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Enregistrement W2896049231 · doi:10.7939/r3542jp23

Scale-up of Solvent Injection Processes in Post-CHOPS Applications

2017· article· en· W2896049231 sur OpenAlexaboutno aff
Martinez Gamboa

Notice bibliographique

RevueUniversity of Alberta Library · 2017
Typearticle
Langueen
DomaineEngineering
ThématiqueInnovative Microfluidic and Catalytic Techniques Innovation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScale (ratio)Environmental scienceComputer scienceGeography

Résumé

récupéré en direct d'OpenAlex

Cold Heavy Oil Production with Sand (CHOPS) is widely used as a primary non-thermal production technique in thin heavy oil reservoirs in Western Canada and some other regions in South America. It has been reported that more than 85% of the original oil in place remains trapped in-situ, requiring additional follow-up (i.e., post-CHOPS) recovery strategies to be implemented. Solvent-aided processes, such as cyclic solvent injection (CSI), are commonly adopted due to the particular thin pay zone, which renders the application of thermal approaches uneconomical. It is widely accepted that configuration of wormhole networks (i.e., high-permeability channels caused by sand production) and foamy oil flow are key characteristics pertinent to these processes, and they play an important role in the overall success. Field-scale flow simulations are often performed to approximate the reservoir response and to optimize operating strategies. However, grid block sizes in field-scale models are generally much larger than the wormhole scale, and numerical analysis is often performed by arbitrary adjustment of dispersivity. This thesis proposes a practical workflow to scale up these mechanisms for field-scale simulations in wormhole networks that span over multiple scales. First, a set of detailed high-resolution (fine-scale) simulation models, where both matrix and high-permeability wormholes (modeled as fractal networks) are represented explicitly in the computational domain, is constructed to model how the solvent propagates away from the wormholes and into the bypassed matrix. Next, a dual-permeability approach is adopted to facilitate the scale-up analysis. Solvent transport and additional mixing in wormhole networks can be captured by parameters such as shape factor and effective dispersivity in an equivalent coarse-scale dual-permeability system. Bivariate distributions of effective longitudinal/transverse dispersivities and wormhole intensity are constructed and calibrated by minimizing the difference in recovery response (i.e., profiles of gas/oil production) between the detailed model and an equivalent dual-permeability continuum model. Finally, field-scale simulations are constructed using average petrophysical properties and initial conditions (fluid saturations, pressure distribution, and wormhole development) commonly encountered at the end of CHOPS. Multiple field injection scenarios (i.e., of different number of cycles and durations of the soaking period) are simulated and analyzed. As expected, extended soaking period is more beneficial in terms of ultimate oil recovery (slower decline in oil rate), but it also reduces the early production rate. These observations can be attributed to the fact that a longer soaking period may prolong the production phase by increasing the effective drainage area contacted by the solvent; however, the amount of solvent in the near well region is also diluted. Interestingly, when an economic limit (i.e., minimum oil producing rate) is imposed, the optimal soaking time is not necessarily the longest one. It depends on the trade-off between extracting additional oil recovery at late times versus producing at a higher rate at early times. The analysis also reveals that during the implementation of multiple consecutive cycles, the two initial cycles contribute the most to the final oil recovery. Therefore, injecting larger volumes of solvent and extending the soaking times are recommended strategies during the first and/or second cycles. In addition, when the amount of solvent available is limited, the results support in the strategy of injecting all the solvent in one single consolidated cycle, with an extended soaking period, rather than performing shorter consecutive cycles.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,433
Score d'incertitude au seuil0,267

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,192
Écart entre enseignants0,186 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2017
Routes d'admission1
Résumé présentoui

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