Modelling Geomechanics Into Petroleum Reservoir Numerical Simulation: A Coupled Technique in a Water Injection Project
Notice bibliographique
Résumé
Abstract Once a reservoir has been discovered it is essential to characterize it as accurately as possible in order to determine the most effective way of draining the recoverable oil. Reservoir characterization involves a great amount of data from geology, laboratory and production. An important data aspect in reservoir characterization is whether or not to consider geomechanic effects on the reservoir response. This is true in several exploitation scenarios and in particular when designing water injection projects for high-pressure/high-temperature reservoirs. This work describes the construction and numerical simulation of a reservoir model with incorporation of geomechanics for a real oilfield producing under waterflooding. Firstly, the model boundaries are prolonged to highlight the reservoir geomechanical behavior in the producing area. Secondly, the reservoir model is populated with geomechanical variables like vertical and horizontal stresses and equilibrated. Thirdly, a coupled procedure is implemented that allows the incorporation of geomechanics during numerical simulation of reservoir behavior. In this coupled procedure a commercial numerical flow simulator resolves the fluid flow behavior while a commercial geomechanical package controls the deformation aspects that occur during waterflooding. The technique developed in this work has been applied for reservoir performance forecasting of a giant Brazilian deepwater oilfield producing by water injection. Results obtained in this real case problem revealed important geomechanical features that must be considered in complex oil exploitation project scenarios in which limited information and production uncertainties are present. Introduction There are five critical areas in the process of modeling deepwater reservoirs. These are geological and geophysical modeling, reservoir characterization, reservoir flow modeling, facilities/flow assurance, and uncertainties/risk analyses. This research will focus more in reservoir flow modeling. This work describes a general modeling process that improves reservoir understanding and performance forecasting. These factors are extremely important in a high cost, high-risk deepwater environment, where wrong decisions lead to expensive mistakes and can materially affect a company's financial standing. In this work, a methodology is developed which enables the incorporation of key mechanisms and parameters to solve a numerical reservoir simulation problem that considers geomechanical aspects. The proposed technique utilizes an iterative-coupled reservoir-geomechanical modeling approach to capture the link between flow and in-situ stresses. The main objective of this research is to explore uncertainties of flow through an oil reservoir that contains a major fault and which it is producing under water injection. It also aims on investigating the role of geomechanics in the fault reactivation. The usefulness of the technique developed here is illustrated for reservoir performance forecasting of a real Brazilian deepwater oilfield. The solution achieved to this real case problem will be considered in complex oil exploitation project scenarios in which limited information and production uncertainties are present. This work presents an approach to integrate geomechanics at the early stages of a field development.
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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 | 0,001 | 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 | 0,000 | 0,001 |
| 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 ».