolomite content derived from neutron-induced gamma-ray spectroscopy data and other common logs measurements. Predicted flow profiles and flow capacity of the reservoirs can be calculated from the estimated matrix permeability and can be verified by comparison with available production logs and test data.

Several examples will highlight the comparison between the predicted synthetic flow profiles and the flow profiles measured by production logs, as well as the comparison of estimated flow capacity with pressure transient analysis data. Such comparisons can be used to diagnose stimulation effectiveness, identify zones dominated by fractures, confirm solid bitumen effects, and identify zones with significant formation damage. Another important application is the selection of perforation and stimulation zones to achieve optimum production based on the expected permeability contrast. This integrated approach to flow capacity prediction is proving to be an effective tool in understanding the behavior of complex carbonate reservoirs.

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