Notice bibliographique
Résumé
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 157923, ’Real-Time Optimization of SAGD Wells,’ by Luis E. Gonzalez, SPE, Peter Ficocelli, SPE, and Tad Bostick, SPE, Weatherford, prepared for the 2012 SPE Heavy Oil Conference Canada, Calgary, 12-14 June. The paper has not been peer reviewed. The steam-assisted-gravity-drainage (SAGD) process along with an efficient steam-use process can reduce production costs and increase the oil-recovery rate. The use of real-time downhole monitoring is an effective approach to achieve this optimization. The use of downhole distributed-temperature sensing (DTS) and array-temperature sensing by use of fiber-optic technology has led to instrumented wells that enable data access on a real-time basis, leading to better control of operations, and to optimizing the steam process. Also, fiber-optic technology enables measuring pressure and temperature over the same fiber and in close proximity along the wellbore. Introduction At reservoir conditions, bitumen is essentially immobile, and recovery of these highly viscous fluids requires viscosity reduction, often by applying heat. The SAGD process is an effective recovery method for heavy oil and bitumen. The SAGD process typically uses two parallel horizontal wells that normally are separated vertically by approximately 5 m. The top well is the steam injector, and the bottom well is the producer. As steam is injected, a steam chamber will grow around and above the injection well. Despite its effectiveness, the SAGD process has many economic risks including a high initial investment for constructing the surface facilities and uncertainties related to product prices. Displacement efficiency is a critical factor in controlling oil recovery from the steam chamber, and, although increased volumetric sweep is beneficial, the chamber-growth rate greatly affects the rate at which the displacement efficiency increases in the steam chamber. Increasing the volume of the steam chamber too quickly may decrease the effectiveness of the SAGD process. Uniform distribution of steam along the entire length of the wellbore could lead to a more-uniform steam-chamber growth, making the entire length of the well productive and developing optimum performance of a SAGD well pair. Traditionally, the SAGD injection well is completed with dual injection strings (one injection string ending at the heel and the other injection string ending at the toe) and the production well is completed with a slotted liner, as shown in Fig. 1. Steam distribution along the well is governed by different factors. The most important factors include pressure in the injector and producer wells, fluid-flow regime, fluid velocity, wellbore trajectory, and heat loss along the length of the wellbore. A new well/injector configuration is proposed that includes steam diverters, inflow-control devices, centralizers, fiber-optic pressure gauges, a fiber-optic DTS system, and control lines. An inter-mediate configuration could be the traditional dual string with the addition of temperature and pressure measurement by use of fiber-optic technology to help control the shape of the steam chamber.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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) | 0,003 | 0,001 |
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 ».