Correlation of methodologies for predicting asphaltene content of low sulfur heavy stock fuel oil from CCR content
Low sulfur heavy stock (LSHS Premium) is a green alternative to Fuel oil. Asphaltene content is a very important quality parameter and is stipulated in LSHS (Premium) specifications. IP 143 is a standard method to conduct the asphaltene analysis; however it is a tedious process which requires around...
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Published in | Petroleum science and technology Vol. 42; no. 11; pp. 1402 - 1412 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Taylor & Francis
02.06.2024
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Low sulfur heavy stock (LSHS Premium) is a green alternative to Fuel oil. Asphaltene content is a very important quality parameter and is stipulated in LSHS (Premium) specifications. IP 143 is a standard method to conduct the asphaltene analysis; however it is a tedious process which requires around 48 h for analysis. In this study, a correlation of two standard methods (IP 143 and JPI-5S-45-95) has been carried out based on the experimentally determined asphaltene contents of LSHS (Premium) samples from different production sources. The correlation coefficient between two standard methods is observed to be near unity, suggesting an excellent correlation. This indicates that JPI-5S-45-95 can be used as a substitute of IP 143 method for asphaltene analysis consuming less time (1 h). A correlation equation has also been established between CCR (ASTM D4530) and asphaltene contents (JPI-5S-45-95) of LSHS (Premium) which indicate the linear dependency of CCR with its asphaltene content. For validation of correlation equation, the calculated asphaltene content was compared with experimentally determined values and it is observed that this correlation equation can be employed to fairly predict the asphaltene content accurately without conducting IP 143 or JPI-5S-45-95 methods. |
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ISSN: | 1091-6466 1532-2459 |
DOI: | 10.1080/10916466.2022.2143811 |