Assessment of Limited Entry Cluster Distribution Effectiveness and Impactful Variables using Perforation Erosion Measurements
Notice bibliographique
Résumé
Abstract Limited entry perforating is the most common method of diversion used in unconventional hydraulic fracturing. Still it is not immediately apparent how even the stimulation treatments are distributed between the clusters, and the impact of different perforating variables. This paper presents the finding of two well perforation erosion measurement in the Duvernay formation of Western Canada using two logging techniques, optical imaging and ultrasonic measurements. In two wells multiple perforating variables were tested including shot diameter, shot orientation, perforation pressure drop, variable vs constant cluster shot count, and cluster count per stage. Unstimulated perforations were measured for each perforating charge type and orientation to validate baseline perforation dimensions prior to erosion and use to calibration data for incremental erosion calculation. Each of the two wells were logged with an ultrasonic measurement device while one of the two was also logged with an optical imaging tool separately. Perforation area increase for each perforation and the total area increase for each perforation cluster were analyzed to assess the impact of perforating variables on erosion of individual perforation and effectiveness of different perforating designs with respect to equal distribution. The erosion measurement using both logging techniques provided unique opportunity to compare their measurement capability (optical imaging measured 90% of fracture stages as compared to ultrasonic, but both techniques missed ~10% of total measured perforations to quantify perforation size) and range of uncertainties of measurement erosion (general variability in eroded perf diameter measurement of individual perforation by each technique, but statistically R2 of 0.95 correlation excluding 3 outliers of total 873 perforations measured). Of the variables tested a few stood out as providing more even perforation distribution than others. Not surprisingly, reducing total shot count and subsequent flow area, creating a larger pressure drop at the perforations, resulted in a more even distribution of erosion. Smaller initial hole size with an increased shot count, to provide a similar expected pressure differential, also resulted in improved cluster distribution. Variable shot count perforating achieved a more even distribution and counteracted a nature tendency for heel bias. In general perforations on the lower side of the casing showed increase erosion compared to perforations in the upper part of the casing, providing credence to the notion that sand densities are higher in the bottom of the casing even with very high sand transport velocities. This paper shares a case history with results comparison of two major erosion measurement techniques, erosion variability of each perforation as per its azimuth, and highlights some of the variables that have a large impact on cluster distribution and is of benefit to anyone optimizing a perforating design or developing a similar trial to test cluster distribution in other basins.
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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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 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 ».