High-Resolution Petrophysics Through the Integration of NMR Logs and Acoustic Image Logs

The estimation of permeability from well logs is a challenging task in formation evaluation. The models usually employed calculate permeability from a function of porosity. The average permeability of an interval will be underestimated when using low-resolution porosity logs, which is particularly critical in heterogeneous formations such as pre-salt carbonates, where the conventional resolution of the logs is insufficient to distinguish matrix porosity from karsts with high permo- porosity. In this context, acoustic imaging can be used to quantify this portion of the porous framework. Our work presents a method for generating high-resolution petrophysical property curves through NMR logs integrated with acoustic image logs. First, we calculate the median of the image amplitudes for each depth and apply a moving average filter to match the resolution with the total porosity from the NMR, achieving good correlation between the curves. Leveraging the relationship between image amplitude and impedance and inspired by the relationship between impedance and porosity, we proposed a polynomial equation relating impedance to porosity, which is adjusted to the data to minimize the least error while honoring the boundary points of 0% and 100% porosity. We applied this equation to the acoustic image, generating a high- resolution total porosity curve. From the relationships between total porosity, effective porosity, and free fluid, we also generated high-resolution permeability curves. Analyzing the high-resolution petrophysical properties generated in a well drilled in pre-salt carbonates, we observed that the detailing of karstified zones provides a flow capacity estimate more consistent with the values observed in injectivity tests. We conclude that our method has the potential to improve the characterization of heterogeneous rocks.