Numerical Investigation of Sand Production Under Realistic Reservoir/Well Flow Conditions
Notice bibliographique
Résumé
Abstract A new numerical model has been developed for investigation of sand production under realistic reservoir/well flow conditions. The model allows prediction of critical drawdown leading to the onset of sanding as well as the rate of sand production in real time. The model predictions have been validated by using laboratory data. The proposed numerical model has been embedded into ABAQUS, which is a finite element program capable of simulating interaction between fluid flow and mechanical deformation of the medium. The model has been designed to encompass a number of the factors that are influential in the process of sanding. This includes a time-dependent coupled fluid flow and deformation analysis of the rock, material disaggregation, sand removal, and operational conditions including drawdown, depletion, and water-cut. The model has been validated by using the experimental data on hollow cylinder specimens involving real time sand production measurements under various conditions. The results of the numerical modeling study show a good agreement with experimental data in terms of the operational conditions leading to the onset of sanding as well as an estimation of the sanding rate. The model presents a live picture of the ongoing alterations in the material at the wellface during the production which provides a deeper insight into the role of the various parameters involved. Introduction Several sand production prediction methods have been proposed using geomechanical models. These methods could be grouped into analytical (e.g., Risnes et al. 1982, Morita et al. 1989a, Weingarten & Perkins 1992, van den Hoek et al. 2003) and numerical models (e.g., Morita et al, 1987a, Stavropoulou et al. 1998, Papamichos & Malmanger 1999, Vaziri et al. 2002, Nouri et al. 2006). The analytical models provide formulations for the flow rate required to induce tensile failure. Tensile failure of the material due to seepage drag forces is taken as criterion for sand production. Their limitation is the general constraints with respect to geometry, boundary conditions, and implementation of intricate material behavior. Further, they fall short in providing an indication of the severity of sanding once it is triggered. Numerical models could overcome many of the limitations mentioned above. Some of these models work by modeling rock disaggregation at cavity face in post-peak strength phase of the rock (e.g. Nouri et al. 2006). Others tie sand production to the mobilized plastic strain level (e.g. Morita & Fuh 1998). Sand production in these models occurs once equivalent plastic strain exceeds a threshold. Some numerical models assume sand production to be in the form of sand erosion which is tied to mechanical damage of rock around a wellbore (e.g. Geilikman et al. 1997, Vardoulakis et al. 1996, Stavropoulou et al. 1998). A critical review of various sand production models was provided in Nouri et al. (2006). This paper presented a finite difference model which used continuum mechanics approach for modeling the process of sanding as a function of several parameters that have an effect on sand production. These include: operation conditions, i.e., drawdown and depletion, completion technique, formation strength and mechanical behavior, permeability, and a moving boundary due to solid material flow, i.e., sand production.
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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 ».