Estimativa de permeabilidade de rochas carbonáticas a partir de parâmetros do espaço poroso.

Abstract

Computational petrophysics is a technique that has been increasingly used in the petroleum industry to characterize reservoirs and to simulate computationally its physical behavior. Through this technique it is possible to characterize a big number of samples, under different environmental conditions, in a relatively short time. This work proposes a model of permeability estimation that uses petrophysical parameters taken from x - ray microtomography images (µCT) and compare them with petrophysical parameters measured in the laboratory. It was analyzed a set of 19 samples with different depositional, diagenetic and textural characteristics, belonging to the Araripe, Potiguar and Sergipe - Alagoas basins. Of these, 14 are limestones, 2 of tufa limestone, 2 of caliche and 1 of dolomite. In the laboratory a gas permoporosimeter was used to measure the porosity and permeability parameters. µCT samples were obtained with a resolution of about 2.0 μm. The set of images created was treated in Avizo Fire software and the porosity, permeability, connectivity and pore diameter parameters were extracted. A statistical model was established to predict permeability from pore space parameters extracted from µCT images. The results indicate that the connectivity of micropores, inferred from the calculation of the Euler Number in 3D images, is the parameter that exerts the greatest influence in the estimation of permeability, followed by the porosity of the macropores and the connectivity of the macropores. The proposed predictive model presented a coefficient of determination of 0.994, being very reliable for the group of samples investigated.