Modeling 2-Phase Flowback of Multi-Fractured Horizontal Wells Completed in Shale
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Abstract Early fluid production and flowing pressure data gathered immediately after fracture-stimulation of multi-fractured horizontal wells may provide an early opportunity to generate long-term forecasts in shale gas reservoirs. These early data, which often consists of hourly (if not more frequent) monitoring of fracture/formation fluid rates, volumes and flowing pressures, are gathered on nearly every well that is completed. Additionally, fluid compositions may be monitored to determine the extent of load fluid recovery, and chemical tracers added during stage treatments to evaluate inflow from each of the stages. There is currently debate within the industry of the usefulness of these data for determining the long-term production performance of the wells. "Rules of thumb" based upon percentage of load fluid recovery are often used by the industry to provide a directional indication of well-performance. More quantitative analysis of the data is rarely performed; it is likely that the multi-phase flow nature of flowback, and the possibility of early data being dominated by wellbore storage effects has deterred many analysts. In this work, the use of short-term flowback data for quantitative analysis of induced hydraulic fracture properties is critically evaluated. Examples from the Marcellus shale are analyzed. The short (< 48 hours) flowback periods were followed by long-term pressure build-ups (~1 month). Gas/water production data was analyzed using analytical simulation and rate-transient analysis methods designed for analyzing multi-phase coalbed methane (CBM) data. One interpretation is that the early flowback data corresponds to wellbore + fracture volume depletion (storage). It is assumed that fracture storage volume is much greater than wellbore storage. This flow-regime appears consistent with what is interpreted from the long-term pressure buildup data, and from rate-transient analysis of flowback data. Assuming further that the complex fracture network created during stimulation is confined to a cylindrical region around perforation clusters in each stage, fluid production data can be analyzed using a 2-phase tank model simulator to determine fracture permeability and drainage radius, the latter being interpreted to be equivalent to effective (producing) fracture half-length. Total fracture half-length, derived from rate-transient analysis of on-line (post-cleanup) data, verifies the flowback estimates. An analytical forecasting tool that accounts for multiple sequences of post-storage linear flow, followed by late-stage boundary flow, was developed to forecast production using only flowback-derived parameters, volumetric inputs, matrix permeability, completion data and operating constraints. The preliminary forecasts are in very good agreement with on-line production data, after several months of production. The use of flowback data to generate early production forecasts is therefore encouraging, but needs to be tested for a greater data set for this shale play and for other plays.
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.
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 | 0,000 | 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) | 0,001 | 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 découle