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Unlike other CCUS technologies, CO2 EOR has been widely implemented at a commercial level and on an industrial scale. In CO2 EOR, CO2 can be injected on its own or alternated with water in CO2 WAG (water-alternating-gas). Both applications have a direct impact on produced fluid compositions influencing GOR, water cut, CO2 concentration and consequently Ca2+, alkalinity and pH. The variation of fluid compositions has an inevitable impact on the scaling potential of produced fluids and on the resulting level of scale formation and its mitigation strategy. The aim of this work is to investigate the scaling potential changes for a wide range of CO2 WAG scenarios in a high salinity carbonate reservoir in the Middle East using input data from reservoir modelling simulations and running multiple sensitivity studies. The main scale formed in this reservoir is calcium carbonate (CaCO3). The equilibrium reservoir water, the produced water chemistry profiles from downhole to stock tank and the scaling risk profiles are modelled using a commercial integrated PVT and aqueous phase software. A rigorous scale prediction procedure previously published by the authors is applied to accurately calculate scale risk trends for variable production scenarios. As CO2 increases in the WAG cycle, reservoir pH drops but the equilibrium with CaCO3 rock causes an increase in alkalinity. This results in more CaCO3 precipitation in the production system where pressure drops and CO2 flashes off solution. Hence, these results show unequivocal detrimental impact of CO2 WAG on the calcium carbonate scaling potential of produced fluids. This leads to a need for operational and/or chemical adjustments to the scale management program when this technology is deployed. Whilst in this field some CaCO3 scale is predicted to form downhole, but this is not a severe problem although it may need to be addressed. The separator is operated at a sufficiently high pressure that calcium carbonate is not expected to form there. Changing operating pressures and CO2 and H2S concentrations can shift some of the problem to the separator, but if this remains at high pressure there will be no scale precipitation here. However, the calcium carbonate scale will predominantly precipitate at stock tank conditions. Implementing green technologies such CCUS is fundamental to achieving net zero goals and this work clearly shows that actions need to be taken to manage the associated CaCO3 scale problems in the produced fluids to make this application successful.
Unlike other CCUS technologies, CO2 EOR has been widely implemented at a commercial level and on an industrial scale. In CO2 EOR, CO2 can be injected on its own or alternated with water in CO2 WAG (water-alternating-gas). Both applications have a direct impact on produced fluid compositions influencing GOR, water cut, CO2 concentration and consequently Ca2+, alkalinity and pH. The variation of fluid compositions has an inevitable impact on the scaling potential of produced fluids and on the resulting level of scale formation and its mitigation strategy. The aim of this work is to investigate the scaling potential changes for a wide range of CO2 WAG scenarios in a high salinity carbonate reservoir in the Middle East using input data from reservoir modelling simulations and running multiple sensitivity studies. The main scale formed in this reservoir is calcium carbonate (CaCO3). The equilibrium reservoir water, the produced water chemistry profiles from downhole to stock tank and the scaling risk profiles are modelled using a commercial integrated PVT and aqueous phase software. A rigorous scale prediction procedure previously published by the authors is applied to accurately calculate scale risk trends for variable production scenarios. As CO2 increases in the WAG cycle, reservoir pH drops but the equilibrium with CaCO3 rock causes an increase in alkalinity. This results in more CaCO3 precipitation in the production system where pressure drops and CO2 flashes off solution. Hence, these results show unequivocal detrimental impact of CO2 WAG on the calcium carbonate scaling potential of produced fluids. This leads to a need for operational and/or chemical adjustments to the scale management program when this technology is deployed. Whilst in this field some CaCO3 scale is predicted to form downhole, but this is not a severe problem although it may need to be addressed. The separator is operated at a sufficiently high pressure that calcium carbonate is not expected to form there. Changing operating pressures and CO2 and H2S concentrations can shift some of the problem to the separator, but if this remains at high pressure there will be no scale precipitation here. However, the calcium carbonate scale will predominantly precipitate at stock tank conditions. Implementing green technologies such CCUS is fundamental to achieving net zero goals and this work clearly shows that actions need to be taken to manage the associated CaCO3 scale problems in the produced fluids to make this application successful.
