Cluster Flow Identification During Multi-Rate Testing Using a Wireline Tractor Conveyed Distributed Fiber Optic Sensing System With Engineered Fiber on a HPHT Horizontal Unconventional Gas Producer in the Liard Basin
Notice bibliographique
Résumé
Abstract This paper investigates the flow performance of a horizontal unconventional gas producer where cluster flow has been detected and quantified. The method employed is the first use of a wireline deployed engineered fiber optic Distributed Acoustic Sensing (DAS) system for the purpose of production monitoring. It further describes the technological advancement of the DAS system. While distributed fiber optics sensors have been used in unconventional wells for over ten years, the focus has been on stimulation monitoring, where relatively large thermal and acoustic signatures are easily measured. There has been limited success on the use of the same systems for production monitoring in horizontal wells since the thermal and acoustic flow signatures are very small. The recent technological advancements achieved in the area of Distributed Acoustic Sensing, using engineered fibers with dramatic improvements in the signal-to noise ratio, now make it possible to sense low levels of inflow noise with DAS systems. This study presents two distinct ways of analysing DAS data to extract production information and demonstrates the analysis using real field data. The well is an unconventional dry gas producer in the Liard Basin, Canada, which was completed in 18 stages, with 3 cluster per stage, a total of 54 clusters along a horizontal section of ~2000m. The top 11 stages were logged on tractor conveyed wireline with DAS and DTS data acquired over a 19-hour period. The acquisition covered an initial shut-in period, followed by a ramp up to a maximum test rate, and a final shut-in period. Data from the full acquisition period was analysed and is presented in the paper. The data acquired at various points during the acquisition period was used to detect and quantify inflow. It was found that one of the clusters was active throughout the shut-in period and inactive during the maximum test rate. We were also able to identify more clusters being activated as the production rate increased. The increase in the number of active clusters was not proportional to the increase in the surface gas rate, with heel side clusters becoming active before the toe side clusters as the production rate was increased. The results of this survey yielded remarkable insights that informed the operator on the completion efficiency and the relationship between the total production rate and cluster activity.
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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) | 0,000 | 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 ».