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Adsorption Properties of a Modified Adsorbent in Petroleum Analysis by Geochemical and Chemometric Methods.

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Title: Adsorption Properties of a Modified Adsorbent in Petroleum Analysis by Geochemical and Chemometric Methods.
Authors: Badikova, A. D.1 (AUTHOR) fohtf@mail.ru, Masagutov, R. Kh.1,2 (AUTHOR), Beigul, N. A.1,3 (AUTHOR), Sakhibgareev, S. R.1 (AUTHOR), Kulyashova, I. N.1 (AUTHOR), Grigor'eva, S. S.1 (AUTHOR)
Source: Chemistry & Technology of Fuels & Oils. May2025, Vol. 61 Issue 2, p351-356. 6p.
Subjects: Cyclic compounds, Geochemical surveys, Distribution (Probability theory), Hydrocarbons, Natural gas
Abstract: In order to predict the prospects of licensed subsurface areas for oil and natural gas, a sorber module with thermally‑graphitized carbon black modified with fullerene C60 has been proposed for use in geochemical surveying. GC/MS was used to identify the hydrocarbon compounds extracted using this sorbent by passive adsorption, including references, characteristic of the oil deposits of the Pashyan horizon. The presence of C5‑C19 alkanes, arenes, cyclic compounds, aldehydes, and alcohols as well as by‑products and other compounds in the extracted mixture was demonstrated. The chemometric method was used for treating the chromatographic data in order to construct a map of the surface of the probability distribution of the model on a fragment of one of the licensed sites, indicating the areas reflecting the presence or absence of hydrocarbons in productive formations. [ABSTRACT FROM AUTHOR]
Copyright of Chemistry & Technology of Fuels & Oils is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Adsorption Properties of a Modified Adsorbent in Petroleum Analysis by Geochemical and Chemometric Methods.
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  Data: <searchLink fieldCode="JN" term="%22Chemistry+%26+Technology+of+Fuels+%26+Oils%22">Chemistry & Technology of Fuels & Oils</searchLink>. May2025, Vol. 61 Issue 2, p351-356. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Cyclic+compounds%22">Cyclic compounds</searchLink><br /><searchLink fieldCode="DE" term="%22Geochemical+surveys%22">Geochemical surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrocarbons%22">Hydrocarbons</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+gas%22">Natural gas</searchLink>
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  Data: In order to predict the prospects of licensed subsurface areas for oil and natural gas, a sorber module with thermally‑graphitized carbon black modified with fullerene C60 has been proposed for use in geochemical surveying. GC/MS was used to identify the hydrocarbon compounds extracted using this sorbent by passive adsorption, including references, characteristic of the oil deposits of the Pashyan horizon. The presence of C5‑C19 alkanes, arenes, cyclic compounds, aldehydes, and alcohols as well as by‑products and other compounds in the extracted mixture was demonstrated. The chemometric method was used for treating the chromatographic data in order to construct a map of the surface of the probability distribution of the model on a fragment of one of the licensed sites, indicating the areas reflecting the presence or absence of hydrocarbons in productive formations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Chemistry & Technology of Fuels & Oils is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10553-025-01874-3
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        Text: English
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      – SubjectFull: Cyclic compounds
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              Text: May2025
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