Rigorous Estimation of the Initial Conditions of Flowback Using a Coupled Hydraulic-Fracture/Dynamic-Drainage-Area Leakoff Model Constrained by Laboratory Geomechanical Data
Notice bibliographique
Résumé
Summary The application of rate-transient-analysis (RTA) concepts to flowback data gathered from multifractured horizontal wells (MFHWs) completed in tight/shale reservoirs has recently been proposed as an independent method for quantitatively evaluating hydraulic-fracture volume/conductivity. However, the initial fluid pressures and saturation in the fracture network and adjacent reservoir matrix are generally unknown at the start of flowback, creating significant uncertainty in the quantitative analysis of flowback data. In this study, we present a semianalytical flow model, coupled with a hydraulic-fracture (fracture) model and constrained with laboratory-based geomechanical data, for evaluating the initial conditions of flowback. In previous work, a semianalytical model based on the dynamic-drainage-area (DDA) concept was used to simulate water-based fluid leakoff from an MFHW into a tight oil reservoir (Montney Formation, western Canada), with minimal mobile water, during and after fracturing operations. The model assumed that each fracturing stage can be represented by a primary hydraulic fracture (PHF) containing the majority of the proppant, and an adjacent nonstimulated reservoir (NSR) or enhanced fracture region (EFR), which is an area of elevated permeability in the reservoir caused by the stimulation treatment. Each region was represented by a single-porosity system. The DDA propagation speed within the PHF during the stimulation treatment was constrained through using a simple analytical fracture model. Although this approach was considered novel, several improvements and additional laboratory constraints were considered necessary to yield more accurate predictions of initial flowback conditions. In the current work, the modeling approach described previously was improved by representing the EFR with a dual-porosity system; fully coupling the fracture model (used for PHF creation and propagation) with the DDA model for fluid-leakoff simulation into the EFR and adding a proppant-transport model; and modeling the shut-in period. Finally, to ensure that model geomechanics were properly constrained, a comprehensive suite of previously gathered laboratory data was used. Laboratory-derived propped (PHF) and unpropped (EFR) fracture-permeability/conductivity data as a function of pore pressure, as well as fracture-compressibility data, were used as constraints for the model. It should be noted that our model assumes that fracture closure has no effect on the pressure/saturation of the PHF/EFR/matrix. The improved model was reapplied to the tight oil field case and yielded more realistic estimates of initial flowback conditions, enabling more confident history matching of flowback data. The results of this study will be important to those petroleum engineers interested in quantitative analysis of flowback data to accurately obtain fracture properties by ensuring proper model creation.
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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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».