Fracture Stimulation Challenges in Tight Walloons Coal Measures: Surat Basin Queensland, Australia
Notice bibliographique
Résumé
Abstract Walloons Coals of the Surat Basin, Queensland (Australia) contain world class Coal Seam Gas (CSG) plays, where permeability varies from high (>1Darcy), due to Gaussian curvature-related natural fracture connectivity, to low (<1mD) due to unidirectional fracture-systems attributed to regional unidirectional flexure. The low permeability Walloons Coals require stimulation to unlock their gas resources. This contribution describes the design evolution of stimulation concepts in the Surat Basin in context of five key subsurface drivers Coal net to gross: Surat Basin coals contain 30 coal seams with a cumulative thickness of 20-35m in a gross rock column of >300m Permeability of coals requiring stimulation for economic flow rates varies from <1mD - ~30mD Varying stress regimes, both vertically and laterally Ductile rock properties in Walloons coal reservoirs Productivity Index drop (PI drop) can occur when (incompressible) water is replaced by (compressible) gas during coal dewatering Early stimulation treatments in Surat Basin (pre-2010) followed ‘standard’ high rate water/sand designs adapted from the shale industry. However, high treating pressure and rates resulted in several instances of casing shear (Johnson et al. 2003) particularly at depths associated with stress regime transitions. Subsequent designs (2010-12) repeated water fracs albeit including ample diagnostics (Johnson et al 2010; Flottmann et al 2013), showing that water fracs appear to be ineffective in stimulating Walloons Coals. Design optimizations in 2015 (Kirk-Burnnand et al. 2015) based on extensive modeling work (Pandey and Flottmann 2015), identified low rate gel fracs as optimal to stimulate rocks with ‘ductile’ Walloons-specific coal properties. However, treatment rates were limited to optimize height growth, both to connect coals and to avoid height growth into non-reservoir. Initial production data indicated a drop in well productivity in some fracture stimulated coals (Busetti et al. 2017). Consequently, stimulation designs were modified in late 2016 to account for such productivity drops while maximizing the fluid recovery. Early time post stimulation drawdown strategy was also field-tested to mitigate loss of well productivity due to excessive drawdown which could cause partial or full fracture closure (especially near the wellbore region), and lead to loss of communication between reservoir and well. Sub-surface drivers identified in tight Walloons Coals control the effectiveness of any stimulation option deployed. These drivers influence the effectiveness of stimulation in multiple ways. First, these drivers can lead to a sub-optimal connectivity between well and reservoir resulting in poor productivity and marginal recovery. Second, the drivers may influence an operator towards expensive stimulation options which may provide better well to reservoir connectivity but diminish the economic value due to the high costs involved. Hence the inclusion of sub-surface drivers in selecting stimulation design is paramount as demonstrated in this paper.
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.
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 | 0,000 | 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 ».