Modelling of Production and Fiber Optic Data for Analyzing Inter-Well Interactions in Fractured Shale Gas Reservoir
Notice bibliographique
Résumé
Abstract Fiber optic techniques, including Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS), enable real-time monitoring and interpreting of fracture hits, stress shadowing, and production behavior. However, integrating field DTS/DAS data and production responses remains challenging. This work uses numerical simulation to model fracture propagation, stress evolution, and fluid production in a shale reservoir. The capability of the numerical model to address these coupled flow-geomechanical issues is systematically evaluated. The simulation responses are analyzed to understand various observations extracted from some field DTS/DAS data. While previous coupled flow-geomechanical simulation studies have compared their numerical results of fracture hits to DAS responses, few studies have examined how the observed fracture interference would affect the fracture development and production performance of other nearby well drilled subsequently (e.g., child well). There are even fewer attempts to incorporate DTS data when analyzing the production performance of these offset wells. Detailed mechanistic models are constructed to simulate various fracture hits and crossflow scenarios. 3D thermal flow models with wellbore modelling are coupled with geomechanical calculations. Multi-scale fracture responses are modelled, e.g., physical opening/closure of hydraulic fractures (HF), induced secondary fractures, and pre-existing natural fractures. A commercial simulator is used, a systematic examination of most available model setup options was performed to achieve the most accurate responses in the flow-geomechanical simulations. Two novel features are added: first, the apparent permeability of the matrix is updated based on pore pressure to capture the effects of nano-scale flow behaviors; next, natural fracture properties are updated based on the computed stress, capturing their closure/dilation. Several field cases based on the Montney Formation are replicated. Simulated strain rate and temperature responses are compared to field DAS/DTS and production data provided by an industrial partner. Simulation results reveal that while fracture hits and stress shadowing hinder the development of adjacent new fractures, they also boost the production of nearby stages, especially in the early phases. Frac hits lead to slower cooling during injection and faster warm-back during shut-in and flowback near the wellbore; they additionally induce unforeseen temperature reductions in areas devoid of any newly stimulated fractures, this demonstrates that DTS can detect the effects of fracture hits and crossflows in real time during treatment. These effects intensify with closer proximity but diminish with higher intensity of frac hits. For the first time, optimal model configurations have been introduced that are designed for deployment within the commercial software package to achieve precise simulations of the hydraulic fracturing process. A quantitative framework is presented for correlating simulation responses with DAS/DTS data. This type of analysis is useful for a variety of geological energy applications. The results highlight the sensitivity of downhole temperature, strain/stress and production responses to treatment-monitor well interactions. Different scenarios are simulated and compared with field data. The findings provide valuable insights for using real-time DTS/DAS data from the field in fracture hit and fracture diagnosis and production data analysis.
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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 | 0,000 | 0,001 |
| 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 | 0,001 | 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 ».