Optimized Natural Gas From Coal Stimulations in the Western Canadian Sedimentary Basin, Part I: Database Collection
Notice bibliographique
Résumé
Abstract The Western Canadian sedimentary basin (WCSB) contains numerous coal seams of various ranks and petrophysical characteristics. The process presented in this paper correlates the area of interest with the rich historic volume of data that is available. Production, detailed stimulation data, engineering designs, petrophysical analysis, fluid analysis and sophisticated computer work come together in the application to produce a statistical approach to initial stimulation designs. The final design evolves with respect to the characteristics of the well of interest. Designing stimulations for coal beds is complicated based on the small amount of unshared and unformatted data that exists in any one place. The significant accomplishment of this paper is rooted in obtaining a large amount of useful data from the many small, incomplete and confusing data sources. Although the data has always existed in various formats and places, the completions or wells rarely reference the target of Natural Gas from Coal (NGC). Cooperation by industry partners enhances the efforts to combine information and improve correlations of well production responses to stimulations. This paper presents the first step in developing a comprehensive design philosophy and database collection to assist is optimizing future NGC wells and plays. Introduction The use of offset treatment data is a valuable tool in the design of fracture stimulation treatments when used properly. However, "just doing what was done before" is not necessarily providing the best design. Offset data is only one aspect of an engineer's repertoire that should also include a thorough knowledge of the reservoir, the client's expectations and goals as well as a solid background of experience. However, designing fracture stimulation treatments for coal seams is a relatively new process. Complicating this learning curve is the shortage of data available to industry due mainly to the tight-hole status of many NGC projects. Everyone wants to benefit from the learning curves of others, but are sure to carefully guard their own experience. However, this state of secrecy is not unwarranted since relatively large tracts of land are waiting to be purchased and developed. Based on the extended times required to show economical production, tighthole status is requested for as long as 5 years to ensure as much secrecy as possible while developing the plays and positioning for future land sales. Through sophisticated data mining techniques, an extensive NGC database can be pieced together using internal and industry data. This data set includes coal reservoir data, completions and production impact results across a wide geographical and geological area encompassing all the major coal plays in the WCSB. The use of this data, while respecting our tight-hole information, is a valuable tool in the design of effective NGC stimulations. Outline of Project Although gas bearing coal bed deposits are pervasive throughout Western Canada, the variation in reservoir quality is significant. To effectively stimulate various coal seams, a thorough understanding of the particular coal is required. Through a detailed analysis of the available data, trends of effective stimulation designs can be developed.
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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 | 0,001 | 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) | 0,001 | 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 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 ».