Well Performance Evaluation of Carbonate Reservoirs After a Novel Hybrid Volume Stimulation Treatment
Notice bibliographique
Résumé
Abstract A large proportion of gas and oil resources are trapped in carbonate reservoirs. Efficient development of these formations is crucial for world energy supply. Recently, a novel hybrid volume stimulation (HVS) technique has been proposed and enhanced carbonate reservoir production in the Bohai Bay Basin and the Ordos Basin of China (Cai et al., 2015; Chu, 2017). This technique involves three stages, including pad-fluid fracturing (primary fracture and fracture branch initiation), massive acid fracturing (acid etching and connection of natural and induced fractures), and proppant injection (conductivity maintenance). Compared with conventional acid fracturing, HVS generates a more complex fracture system by taking the advantage of both hydraulic fracturing and acid fracturing, mitigating high-temperature effects, and increasing the acid penetration distance. Currently, no existing models can predict the pressure and rate behavior of wells after HVS treatments due to the complex fracture geometry and the complicated flow pattern. This study presents a multi-region linear flow model to facilitate evaluating well performance of carbonate reservoirs after HVS and obtaining a better understanding of key factors that control well responses. The model incorporates the fundamental characteristics of the complex fracture system generated by HVS. The primary hydraulic fracture is characterized by two flow regions. One is for the propped primary fracture segment (region 1), while the other represents the unpropped but acid-etched primary fracture tip (region 2). The region adjacent to the primary fracture (region 3) denotes acid-etched fracture branches. Because the acid usually cannot fully penetrate the hydraulic-fracturing-induced branches, the fractal theory is employed to depict the properties of the small fracture branches beyond the acid-etched sections. Finally, the unstimulated reservoir is described by a dual-porosity region (region 4) with vug and matrix systems. Specifically, triple-porosity region 3 contains two possible flow scenarios: one is from vugs to matrices, to fracture branches, and to the primary fracture, while the other is from vugs to matrices, and to the primary fracture. Two weighting factors are utilized to describe the proportion of reservoir volume that is involved in the two fluid flow scenarios. These flow regions are coupled through flux and pressure continuity conditions. The degenerated form of this model is verified against a published analytical model. A good agreement has been achieved between the results of the two models. Analysis results show that four flow regimes can be identified in the log-log type curve. Compared with classical type curves of fractured wells, there is a distinctive fracture-branch-affected transient regime in the pressure derivative curve with a slope between one-half and unity. The HVS generated complex fracture system enhances well productivity from the inter-porosity flow regime to the late fracture-branch-affected transient regime. The impacts of various fracture and reservoir properties on pressure and rate behavior are also documented.
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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 | 0,000 | 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 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 ».