MétaCan
Menu
Retour à la cohorte
Enregistrement W1993911385 · doi:10.2118/2009-152

Non-isothermal Kinetics of the Pyrolysis of the Whole Oil and its Asphaltene Derived from Fosterton Oil

2009· article· en· W1993911385 sur OpenAlexafffund
Nader Mahinpey, Thilakavathi Mani

Notice bibliographique

RevueCanadian International Petroleum Conference · 2009
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensUniversity of CalgaryUniversity of Regina
Organismes subventionnairesPetroleum Technology Research Centre
Mots-clésAsphaltenePyrolysisKineticsIsothermal processPetroleum engineeringChemical engineeringMaterials sciencePyrolysis oilThermodynamicsChemistryOrganic chemistryGeologyEngineeringPhysics

Résumé

récupéré en direct d'OpenAlex

Abstract Coke formation from heavy oil has been extensively studied and various kinetic models have been proposed in the literature. In this study, thermal behavior of crude oil and its asphaltene obtained from Fosterton field was investigated using thermogravimetric analysis. Non-isothermal pyrolysis experiments of whole oil and its asphaltene was performed in nitrogen atmosphere at different heating rates of 5, 10, 15 and 20 ?C/min. Although, much difference was not observed in the weight loss profile for whole oil and its asphaltene, the final amount of coke formed changes with the heating rate. Nonisothermal experiments were better described by Distributed Activation Energy Model (DAEM) compared to other applicable models. The non-isothermal pyrolysis kinetics of whole oil and its asphaltene were studied with DAEM equation. The activation energy for whole oil pyrolysis spreads over a range from 7 to 129 kJ/mol and the pre-exponential factor varies from 102 to 10 11 min−1. The asphaltene fraction separated from the oil has the activation energy from 50 to 183 kJ/mol and the pre-exponential factor ranges from 10 7 to 1014 min-1. Results from the kinetic analysis suggest that asphaltene requires more activation energy compared to the whole oil. Introduction Thermal cracking of heavy oil feedstocks results in the formation of a wide range of gaseous, liquid and solid products. During pyrolysis, several reactions take place, which influence the overall kinetics and the resulting coke formation. It is well known that thermal treatment of hydrocarbons follows a free radical mechanism, where cracking reactions take place in the initiation step, condensation and polymerization reactions comprise the final step [1]. The final step reactions explain the formation of products such as coke. Among the SARA fraction present in the whole oil, asphaltenes are precursors of coke formation. Asphaltenes are complex associated species typically isolated as a solubility class obtained by precipitation with a weak solvent [2]. Coke formations from both whole oil and its fractions like asphaltene have been extensively studied [3, 4]. However, the coke formation characteristics vary with the different sources of oil. The kinetics of the thermal decomposition of various oil from different regions of the world, have been investigated and various suggestions as to the decomposition mechanism have been reported [5, 6]. Many thermogravimetric studies have been carried out under isothermal conditions, but this method involves some inaccuracies. It is more accurate to use a nonisothermal method to determine the kinetic parameters of the pyrolysis process, employing a TGA apparatus, with the sample heated at a constant rate and recording its weight change. This is mainly because of the shorter experimental time and the fewer encountered difficulties. But the principal reason for their popularity in the field of oil pyrolysis is that it more closely simulates the conditions expected in commercial scale. Thus, such a technique for determining the reaction kinetics, such as activation energy, has been preferred by many researchers [7–9]. Hence, the kinetics of thermal degradation of whole oil and its asphaltene from fosterton region can be obtained using a TGA apparatus.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,105
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,217
Écart entre enseignants0,205 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2009
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueCanadian International Petroleum ConferenceMême sujetPetroleum Processing and AnalysisTravaux en français237 207