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Enregistrement W1981760659 · doi:10.2118/2002-007

Compositional Changes During Vapex (Vapour Extraction) Operations in Heavy Oil Pools

2002· article· en· W1981760659 sur OpenAlexaboutno aff
A.K. Singhal, D. Fisher, Hok‐Sum Fung, Jon Goldman

Notice bibliographique

RevueCanadian International Petroleum Conference · 2002
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésExtraction (chemistry)Petroleum engineeringEnvironmental scienceWaste managementPulp and paper industryProcess engineeringChemistryChromatographyEngineering

Résumé

récupéré en direct d'OpenAlex

Abstract During Vapex (Vapour Extraction) operations for heavy oil recovery, a condensable solvent (such as propane or CO2) is injected into the reservoir via a horizontal injector and mobilized oil is drained via a horizontal producer placed directly underneath it. The solvent is chosen such that it is close to its dew point under reservoir conditions. Mixing with this solvent significantly reduces viscosity of the heavy oil. Theoretical treatments assume the oil to be 'black' i.e. no changes to the oil occur, other than viscosity reduction due to localized dissolution of the solvent. However, one observes several compositional changes during Vapex experiments in the laboratory, especially when working with conventional heavy oils such as those from the Lloydminster Area of Canada. Via physical model studies involving different heavy oils, it was seen that compositional changes occur in the oil being produced as well as, in the oil still resident within the model. These include solvent extraction of vaporizable components of the heavy oil, especially in the early stages of Vapex; subsequent produced oil was seen to be progressively heavier. These effects are more than compensated if de-asphalting of the oil occurs, as was observed in many laboratory Vapex experiments. Since the process is dynamic (unsteady state), oil quality and rates change with time. These changes may also affect price one obtains for the oil produced (function of API gravity and sulfur/ metal contents). Regarding deasphalting of the oil produced, it makes a lot of technical and economic sense to focus on ways of improving oil extraction rates down-hole by partially upgrading the oil in-situ and, on improving commodity quality in surface facilities once the heavy oil-solvent mixture has been produced, prior to its shipment to the refinery/ up-grader. Various aspects of compositional changes during Vapex are discussed using data from physical models; glass micro-models and MRI Images obtained during different Vapex experiments. Introduction In Vapex (Vapour Extraction) operations for heavy oil recovery, a condensable solvent (e.g. propane or CO2) is injected into the reservoir via a horizontal injector and mobilized oil is drained via a horizontal producer placed directly underneath it. The solvent is chosen such that it is close to its dew point under reservoir conditions and resulting solvent-oil mixture in vicinity of the vapour chamber, has significantly lower viscosity as compared to the native oil. The main driving mechanism is gravity to help drain the oil thus mobilized1 (having reduced viscosity) as shown in Figure 1. Theoretical treatments of Vapex assume the oil to be 'black', i.e. no changes to oil occur, other than viscosity reduction due to localized dissolution of the solvent. However, one observes several compositional changes occurring in the laboratory during Vapex, especially when working with conventional heavy oils such as those from the Lloydminster area. These include progressive extraction (into the injected solvent) of light hydrocarbon components of oil and asphaltene deposition. Upon contact with the solvent vapour, vaporizable components of oil are extracted into the vapour phase and/or transfer of some of the solvent into the oil phase occurs.

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 candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,699
Score d'incertitude au seuil0,988

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0160,000

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 Opus0,023
Tête enseignante GPT0,248
Écart entre enseignants0,225 · 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.

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

Citations2
Publié2002
Routes d'admission1
Résumé présentoui

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