Anthropogenic CO2 emissions have accumulated significantly in the last few decades aggravating global warming. Mineral trapping is a key mechanism for the global energy transition during which injected CO2 is sequestered within the subsurface formations via dissolution/precipitation. However, the data of CO2 mineralization are extremely scarce, which limits our understanding of suitable candidate formations for mineral trapping. The aim of this study is to emphasize the impacts of wettability and rock heterogeneity on mineral trapping occurring during CO2 sequestration in carbonate formations. In this study, a numerical approach was followed by setting up one-spot pilot test-scale models of homogeneous and heterogeneous carbonate formations to predict the mineral trapping capacity of CO2 gas for two distinct wetting states: Strongly Water-Wet (SWW) and Intermediately Water-Wet (IWW). Accordingly, a 3D Cartesian base case model was created with upscaled petrophysical parameters to mimic the subsurface conditions of a representative carbonate formation from UAE. The study highlighted the relationship between carbonate wettability, rock heterogeneity, and fate of CO2 plume and mineralization potential. In this study, the effect of wettability and heterogeneity were analyzed in terms of CO2 mineralized after 1 year of injection and 200 years of storage. The mineral trapping capacities computed showed a monotonic increase as the wettability shifted from SWW to IWW irrespective of reservoir heterogeneity with different extents. Notably, after 115 years of storage, the heterogeneous formations started to sequester more CO2 attributed to permeability variance increase. In the same context, plume of CO2 extended upwardly and laterally further in case of intermediately water-wet compared to strongly water-wet, especially at earlier stages of storage duration. Classical trapping mechanisms such as solubility trapping gained more attention than mineralization. This is attributed to the time-dependency of mineralization with slow reaction rate scaling up to millennia. Thus, CO2 mineralization potential assessment is important to de-risk large-scale pilot tests. This work provides new insights into underpinning the effects of wettability and rock heterogeneity on CO2 storage capacity in carbonate formations. The findings suggest that mineralization within carbonate immobilizes CO2 and thus, assists in stable and long-term storage.
Phase equilibrium calculations require experimental lab data to constrain component properties in an equation of state (EOS) model. These thermodynamics-based models generally perform well when it comes to predicting conventional PVT experiments but often fall short when it comes to predicting gas injection experiments, particularly for CO2 injection. We therefore seek to develop methods that can help provide a good initial estimate of the swelling curve, in cases where laboratory data are not available. Our company PVT database compromises more than 2,200 PVT studies, which enables us to pursue three different avenues for predicting the CO2 swelling curve. The first method relies on a machine-learning algorithm, which takes fluid composition and temperature as input. In general, we find that this solution does not preserve monotonicity of the pressure-dependent properties and it extrapolates poorly outside the parameter space used for training. As an example, it fails to predict the first-contact miscible pressure defined as the maximum pressure on the swelling curve. The second option involved correlating swelling pressure, swelling factor and swelling density as a function of the amount of injected gas. We find that all three curves are well-represented by a parabolic expression and we were able to correlate the coefficients as a function methane content in the reservoir fluid only. The resulting model predicts saturation pressure, swelling factor, and density of the swollen mixtures with an absolute average deviation of 4.8%, 2.3% and 1.7%, respectively, which is an excellent starting point for tuning an EOS model for EOR screening studies until experimental data becomes available. The third strategy involved tuning a separate EOS model to each of the 34 CO2 swelling studies and then attempt to correlate the EOS component properties. We compare the values of the tuned pseudo-component properties against some standard correlations such as Pedersen, Kesler-Lee, Riazi-Daubert and others. We find that the Pedersen correlations for critical pressure, critical temperature and acentric factor provide a more accurate initial guess than the other correlations tested. However, we observed that the tuned solution depended to some extent on the initial guess. We find that for our fluid systems, the default values for the critical volume of the pseudo-components need to be reduced by 15% to better predict the viscosity using the LBC model. Despite the slightly improved property estimation, we did not manage to find a clear trend for the binary interaction coefficient between CO2 and the plus fraction. Therefore, we would recommend predicting the CO2 swelling curve with the set of parabolic correlations.
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