Factors Affecting Horizontal Well Gravel Pack Efficiency
Notice bibliographique
Résumé
Abstract Four major factors affecting horizontal well gravel pack were studied using a 3D simulator developed for horizontal well gravel packing. The factors included settling effect, gravel concentration, injection rate and carrier fluid viscosity. Three actual field horizontal well gravel pack jobs obtained from the literature were performed using the simulator to study these factors. The effect of carrier fluid viscosity on gravel pack efficiency was studied by varying the viscosity between 1 and 51 cP, injection rate between 0.159 and 0.636 m3/min and gravel concentration between 0.50 and 4.0 pound mass per gallon. Simulation results demonstrate the validity of the solution routine and the capability of the simulator, because the results were in agreement with the field results. The predicted pack efficiency for cases that considered settling effect are consistently higher than the cases without settling effect. The study also showed that the settling factor decreases with increasing gravel concentration and injection rate. Introduction Several authors have investigated the factors affecting gravel transportation and placement towards achieving an effective gravel pack. Gruesbeck et al.(1) performed experiments to measure pack efficiency as a function of screen parameter, fluid and gravel properties, completion configuration and angle of inclination of the wellbore. They concluded that packing efficiency increases with lower gravel concentration, lower gravel density, higher flow rate and increasing resistance to fluid flow in the tailpipe/screen annulus. Hodge(2) substantiated Gruesbeck et al.'s work by determining the accuracy of the predicted equilibrium bank height. Elson et al.(3) reported a study conducted to define optimum gravel pack procedures and completion design factors for high angle wells. Results of the study showed that high viscosity carrier fluids with high gravel concentration provide good gravel transport, but are unsuitable in wells with angles of 80 º from vertical. Skaggs(4) presented the results of a large-scale vertical wellbore model he used to study gravel transport through perforations during a high-density squeeze gravel packing operation. He concluded that the transport efficiency through perforations increases with increased fluid viscosity, gravel concentration and annular velocity. Winterfeld and Schroeder(5) developed a finite element numerical simulator and used it with a full-scale wellbore model to study gravel placement in perforations and annulus. Their model was based on mass and momentum conservation equations, as well as those for vertical wells. Peden et al.(6) developed some mathematical design models for predicting the optimum combination ofrequired design parameters, such as tailpipe diameter, slurry flow rate and gravel concentration, for an optimum packing efficiency. These models were based on extensive experimental study of factors affecting packing efficiency and dimensional analysis of obtained data. In 1988, Wahlmeier and Andrews(7) improved on the earlier works of Gruesbeck et al. and Peden et al. by developing a pseudo-three-dimensional mathematical model suitable for designing and evaluating gravel pack treatments. Shryock(8) worked on a full-scale deviated model and had similar conclusions with earlier works.
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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».