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Enregistrement W2078513050 · doi:10.4043/16682-ms

Unlocking Deepwater Heavy Oil Reserves - A Flow Assurance Perspective

2004· article· en· W2078513050 sur OpenAlex

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Notice bibliographique

RevueOffshore Technology Conference · 2004
Typearticle
Langueen
DomaineEngineering
ThématiqueOil and Gas Production Techniques
Établissements canadiensnon disponible
Organismes subventionnairesShell Global Solutions International
Mots-clésFlow assuranceOil reservesSubseaEnvironmental sciencePetroleum engineeringProduction (economics)Petroleum industryLead (geology)Submarine pipelinePetroleumRisk analysis (engineering)BusinessEngineeringGeologyEnvironmental engineeringMarine engineeringChemistryOceanography

Résumé

récupéré en direct d'OpenAlex

Abstract As the industry's deepwater developments continue to mature, newer discoveries in the ultra deepwater demonstrate a trend towards more difficult and heavier hydrocarbons that are far removed from existing infrastructure. Since heavy oils represent a significant reserve-base, there is a strong economic incentive within the industry to develop technologies to profitably produce these hydrocarbon reserves. Heavy oils are often characterized by their high viscosity, low API gravity and low reservoir energy. Heavy oils are also prone to the formation of emulsions. The combination of these factors makes the production and transportation of heavy oils a major challenge from a flow assurance perspective. Development of a robust flow assurance strategy will play a central role in the system selection, detailed design, and operation of deepwater heavy oil fields. In this paper, we identify some of the most significant flow assurance challenges associated with heavy oil production and discuss technology developments needed to overcome them. In particular, we have focused our attention on viscosity management techniques and emulsion formation tendencies of heavy oils and also assessed the risk posed by solids such as hydrates, wax and asphaltenes. We also present a brief analysis of the operability aspects for producing deepwater heavy oils, describe major differences from conventional lighter oils, and evaluate its impact on the topsides infrastructure and subsea system selection and design. Introduction Heavy oils have been successfully produced for several decades from various locations around the world. A majority of this heavy oil production has come from either onshore or shallow water fields in Venezuela, Mexico, Canada, Oman and California. The profitability of production from heavy oils is directly correlated to the price of oil. In high price environments, producing these heavy oil fields can be relatively profitable, but in low price environments they can be marginal or non-economic. The high cost of producing heavy oils is attributed to its intrinsic qualities that are characterized by a low API gravity (usually less than 20), high viscosity, low pour point, high acid number, strong emulsion tendency and low reservoir energy. Each one of the above factors leads to a high cost of producing each barrel of heavy oil and it commands a relatively lower price compared to conventional light oil. The challenge of producing heavy oil reserves in deepwater is further exacerbated by the discovery of reserves in remote locations that are cut-off from production facilities and infrastructure. The recovery, lift, transportation, processing and eventual upgrading for sulfur, metal and acid removal, poses some unique challenges for economically producing deepwater heavy oil reservoirs as recently summarized1,2,3 by some of the major industry players active in developing these resources. While the deepwater environment represents much more complex technical and economic challenges for producing heavy oils, some of the basic issues pertaining to heavy oil are essentially the same regardless of its origin. Consequently, as the industry begins to develop technical solutions for unlocking heavy oils, it would be prudent to first tap into the vast body of experience and knowledge that has already been gained in producing onshore and shallow water heavy oil fields.

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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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,753
Score d'incertitude au seuil0,939

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 ouverte0,0000,000
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 GPT0,232
Écart entre enseignants0,220 · 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