Data-Driven Well Pad Development Performance Review: Focus on the Role of Liner Design on Well Performance
Notice bibliographique
Résumé
Abstract Steam Assisted Gravity Drainage (SAGD) is the dominant in-situ method for oil production in Western Canada. The current study analyzed the relative performance of various well-completion practices using data from 4,000 well pairs that were drilled over a decade. The data analysis provided a unique opportunity to find best operating practices. The scope of this paper is to review the performance of major thermal projects in Canada and investigating the effect of liner design and Flow Control Devices (FCDs) on well pair performance and development. Cumulative oil production and cumulative steam oil ratio (cSOR) were used as the key metrics in comparing the well performance in a SAGD operation. However, to compare different pads and different projects, it was critical to normalize the data with geological variation, well length, well spacing, and with consideration to the well failure rate, remedial completion and re-drills. In this paper we review seven thermal projects of four key operators with almost 3,500 wells and 1,200 well pairs in operation as early as 1996. All geoscience, and production/injection data have been extracted from public databases and utilized to develop a data-driven model. The reservoir thickness variation for each well was determined using available geoscience data, and through the development of a geological model based on the available core data and well logs. The model was used to define the drainage volume for each well pair, which in turn was used to assign a geological ranking to the well. The cumulative oil production and cSOR were then normalized with the geological ranking and the size of the net drainage volume. The number of well pairs in each pad and the cumulative pad production were normalized against the number of days in production and their relative decline, which allowed for comparison between pads within the same project, as well as pads from other projects. The cumulative production of the active pads in each project was used to compare the relative performance of different projects. Also, we separated the projects and wells based on their use of FCDs in the producer and injector to compare the relative performance of each technology in the field. This paper is the initial phase of the study on the role of completion design on relative well and well pad performance. The results will help completion and production engineers to better understand the well pair and pad relative performance and how to normalize the oil production data against geological variation to compare performance.
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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 | 0,001 | 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 ».