Cargando…
Modeling interfacial tension of surfactant–hydrocarbon systems using robust tree-based machine learning algorithms
Interfacial tension (IFT) between surfactants and hydrocarbon is one of the important parameters in petroleum engineering to have a successful enhanced oil recovery (EOR) operation. Measuring IFT in the laboratory is time-consuming and costly. Since, the accurate estimation of IFT is of paramount si...
Autores principales: | Rashidi-Khaniabadi, Ali, Rashidi-Khaniabadi, Elham, Amiri-Ramsheh, Behnam, Mohammadi, Mohammad-Reza, Hemmati-Sarapardeh, Abdolhossein |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322925/ https://www.ncbi.nlm.nih.gov/pubmed/37407692 http://dx.doi.org/10.1038/s41598-023-37933-0 |
Ejemplares similares
-
Modeling Viscosity
of CO(2)–N(2) Gaseous Mixtures Using Robust
Tree-Based Techniques: Extra
Tree, Random Forest, GBoost, and LightGBM
por: Zheng, Haimin, et al.
Publicado: (2023) -
On the evaluation of the carbon dioxide solubility in polymers using gene expression programming
por: Amiri-Ramsheh, Behnam, et al.
Publicado: (2023) -
Formulating a novel drilling mud using bio-polymers, nanoparticles, and SDS and investigating its rheological behavior, interfacial tension, and formation damage
por: Taghdimi, Ramin, et al.
Publicado: (2023) -
Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state
por: Mohammadi, Mohammad-Reza, et al.
Publicado: (2022) -
Solubility of gaseous hydrocarbons in ionic liquids using equations of state and machine learning approaches
por: Nakhaei-Kohani, Reza, et al.
Publicado: (2022)