A Coupled Flow–Geomechanical Modeling of Out-of-Sequence Fracturing Using a Dual-Lattice Implementation of Synthetic-Rock-Mass Approach
Notice bibliographique
Résumé
Summary In out-of-sequence (OOS) pinpoint fracturing, Stage 1 is fractured, followed by Stage 3, after which Stage 2 (center fracture) is placed between Stages 1 and 3 (outside fractures). The center fracture can exploit the reduced stress anisotropy to activate planes of weakness (e.g., fissures) and create branch fractures that can connect hydraulic fractures to stress-relief fractures, ultimately enhancing fracture connectivity and complexity. It has been trialed in western Siberia (2014) and western Canada (2017 to 2019) with overall operational and production performance success. Previous fracture-modeling works calibrated by OOS fracturing trials have either used shear-decoupled planar-fracture models (in which slippage along the shear planes restricts the displacement to a limited area because of displacement damping)—which are unable to reproduce out-of-plane fracture complexity, and to dynamically track the change in stress anisotropy and orientation—or discrete-fracture-network (DFN) models, which often exaggerate the fracture-network connectivity, and reproduce unrealistically high fracture-network-extension pressures in the stimulated reservoir volume (SRV). This work attempts to resolve the issues in planar-fracture and DFN models by more realistically addressing the dominant mechanisms of OOS fracturing, dynamic changes in the stress anisotropy and orientation, activation of pre-existing planes of weaknesses, and poroelasticity using an iteratively coupled flow–geomechanical model that uses the dual-lattice implementation of the synthetic-rock-mass (SRM) model with a robust, fully coupled, iterative flow/stress solution to capture the following: Nonlinear deformations caused by induced tensile- and shear-fracture-complexity propagation Induced stress shadowing in and around the SRV Sliding of opened, pre-existing joints, fractures, and fissures using the smooth-joint model (SJM) Propagation of the hydraulic fracture as an aggregate of intact matrix fracturing and opening and slip of pre-existing fluid-filled planes of weakness (e.g., joints, fractures, fissures) Permeability enhancement in the main tensile and complex fractures following the updated deformation aperture from the coupled solution The results (fracture geometries and treatment pressures) of the three models (planar-fracture, DFN, and SRM with lattice models) are compared after using each model for treatment-pressure history matching of an OOS-fracturing trial. The calibrated, coupled SRM with lattice model more reasonably reproduces the measured fracture-extension pressures and end-of-job pressures from OOS pinpoint fracturing treatments, and it reveals the following: The dynamic change in the stress-field orientation and magnitude during OOS fracturing leads to a reduction in stress anisotropy and complex out-of-plane fracturing in the SRV for center fractures. Center fractures tend to be narrower and shorter if sufficient out-of-zone growth is attained in the absence of strong vertical containment, making OOS fracturing an option for penetrating multistacked zones in one treatment. Where center fractures are shorter or near-well fracture complexity is generated, OOS fracturing can be considered in treating the child wells to reduce fracture hits. Compared with planar-fracture and DFN models, this coupling technique achieves the following: Accounts for dominant mechanisms of complex shear and tensile fracturing Renders fast computation in simulating large 3D models with dual-lattice implementation of SRM with SJM Reproduces fracture surface area and SRV permeability more realistically Leads to a more reasonable history match of the measured OOS-fracturing pressures
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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 ».