Pushing the Boundaries for Carbonate Productivity Estimations

Abstract

Abstract We propose a reliable methodology for evaluating and estimating productivity of carbonate reservoirs. Our methodology starts with a geological evaluation of image logs focused on locating fractures, quantifying the macro (vuggy) porosity and understanding the depositional and diagenetic environment. Porosity, below the image resolution, is partitioned by analyzing the acoustic and nuclear magnetic resonance (NMR) logs. These data are integrated with petrophysical evaluations by using conventional resistivity analysis conditioned with the fluid, pressure and mobility information gathered from a formation tester. The crucial part of the analysis identifies vugs and their degree of connectivity using acoustic log, formation tester and NMR spectral data, which results in a p-factor. A reliable matrix permeability profile, responding to varying pore connectivity along the hole, is constructed by modifying the conventional NMR permeability with the p-factor. The modified matrix permeability profile is calibrated with the mobility data from the formation tester. Fracture identification and quantification of its permeability are achieved using Stoneley wave and NMR comparisons, and borehole image data. The resultant data set leads to productivity estimations by either handling fracture (if present) or matrix permeability in a dual permeability simulation or via a simple tank model. Timely estimations of carbonate reservoir productivity within weeks of data acquisition result in planning for appraisal or production wells and completion designs before SCAL results become available, early identification of test zones, and/or negating the need for production testing leading to sizable savings.