Well Performance Analysis for Heavy Oil With Water Coning
Notice bibliographique
Résumé
Abstract As conventional petroleum is approaching its maximum production and the world oil demand continues to grow, heavy oil becomes one of the obvious replacement resources. By 2015, its contributions to total oil production would reportedly grow from the present 2.5 MMbpd to 4MMbpd and stay at this level for a couple of decades. Recovery of heavy oil reservoir with wells is a challenge due to low API gravities (6 °-25 °), high viscosity (100cp-1000cp)-particularly in the presence of water. For example, the recovery factor from a heavy oil reservoir with bottom water in the H.K. oilfield, Shandong province, in China, having viscosity of 710 cp does not exceed one percent. One of the most important problems in heavy oil recovery is dramatic loss of wells' productivity at the onset of water inflow due to the two fluids' mobility contrast. Not only the recovery at breakthrough time is very low, but also the water cut increase is extremely rapid. The presented simulation study investigates dynamics of productivity loss in wells producing heavy oil with bottom water. The production system (nodal) analysis model simulates inflow performance relationship with variable water cut. The model captures the difference between heavy and light oil in terms of mobility ratio effect, recovery dynamics prior to and after water breakthrough, and water cut control with production rate. The results show that preventing water breakthrough to wells in heavy oil is several-fold more important (in terms of well productivity and recovery rate) than that for conventional oil wells. Introduction Definition of heavy oil is not rigorous and varies between authors. Some clarify heavy oil by density measured on the API gravity scale as lower than 20 API. Others emphasize in-situ viscosity of heavy oil. Conventional-oil viscosity may range from 1 cp to about 10 cp. Viscosity of heavy oil and extra heavy oils may range from less than 20 cp to more than 1,000,000 cp. On the extreme, the most viscous hydrocarbon, bitumen, is a solid at room temperature (1, 2). Most of the world's oil resources are heavy, viscous hydrocarbons. It is commonly accepted that after conventional oil and natural gas, the next easiest fossil fuel resource to develop is the viscous oil. It has been estimated that there is probably 2.5 times the amount of viscous oil as there is conventional oil. By some estimates, there are 8–9 trillion barrels of heavy oil and bitumen in place in the world (not including hydrocarbon in shales) (1). Canada has the largest heavy oil resource with some 1.7 trillion barrels of extra-heavy oil situated in the oil sands of Alberta, plus a further 25 billion barrels of heavy oil in the 10 – 22.3 API gravity range. Venezuela has around 1.2 trillion barrels of extra-heavy oil in the 400-mile long Orinoco Belt in the eastern part of the country. Reserves in Russia-another heavy oil giant, are approaching 200 billion barrels of bitumen and extra heavy oil (1- 3).
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 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 ».