Carbon capture and storage is key for sustainable economic growth. CO₂-enhanced oil recovery (EOR) methods are efficient practices to reduce emissions while increasing oil production. Although it has been successfully implemented in carbonate reservoirs, its effect on wettability and multiphase flow is still a matter of research. This work investigates the wettability alteration by carbonated water injection (CWI) on a coquina carbonate rock analogue of a Pre-salt reservoir, and its consequences in the flow of oil. The rock was characterized by routine petrophysical analysis and nuclear magnetic resonance. Moreover, micro-computed tomography was used to reconstruct the pore volume, capturing the dominant flow structure. Furthermore, wettability was assessed by contact angle measurement (before and after CWI) at reservoir conditions. Finally, pore-scale simulations were performed using the pore network modelling technique. The results showed that CWI altered the wettability of the carbonate rock from neutral to water-wet. In addition, the simulated relative permeability curves presented a shift in the crossover and imbibition endpoint values, indicating an increased flow capacity of oil after CWI. These results suggest that the wettability alteration mechanism contributes to enhancing the production of oil by CWI in this system.

Hybrid analytical-numerical solutions for transient flow and transient convective heat transfer within microchannels are presented. Analytical solutions for flow transients in microchannels are obtained by making use of the integral transform approach. The proposed model involves the transient fully developed flow equation for laminar regime and incompressible flow with slip at the walls in simple channel geometries. The solution is constructed so as to account for any general functional form of the time variation of the pressure gradient along the duct. Then, the transient-state convection heat transfer is solved for laminar slip flow inside microchannels formed by parallel-plates, making use of the generalized integral transform technique (GITT) and the exact analytical solution of the corresponding eigenvalue problem in terms of confluent hypergeometric functions so as to eliminate the transversal coordinate. The resulting system of transformed partial differential equations in the longitudinal coordinate is numerically solved by the Method of Lines as implemented in the routine NDSolve of the Mathematica system. Mixed symbolic-numerical algorithms are developed under the Mathematica platform.

Summary: Many methods are used to group and classify rocks, most of them designed to be applied to all petrophysical properties, in general. Some authors, however, point out that these generic classifications may not be able to capture the complexity of the relative permeability property, resulting in highly spread relative permeability groups. These authors use correlations between petrophysical data and relative permeability curves to obtain two-phase dynamic rock types through a manual process. The present work describes a general, systematic, and semiautomatic methodology to determine the relative permeability classes (rock types) from relative permeability experimental data, by use of a clustering method associated with an optimization procedure. Clustering methods are able to classify elements according to their similarities in an n-dimensional space of characteristics, but they may not be able to produce clusters with little data scattering of relative permeability, because these clusters must be related to the rock characteristics available in the reservoir model. The method proposed in this investigation uses a clustering method to obtain groups of reservoir-model rock characteristics associated with an optimization method to deform the space of characteristics (clustering space) such that the clusters become representative dynamic classes with minimum spread of relative permeability curves. The results show a significant decrease of the data scattering found among the relative permeability curves within the groups, therefore reducing the uncertainty of the relative permeability used in reservoir simulations. In our methodology, the relative permeability boundaries of each group are also defined, such that every group has its own set of relative permeability curves with some uncertainty for the curve that represents the group. The associated confidence interval of each curve is evaluated with the Student's-t distribution to determine the relative permeability optimistic and pessimistic curves for each group. These boundaries allow optimistic and pessimist scenarios to be drawn.

In this study, highly accurate measurements of density and dynamic viscosities of a recombined live oil and its mixture with additional CO₂were performed. The experiments were carried out under pressure and temperature gradients found in Brazilian Pre-salt reservoirs, that is, in the pressure range from (27.6 to 68.9) MPa and at (333.15 and 353.15) K. The assumption of volume change on mixing is evaluated from the experimental results, and the influence of pressure and temperature on the volume change upon mixing is assessed. The densities of mixtures are calculated considering (i) the excess volume approach, and (ii) no volume change. The densities are better correlated using the excess volume approach with Average Absolute Deviations (AAD) of 0.03%. Thirteen mixing rules of viscosity are examined by comparing the predicted values with the experimental viscosity of the recombined live oil + CO₂mixture. The performance of some rules using compositional fractions (molar, volume and weight) is also evaluated. Thus, a total of 28 different ways to calculate the mixture viscosities were tested in this study. The worst result was obtained with Bingham’s method, leading to 148.6% AAD. The best result was obtained from Lederer’s method with 2% AAD and a maximum deviation of 5.8% using volume fractions and the fitting parameterα. In addition, deviations presented by the predictive methods of Chevron, Double log, and Kendall did not exceed 9% AAD, using weight fractions (Chevron and Double log) and molar fractions (Kendall and Monroe).