Evaluation of Produced Hydrocarbons Composition During Cyclic CO2 Injection (Huff-N-Puff) in Artificially-Fractured Shale Core Sample
Notice bibliographique
Résumé
Abstract Natural and hydraulic fractures are important contributors to production performance of low-permeability (‘tight’) hydrocarbon reservoirs during primary and enhanced oil recovery. Laboratory studies that have investigated core-scale huff-n-puff (HNP) processes in ‘fractured’ cores are rare, and focused on ‘rock’ analysis primarily, as opposed to ‘fluid’ analysis. The objective of this proof-of-concept experimental study is to evaluate the application of a new core-scale HNP technique, ‘flow-through-frac’, for tracking compositional evolution of produced liquid hydrocarbons during cyclic gas (CO2 herein) injection in ‘fractured’ low-permeability oil reservoirs. The flow-through-frac technique reproduces the near-fracture conditions during a typical HNP process, with significantly faster testing times (25-50%) compared to conventional techniques (e.g., flow-around). The experimental procedure includes: 1) artificially fracturing core plug sample under differential stress to simulate an induced fracture, 2) saturating the fractured core with de-waxed in-situ (formation) oil, and 3) implementing multiple cycles of gas (e.g., CO2, produced gas) injection, soaking and production. To determine whether this technique can detect compositional variations despite its short duration, the compositions of the original in-situ (dead) oil and produced liquid hydrocarbon sample were compared after a typical core-scale HNP process (4 cycles) using CO2. A low-porosity (3.3%), low-permeability (1.25·10−4 md) Duvernay shale (western Canada) core plug sample was analyzed in this study. Compared to the in-situ (dead) oil, lighter components (C7-C11) were significantly (up to an order of magnitude) leaner in the oil sample produced after 4 cycles of CO2 HNP (fractured core plug). The lighter the hydrocarbon components, the leaner the concentrations in the produced oil. The intermediate components (C12-C28) were enriched in the produced oil, with larger discrepancies for C14-C22 components. The latter observation is attributed to the replacement of adsorbed C17-C19 components by injected CO2, in agreement with recent molecular simulation and experimental studies. The concentrations of heavier components (C29-C33) were similar between the in-situ and produced oil samples. Through combining core-scale CO2 HNP and fluid sampling/testing, this work demonstrates that the flow-through-fracture method can detect compositional variations during a typical core-scale HNP experiment. This technique can enable operators to track the composition of produced hydrocarbons at near-fracture conditions at a significantly shorter time frame (25–50%) than the existing methods. This integrated rock and fluid experimental program could potentially become valuable to not only core-based evaluation of enhanced oil recovery (EOR) in unconventional oil reservoirs but also potentially coupled CO2/produced gas EOR and sequestration processes in fractured shale reservoirs.
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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 | 0,000 |
| 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 ».