Estimation of effective permeability at the reservoir scale has been a long standing challenge in carbonate fields. The carbonate depositional and diagenetic history can be quite complex, and this can lead to a permeability field which is quite difficult to characterize. Permeability in vuggy or fractured intervals can be dramatically different from the matrix permeability measured in core plugs. However realistic estimates of oil recovery, and optimized reservoir management requires good estimates of the reservoir permeability. In the Tengiz field, a giant carbonate reservoir in western Kazakhstan, a method has recently been developed to calculate apparent permeability (APERM) based on flow rate from production (PLT) logs. Incorporation of this flow calibrated apparent permeability into the static geologic earth model offers an elegant solution to the long-standing problem of how to best incorporate dynamic PLT data into a reservoir model. A reservoir model recently built using APERM resulted in a step change improvement over previous methods where only static log based permeability transforms were used to populate the earth model. Conventional log based permeability transforms are designed to characterize matrix permeability but not the excess permeability due to fractures & vuggy porosity common in carbonate reservoirs. The APERM method is used for both accurately characterizing total permeability (matrix + excess), and for identifying inaccurate permeability predictions in older wells with poor log quality or limited log data. The log based permeability predictions are more accurate in recent wells with modern logs, but hot streak identification and quantitative permeability estimation from static well logs is still problematic. The apparent permeability is calculated by solving Darcy's law on an interval basis, using as input our knowledge of flowing and static pressures, plus well, reservoir, and fluid properties. The method makes several simplifying assumptions, but the resulting errors are second order in nature, and the method offers improvements over using conventional static log based transform permeability. Application of the method is enhanced by the derivation of coarse scale zonal layer pressures with multi-rate PLTs. Accurate zonal layer pressures improve the accuracy of the permeability derivation. The apparent permeability from PLT is then used as a benchmark to adjust the transform permeability derived from static well logs using a variable multiplier. This technique has the advantage of preserving the original fine scale heterogeneities of the wireline logs, while calibrating their magnitudes. It also has the advantage of identifying higher permeability intervals from rapid changes in well inflow profile, that may not have been characterized by conventional (core plug and wireline) estimates. Recently a full field reservoir model for Tengiz Field has been constructed using APERM data and petrophysical rock types. Preliminary history match results from the model show that use of APERM has increased confidence in the modeled permeability field before history match. Fewer changes are required to calibrate the full field reservoir model to well pressure data (SGS). Permeability-Height (KH) estimates from the model are a much better match to well test KH, than models derived from core transforms. The models also have significantly more heterogeneity, as shown by Dykstra-Parsons calculations. A similar improvement in history match was recently observed in a high resolution model constructed using APERM to monitor gas movements in the Tengiz platforms area. History match pulse tests have shown that this model has a much better prediction of the inter-well connectivity than models without APERM. Models with the APERM data have provided higher confidence estimates of the future movement of gas injection in the Tengiz platform. Future plans are to investigate a correspondence between APERM and Rock Types as well as statistical transforms with open-hole logs. The log based transforms can then be used in wells or intervals without PLT data, improving accuracy of permeability population into the reservoir model.

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