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First, a major challenge of parametric methods, like the logistic model, is the robustness and reliability of the modeling.
We demonstrate how to ensure the efficiency and reliability of the modeling by bounding the magnitude of the stress redistribution along the interface during the effective cycle.
Hence, an accurate magnitude of the CO2 oil swelling factor increases the precision and reliability of the modeling and simulation studies, which are conducted to capture the main recovery mechanisms and to determine the production performance of CO2 EOR strategies for both heavy oil and conventional oil reserves.
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Comparison between numerical and experimental results show the reliability of the modelling.
Furthermore, the variability among the models was used to evaluate the reliability of the modelling.
A comparative analysis between the modelled predictions and experimental results was performed to verify the reliability of the model.
That ran counter to the forecasts of computer climate models, and global warming skeptics have pointed to Antarctica in questioning the reliability of the models.
Reliability of the model is verified by the experiments.
Reliability of the model is verified by bench-scale experiments.
The results validate the reliability of the model.
Sensitivity analysis confirms the reliability of the model.
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