Simulation of Reservoir Charge to Predict Fluid Compositional Distribution: A New Way to Test the Geologic Model
Notice bibliographique
Résumé
Abstract Reservoir fluids often exhibit compositional complexity vertically and laterally in reservoirs. These complexities include viscous oil and tar distributions, and gas-oil ratios and can also include more subtle fluid variations such as varying biomarker ratios and isotopic ratios. Recent advances have led to resolving of many mixing dynamic processes of reservoir charge fluids over geologic time. The objective is to simulate reservoir charge over geologic time to (a) constrain key attributes of the reservoir which comprise the geologic model and (b) to improve the prediction of fluid properties across tectonic features. The analysis of 80 reservoirs within the context of reservoir fluid geodynamics has allowed identification of mass transport and mixing dynamics of different charge fluids over geologic time. Reservoir simulation can be used to predict resulting compositional distributions; these predictions depend on (1) reservoir attributes, both known and uncertain, (2) the properties and locations of charge fluids, such as density and viscosity and (3) the time since charge. The comparison of predicted and measured fluid distributions allows history matching of reservoir charge. Fluid mechanics principles are shown to validate simulation results building confident in their predictions. Forward modeling with reservoir simulation shows that even simple 2D simulations can illuminate key reservoir attributes that impact fluid compositional distributions such as connectivity and baffling especially over different areal sections of the reservoir. A reservoir case study is used to validate the charge and mixing dynamics that are employed in modeling. Reservoir simulation shows that a substantial range of the extent of mixing is found dependent on reservoir and fluid properties, thereby providing a very sensitive test of these reservoir parameters. In addition, the location of charge also impacts the predicted compositional distributions across a reservoir. More comprehensive and complicated simulation models can be developed if preliminary, simple models show significant promise in testing important reservoir uncertainties. The impact of many parameters can be quantified including reservoir architecture, dip angle, aspect ratio, different aquifer configurations, various baffling structures, viscosities and density contrasts of the charge fluids, and the sequence of the fluid charges. Generalized systematics are developed which are very useful to characterize the dynamics of reservoir charge over geologic time. Simulation of reservoir charge for history matching is a very new concept, yet it relies on standard reservoir simulation (over geologic time) for comparison between predicted vs measured fluid compositional distributions of present day to test the reservoir and geologic models. This approach has shown that several presumptions about mixing of charge fluids were not general and inhibited the new workflow. Removing such conceptual limitations has been crucial to developing the novel workflows introduced in this paper to test the reservoir.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».