Machine learning-based prediction of CO2 fugacity coefficients: Application to estimation of CO2 solubility in aqueous brines as a function of pressure, temperature, and salinity-Reference-Cited by-同舟云学术

Machine learning-based prediction of CO2 fugacity coefficients: Application to estimation of CO2 solubility in aqueous brines as a function of pressure, temperature, and salinity

Published:2023-09 Issue: Volume:128 Page:103971
ISSN:1750-5836
Container-title:International Journal of Greenhouse Gas Control
language:en
Short-container-title:International Journal of Greenhouse Gas Control

Author:

Bhattacherjee Rupom^ORCID,Botchway Kodjo,Pashin Jack C.,Chakraborty Goutam^ORCID,Bikkina Prem

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Industrial and Manufacturing Engineering,General Energy,Pollution

Reference57 articles.

1. Improving the prediction ability of reference correlation for viscosity of carbon dioxide;Abdolbaghi;J. of CO2 Utiliz.,2019

2. Prediction of CO2 diffusivity in brine using white-box machine learning;Amar;J. Pet. Sci. Eng.,2020

3. Modeling viscosity of CO2 at high temperature and pressure conditions;Amar;J. Nat. Gas Sci. Eng.,2020

4. Data-driven modeling of interfacial tension in impure CO2-brine systems with implications for geological carbon storage;Amooie;Int. J. Greenh. Gas Control,2019

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