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The high CO2 content of Brazil’s pre-salt fields, which may reach values from 20% to 44% molar, presents both a challenge as well as an opportunity. CO2 stripped from the produced gas cannot be released into the atmosphere due to environmental restrictions. Therefore, the whole amount of CO2 produced should be continuously reinjected into the reservoir. This work investigates the effect of CO2 content on the low salinity water alternating CO2 injection technique (CO2LSWAG) using a commercial compositional reservoir simulator. In these field-scale simulations, CO2 is stripped from the produced gas and reinjected into the reservoir. Primary oil recovery methods such as CO2 flooding and LSW flooding are also simulated. Chemical reactions between CO2 and the minerals present in the reservoir are modeled. Wettability change is assumed to be the main mechanism for improved oil recovery due to low salinity water injection. Compositional simulations of CO2 injection usually assume a constant injected gas rate. In this case, CO2 is supposed to come from an external source. In many petroleum reservoirs this assumption is true. Three factors are assessed in the present work. The first one is the natural reservoir pressure, which is the main driving force in primary production. The second factor is the amount of CO2 available for injection. The third one is the wettability change promoted by the reaction involving CO2. It is shown that in primary production, higher CO2 content leads to quicker depletion of the natural energy of the reservoir, leading to lower oil recovery. Nevertheless, higher CO2 content also means that more gas is available for reinjection, potentially leading to increased oil production. Finally, as CO2 reacts with minerals it promotes a change in wettability from an oil-wet to a water-wet state. It is shown that the CO2 content is an important variable to be assessed in a high CO2 content reservoir. Optimal injection practices must take these three aspects into consideration.

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From the liquid−liquid equilibrium (LLE) data of a linear polymer, an investigation of the Sanchez and Lacombe equation of state (SL-EOS) is performed with the goal of describing the swelling of three hydrogels: poly(N-isopropylacrylamide), PNIPA; poly(N-vinyl caprolactam), PVCL; and poly(N-diethylacrylamide), PNDEA. The phantom theory is applied to describe the elastic contribution of the network structure. Using SL-EOS with its binary interaction parameter as a linear temperature function is sufficient to describe the lower critical solution temperature (LCST) of non-crosslinked polymers. The results demonstrate that this function is also suitable for modeling the swelling/shrinking and the transition temperature of the corresponding hydrogel. We demonstrate that a simple mechanical model and a simple EOS are sufficient to adequately describe nonelectrolyte hydrogel swelling using LLE data and only one piece of swelling data. In addition, the pressure effects on the hydrogel swelling are analyzed without the need for new parameter estimation, an analysis scarcely found in the literature.

Summary Uncertainties regarding the factors that influence asphaltene deposition in porous media (e.g., those resulting from oil composition, rock properties, and rock/fluid interaction) strongly affect the prediction of important variables, such as oil production. Besides, some aspects of these predictions are stochastic processes, such as the aggregation phenomenon of asphaltene precipitates. For this reason, a well-defined output from an asphaltene-deposition model might not be feasible. Instead of this, obtaining the probability distribution of important outputs (e.g., permeability reduction and oil production) should be the objective of rigorous modeling of this phenomenon. This probability distribution would support the design of a risk-based policy for the prevention and mitigation of asphaltene deposition. In this paper we aim to present a new approach to assessing the risk of formation damage caused by asphaltene deposition using Monte Carlo simulations. Using this approach, the probability-distribution function of the permeability reduction was obtained. To connect this information to a parameter more related to economic concepts, the probability distribution of the damage ratio (DR) was also calculated, which is the fraction of production loss caused by formation damage. A hypothetical scenario involving a decision in the asphaltene-prevention policy is presented as an application of the method. A novel approach to model the prevention of asphaltene aggregation using inhibitors has been proposed and successfully applied in this scenario.