Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling

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Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling. / Kooti, Ghazal; Taherdangkoo, Reza; Chen, Chaofan et al.
In: Acta Geochimica, Vol. 43, No. 5, 10.2024, p. 971-984.

Research output: Contribution to journal › Article › Research › peer-review

Harvard

Kooti, G, Taherdangkoo, R, Chen, C, Sergeev, N, Doulati Ardejani, F, Meng, T & Butscher, C 2024, 'Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling', Acta Geochimica, vol. 43, no. 5, pp. 971-984. https://doi.org/10.1007/s11631-024-00680-8

APA

Kooti, G., Taherdangkoo, R., Chen, C., Sergeev, N., Doulati Ardejani, F., Meng, T., & Butscher, C. (2024). Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling. Acta Geochimica, 43(5), 971-984. https://doi.org/10.1007/s11631-024-00680-8

Vancouver

Kooti G, Taherdangkoo R, Chen C, Sergeev N, Doulati Ardejani F, Meng T et al. Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling. Acta Geochimica. 2024 Oct;43(5):971-984. doi: 10.1007/s11631-024-00680-8

Author

Kooti, Ghazal ; Taherdangkoo, Reza ; Chen, Chaofan et al. / Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions : Implications for stray gas migration modeling. In: Acta Geochimica. 2024 ; Vol. 43, No. 5. pp. 971-984.

Bibtex - Download

@article{bc40594884be4f7699621fc50c1348c3,
title = "Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling",
keywords = "Boosted regression tree, Gas solubility, Groundwater contamination, Hydraulic fracturing, Regression tree, Thermodynamic models",
author = "Ghazal Kooti and Reza Taherdangkoo and Chaofan Chen and Nikita Sergeev and {Doulati Ardejani}, Faramarz and Tao Meng and Christoph Butscher",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",
year = "2024",
month = oct,
doi = "10.1007/s11631-024-00680-8",
language = "English",
volume = "43",
pages = "971--984",
number = "5",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions

T2 - Implications for stray gas migration modeling

AU - Kooti, Ghazal

AU - Taherdangkoo, Reza

AU - Chen, Chaofan

AU - Sergeev, Nikita

AU - Doulati Ardejani, Faramarz

AU - Meng, Tao

AU - Butscher, Christoph

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024/10

Y1 - 2024/10

KW - Boosted regression tree

KW - Gas solubility

KW - Groundwater contamination

KW - Hydraulic fracturing

KW - Regression tree

KW - Thermodynamic models

UR - http://www.scopus.com/inward/record.url?scp=85188311947&partnerID=8YFLogxK

U2 - 10.1007/s11631-024-00680-8

DO - 10.1007/s11631-024-00680-8

M3 - Article

AN - SCOPUS:85188311947

VL - 43

SP - 971

EP - 984

JO - Acta Geochimica

JF - Acta Geochimica

SN - 2096-0956

IS - 5

ER -

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