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New insights into permeability determination by coupling Stoneley wave propagation and conventional petrophysical logs in carbonate oil reservoirs.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-15869-1
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Modelling rate of penetration in drilling operations using RBF, MLP, LSSVM, and DT models.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-14710-z
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- Article
An advanced computational intelligent framework to predict shear sonic velocity with application to mechanical rock classification.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-08864-z
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- Article
Modeling solubility of CO<sub>2</sub>–N<sub>2</sub> gas mixtures in aqueous electrolyte systems using artificial intelligence techniques and equations of state.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-07393-z
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Modeling of CO<sub>2</sub> adsorption capacity by porous metal organic frameworks using advanced decision tree-based models.
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-04168-w
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Modeling of nitrogen solubility in normal alkanes using machine learning methods compared with cubic and PC-SAFT equations of state.
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-03643-8
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Modeling hydrogen solubility in hydrocarbons using extreme gradient boosting and equations of state.
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-97131-8
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White-box machine-learning models for accurate interfacial tension prediction in hydrogen–brine mixtures.
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- Clean Energy, 2024, v. 8, n. 5, p. 252, doi. 10.1093/ce/zkae067
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- Article
Compositional modeling of gas-condensate viscosity using ensemble approach.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-36122-3
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Modeling of H<sub>2</sub>S solubility in ionic liquids: comparison of white-box machine learning, deep learning and ensemble learning approaches.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-34193-w
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Optimization of reaction temperature and Ni–W–Mo catalyst soaking time in oil upgrading: application to kinetic modeling of in-situ upgrading.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-31314-3
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Experimental measurement and modeling of asphaltene adsorption onto iron oxide and lime nanoparticles in the presence and absence of water.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-022-27335-z
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- Article
Evaluation of corrosion performance of superhydrophobic PTFE and nanosilica coatings.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-20729-z
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- Article
Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-18983-2
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- Article
Solubility of gaseous hydrocarbons in ionic liquids using equations of state and machine learning approaches.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-17983-6
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- Article
Modeling of Brine/CO 2 /Mineral Wettability Using Gene Expression Programming (GEP): Application to Carbon Geo-Sequestration.
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- Minerals (2075-163X), 2022, v. 12, n. 6, p. 760, doi. 10.3390/min12060760
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- Article
Modeling Interfacial Tension of N 2 /CO 2 Mixture + n-Alkanes with Machine Learning Methods: Application to EOR in Conventional and Unconventional Reservoirs by Flue Gas Injection.
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- Minerals (2075-163X), 2022, v. 12, n. 2, p. N.PAG, doi. 10.3390/min12020252
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On the evaluating membrane flux of forward osmosis systems: Data assessment and advanced intelligent modeling.
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- Water Environment Research (10614303), 2024, v. 96, n. 1, p. 1, doi. 10.1002/wer.10960
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- Article
Modelling asphaltene precipitation titration data: A committee of machines and a group method of data handling.
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- Canadian Journal of Chemical Engineering, 2019, v. 97, n. 2, p. 431, doi. 10.1002/cjce.23254
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On the evaluation of Alkaline-Surfactant-Polymer flooding in a field scale: Screening, modelling, and optimization.
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- Canadian Journal of Chemical Engineering, 2017, v. 95, n. 8, p. 1615, doi. 10.1002/cjce.22834
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- Article
Accurate determination of the CO<sub>2</sub>-crude oil minimum miscibility pressure of pure and impure CO<sub>2</sub> streams: A robust modelling approach.
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- Canadian Journal of Chemical Engineering, 2016, v. 94, n. 2, p. 253, doi. 10.1002/cjce.22387
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- Article
On the Evaluation of Interfacial Tension (IFT) of CO 2 –Paraffin System for Enhanced Oil Recovery Process: Comparison of Empirical Correlations, Soft Computing Approaches, and Parachor Model.
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- Energies (19961073), 2021, v. 14, n. 11, p. 3045, doi. 10.3390/en14113045
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Experimental study and modelling of asphaltene deposition on metal surfaces with superhydrophobic and low sliding angle inner coatings.
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-95657-5
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- Article
Introducing a Novel Approach for Oil‐Oil Correlation based on Asphaltene Structure: X‐ray Diffraction.
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- Acta Geologica Sinica (English Edition), 2021, v. 95, n. 6, p. 2100, doi. 10.1111/1755-6724.14709
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- Article
Viscosity of Ionic Liquids: Application of the Eyring's Theory and a Committee Machine Intelligent System.
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- Molecules, 2021, v. 26, n. 1, p. 156, doi. 10.3390/molecules26010156
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Toward empirical correlations for estimating the specific heat capacity of nanofluids utilizing GRG, GP, GEP, and GMDH.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-47327-x
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- Article
Estimation of the flow rate of pyrolysis gasoline, ethylene, and propylene in an industrial olefin plant using machine learning approaches.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-41273-4
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- Article
On the evaluation of the carbon dioxide solubility in polymers using gene expression programming.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-39343-8
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- Article
Formulating a novel drilling mud using bio-polymers, nanoparticles, and SDS and investigating its rheological behavior, interfacial tension, and formation damage.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-39257-5
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- Article
Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-39079-5
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- Article
Modeling interfacial tension of surfactant–hydrocarbon systems using robust tree-based machine learning algorithms.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-37933-0
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- Article
Comparative Analysis of Machine Learning Models for Nanofluids Viscosity Assessment.
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- Nanomaterials (2079-4991), 2020, v. 10, n. 9, p. 1767, doi. 10.3390/nano10091767
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- Article
Insights into the Effects of Pore Size Distribution on the Flowing Behavior of Carbonate Rocks: Linking a Nano-Based Enhanced Oil Recovery Method to Rock Typing.
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- Nanomaterials (2079-4991), 2020, v. 10, n. 5, p. 972, doi. 10.3390/nano10050972
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- Article
Artificial Intelligence Based Methods for Asphaltenes Adsorption by Nanocomposites: Application of Group Method of Data Handling, Least Squares Support Vector Machine, and Artificial Neural Networks.
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- Nanomaterials (2079-4991), 2020, v. 10, n. 5, p. 890, doi. 10.3390/nano10050890
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Modeling the permeability of heterogeneous oil reservoirs using a robust method.
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- Geosciences Journal, 2016, v. 20, n. 2, p. 259, doi. 10.1007/s12303-015-0033-2
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