Waterflood Application in Semi-Consolidated Heavy Oil Reservoirs Developed by Horizontal Well Technology
Notice bibliographique
Résumé
Waterflooding is the most common injection process in oil industry and none of the more complex enhanced oil recovery (EOR) methods enjoys the widespread applicability of waterflooding today. Operators in the field have extensive experience in application of waterflooding to conventional light oil reservoirs. However, the waterflood mechanisms and its optimum operating practices in heavy oil reservoirs are poorly understood. Since the primary recovery factor in heavy oil reservoirs is between 5-10% of the original oil in place (OOIP), there is a need for enhanced techniques to increase recovery from these reservoirs. In Western Canada, waterflooding has been applied to lower viscosity heavy oil reservoirs called medium oil reservoirs and somewhat surprisingly, it has increased the ultimate recovery factor of these pools by 100%. Recently, operators have extended the waterflood applications to heavier oil reservoirs which have been developed by horizontal well technology. These reservoirs are usually semi-consolidated sandstones with oil viscosities of more than 1000 cP, which historically, did not produce oil economically with Cold Heavy Oil Production with Sand (CHOPS) technology. This thesis has investigated several field applications of waterflood process in these heavy oil pools developed by horizontal well technology to better understand the recovery mechanism of waterflood in this type of reservoirs and determine important parameters, which affect the performance of the process. Learnings from empirical data, analogous pools and numerical simulation studies are used to develop an initially low water saturated and semi-consolidated heavy oil pool with horizontal wells and implement waterflood application successfully. The PVT data, core flooding test results and detailed geology data are incorporated in a numerical simulation model. Heterogeneous history matched numerical simulation model is used to conduct a sensitivity analysis for several inter-well spacing and then the predicted production forecasts are used in economic models to determine the optimum development spacing. The reservoir was successfully developed with drilling horizontal wells during 2012 and 2013. Then the simulation model was updated based on production profiles from newly drilled horizontal wells. The field conformance plots from analogous pool that has been waterflooded for more than two decades are used to calibrate the reservoir simulation model to predict the waterflood recovery factor and conduct a sensitivity analysis to different operating practices. The waterflood production profile for Voidage Replacement Ratios (VRR) of less than one is generated and economic models are used to estimate the heavy oil waterflood reserves and evaluate the viability of the project. Finally, the generated production profile from the model is compared to actual waterflood results to validate the model. The result of this work shows that the waterflood recovery mechanism in heavy oil reservoirs is different from conventional displacement process and the recovery of the process can be improved significantly by applying optimized operating conditions in the field. Predicting the heavy oil waterflood profiles remains as a main challenge for industry and there is a need to develop a tool to forecast the waterflood response in heavy oil reservoirs.
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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 | 0,001 | 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 | 0,001 | 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 ».