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Enregistrement W2064644354 · doi:10.2118/2002-082

Hydrocarbon Liquid Phase Definition, Determination and Allocation in Two-Phase Hydrocarbon Reservoirs

2002· article· en· W2064644354 sur OpenAlexaboutno aff
A. N. Hamoodi, Salar Babajan, A. H. Desouki, V. Ruffier-Meray, A. Pina

Notice bibliographique

RevueCanadian International Petroleum Conference · 2002
Typearticle
Langueen
DomaineEngineering
ThématiqueHydrocarbon exploration and reservoir analysis
Établissements canadiensnon disponible
Organismes subventionnairesAbu Dhabi National Oil Company
Mots-clésHydrocarbonPhase (matter)Liquid phasePetroleum engineeringHydrocarbon mixturesComputer scienceGeologyChemistryThermodynamicsPhysicsOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Identification of the produced hydrocarbon liquid stream, as either oil or condensate, in two-phase hydrocarbon reservoirs, gains special significance in cases where the gas cap and its associated condensate owners are different from the oil rim owners. Thus, the definition of the produced hydrocarbon liquid stream is critical in determining the allocation of the produced liquid phase and accounting for the volumes of oil and condensate produced to satisfy marketing constraints. In this paper we will discuss classification procedures of the produced hydrocarbon liquid stream, laboratory sampling and analysis, and compositional modeling demonstrated for a saturated oil reservoir with a large gas cap and a critical fluid reservoir. Introduction The definition of the hydrocarbon liquid stream and the characteristics of oil or condensate received significant focus in the petroleum literature. Appropriate sampling and conventional analysis of oil and condensate was discussed as early as 1941 by Flaitz et. al.1 and later in 1954 by Reudelhuber2,3,4. Eilerts et. al.5 in 1957 reported observed characteristics of a number of condensate fluids highlighting the wide range in physical properties and deriving "rule of thumb" to classify condensates based on gas-oil-ratio (GOR) and API gravity. In 1986 Moses et. al.6 discussed the characteristics of oil, near critical fluid and condensate, his work received significant discussion that advanced the understanding of the defining characteristics of the hydrocarbon fluid systems. A more detailed classification was presented by McCain et. al.7,8,9,10,11,12. McCain's classification identified color, API gravity and gas-liquid ratio (GLR) as defining characteristics of the produced hydrocarbon stream. Legal definitions and classifications were also adopted by various governmental agencies and are applied as references. Specifically, the Alberta Mines and Minerals Act 13,14 and the 1988 OPEC classification15. The significance of establishing an agreed criteria and procedure to classify and allocate oil and condensate production is realized in mixed ownership, where the owners of the oil and condensate are different. For mixed production situations, that will inevitably evolve during the development cycle of two-phase hydrocarbon reservoirs, present a challenge in determining the accurate allocation ratio of oil and condensate. We will demonstrate that appropriate periodic sampling and analysis of mixed producing wells provide the technical basis of validating compositional modeling techniques capable of component tracking permitting differentiation of liquid streams originating from the gas-cap or oil column. The procedure was applied to a saturated oil reservoir and a critical fluid reservoir and the results and specific technical challenges will be discussed. CLASSIFICATION PROCEDURES OF THE PRODUCED HYDROCARBON LIQUID Definition of produced hydrocarbon liquid stream as "condensate" based on surface determined properties was presented by Eilerts et. al.5 in 1957, observing that condensates range from very rich with a condensate-gas ratio (CGR) of 500 Stb/MMScf to very lean 10 Stb/MMScf with API gravities reported as low as 30 ° API to as high as 80 ° API. Based on the data reviewed, Eilerts et. al.5 observed that the API gravity of 85% of the samples reviewed ranges between 45 - 65 ° API, and quoted a rule of thumb for a gas condensate system to exist when the GLR exceeds 5000 Scf/Stb and the liquid is lighter than 50 ° API.

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 candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,265
Score d'incertitude au seuil1,000

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)0,0010,000

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 Opus0,028
Tête enseignante GPT0,263
Écart entre enseignants0,235 · 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'étudeSimulation ou modélisation
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
Publié2002
Routes d'admission1
Résumé présentoui

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