A New Coupled Fluid Flow/Stress Model for Porous Media Behavior: Numerical Modeling and Experimental Investigation
Notice bibliographique
Résumé
Proposal Reservoir management has been improved dramatically through adaptation of new technologies, enhancement of uncertainty involved and better data management to meet the challenges of today's economic constraints. Yet, these remarkable achievements included little or none about questioning the fundamental concepts of reservoir behavior and the assumptions made at the early days. In this paper, a comprehensive experimental program has been carried out using a triaxial set-up equipped with on-line acoustic apparatus to study reservoir behavior under depletion process. Fluid flow and reservoir rock properties' behaviors have been investigated as the reservoir is being produced. It has been concluded that the currently used methodology is in great error. Using the diffusivity model based on Darcy's law is one source of this error and the assumption of constant porosity and permeability throughout the life of the reservoir is another source. Therefore, a new fluid model has been proposed to replace the Darcy's model. The new model is derived from the Navier-Stokes equation and is capable of addressing all kinds of fluid flow taking place in reservoirs at low and high flow velocities including both Darcian and non-Darcian regimes1. On the other hand a new model relates porosity to the mean effective stress changes during a depletion process has been mathematically derived, this model is able to track porosity changes as effective stresses increase during reservoir production. The idea is to couple this model with the fluid flow model introduced in this study so both porosity and permeability can be updated at each time step during simulation of reservoir behavior. Laboratory results confirm the numerical predictions of the proposed coupled fluid flow/stress model, at the same time the laboratory results are in complete disagreement with Darcy's model predictions. Improvement of reservoir simulators' accuracy is expected through the implementation of the newly proposed model. Introduction Traditionally, data about petrophysical properties are essential for reserves' estimates and for the fluid flow characterization of petroleum reservoirs. A great deal of money and effort are expended to determine these properties accurately. Permeability and porosity are among those properties and are by far the most important. Porosity is the key for reserves' estimates while permeability is the main parameter to predict flow rates, design drawdown and therefore wellbore completion. Until recently, the common belief was that, once determined, these properties remain constant throughout the production life of the reservoir. However, numerous research studies2–14 including this one, show that this is not the case. During the pressure depletion process as production from the reservoir continues, effective stresses within the reservoir increase. The effect of reservoir stresses on porosity and permeability of the reservoir is more severe when porosity and permeability are high (fractured media is an extreme case), although some experimental studies like Hubbert and Willis3, Voight4 and Rosepiler5, showed that this effect is still significant even at low porosity and permeability. When considering percentage losses from the original state of the reservoir, it seems that the same percentage of porosity and permeability reductions was experienced regardless of the original values. It is also understood that stress paths have a large influence on horizontal and vertical permeability as well as on porosity. The elastic uniaxial strain model is used in reservoir engineering mostly to describe production-induced changes in horizontal stress due to pore pressure decline (pressure depletion). It predicts the total horizontal stress by using overburden stress, reservoir pressure decrease and material mechanical parameters. The principal assumption in this model is that there is no lateral deformation (zero horizontal strain condition) during the depletion process.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 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) | 0,001 | 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 ».