An Integrated Solution Enabling Allocation of Heavy Oil in the Peregrino Field
Notice bibliographique
Résumé
Abstract An Integrated Solution Enabling Allocation of Heavy Oil in the Peregrino Field Unconventional oil plays a growing role in the petroleum industry, especially in operational regions such as Latin America, China and Canada. The complexity of producing from a heavy oil reservoir is a challenge not limited only by ‘economics’ but also by the available technology. There are various methods of producing from heavy oil reservoirs ranging from open-pit mining to steam assisted production. In areas such as Latin America, cold production is used where electrical submersible pumps (ESPs) are employed to artificially lift the oil from the reservoir. This paper highlights an integrated approach of using ESPs and downhole flowmeters in heavy oil production. It will focus on the validation and analysis of the allocation performance of the downhole flowmeters used in the Peregrino field, Brazil. Peregrino is located offshore of Brazil and the ESPs and flowmeters will be used for the multiple wells in the field. There are huge variations in the well's behavior such as production rates as well as bottomhole pressure. Before field deployment, a test was commissioned to benchmark the performance of the ESPs and flowmeter when working in tandem. Different sizes of flowmeters were tested over the flow range of 500stb/d and 30,000stb/d and up to 360cP in oil viscosity. New correction methods were employed to improve the measurement accuracies such as an iterative calculation of the flowmeter discharge coefficient based on the measured fluid properties. The results from this test will help to validate the performance of the ESP while the flowmeter allocation accuracies can be verified to meet the Brazilian authority (Agencia Nacional de Petroleo - ANP) specification. The lessons learned will be applied towards future field allocation applications using downhole flowmeters in the Peregrino field. Introduction As many reservoirs rapidly mature and production rates decline, there is an urgency to find alternate energy sources to meet the current and future demand for oil. There has been reluctance in the past to produce these unconventional sources of energy due to the high cost and deficient technology to recover them. However, significant advancements in technology in recent times as well as higher oil prices have undoubtedly made the acquisition of these unconventional hydrocarbons a priority. One of the most abundant unconventional resources being aggressively pursued as a result of the world's steadily increasing demand is heavy oil. Heavy oil accounts for double the reserves of conventional oil in the world and has very large concentrations in Canada and Venezuela with an estimated volume of 3.6 trillion barrels of bitumen and extra heavy oil [1]. Heavy oil is unique in that it is liquid petroleum with API gravity less than 22° and typically a viscosity greater than 10 centipoises. It is this uniqueness that presents huge challenges when it comes to recovering, transporting, and refining this resource. It is estimated that roughly 10% percent of the world's daily supply of petroleum is so thick that it can't flow through pipelines on its own. Heavy oil is generally not recoverable in its natural state by conventional production methods. There are many primary and secondary recovery techniques that are non-thermal and rely on the natural temperature of a reservoir. Other techniques require the use of heat or dilution to reduce the viscosity in order for it to flow into a well or through a pipeline. The appropriate recovery method is paramount to the success or failure of a heavy oil project.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».