Table 5
Summary of the main activities involving artificial intelligence.
| Year | Activity | Authors |
|---|---|---|
| 2018a | Developed a multi-layer feed-forward neural network algorithm to estimate the CO2 adsorption equilibrium in activated carbon | Rostami et al. |
| 2016 | Studied an innovative Least Square Support Vector Machine (LS-SVM) algorithm to create a model capable of predicting the effective thermal conductivity in dry sandstones | Rostami et al. |
| 2017a | Used the Genetic Programming (GP) method to estimate the interfacial tension between hydrocarbon/water in reservoirs | Rostami et al. |
| 2017c | Performed a GP as a mathematical strategy to estimate the thermal conductivity of supercritical CO2 | Rostami et al. |
| 2017b | Studied a GEP method to estimate the solubility of CO2 in processes of CO2 flooding in oil reservoirs | Rostami et al. |
| 2017 | Developed a comparative study on the estimates of interfacial tension between CO2-brine from the GEP, LS-SVM, and DT modeling methods with the ANN | Kamari et al. |
| 2010 | Applied the artificial neural network model to estimate the minimum amount of PVA needed to improve the polymer flooding process. | Rezaian et al. |
| 2016 | Studied artificial neural network models to estimate the viscosity of polymer solutions of three commercial acrylamide-based polymers | Kang et al. |
| 2018b | Used artificial intelligence to estimate the viscosity of PHPA solutions from neural network models. | Rostami et al. |
| 2018 | Developed a MLP neural network model to predict the viscosities of PHPA-based nanopolymer systems and xanthan gum nanosystems | Corredor-Rojas et al. |