Production Fractionation and Efficiency Indicators from Phase Snapshots
Notice bibliographique
Résumé
Petroleum produced from low permeability shales is different to the dispersed in-situ fluids from which it is derived. Whereas in-situ fluids consist of hydrocarbons, resins and asphaltenes in proportions governed by organic matter type, maturity and retention behaviour, the produced fluids are highly enriched in hydrocarbons and low polarity non-hydrocarbons, and show an enhanced GOR. Here, we study the effects of fractionation during production from Permian and Cretaceous shales using laboratory experiments, PVT-modeling and a regional PVT database. Our goal was to develop methodologies for predicting yields and compositions of produced fluids ahead of drilling. Target wells with known fluid properties were used for calibration. Shales from neighbouring wells of slightly lower maturity were mildly matured to that of the calibration well using MSSV pyrolysis, and a PhaseSnapShot of the resultant fluid made using PVTsim. The first example, from the late oil window Eagle Ford, demonstrates that both kerogen and bitumen are important petroleum precursors, and that in-situ compositions are largely determined by the most recently generated charge, rather than by cumulative addition during maturation. The PVT model, calibrated to the engineering report of the target well and its environs, reveals that a high proportion of the in-place C7+ fluids remain in the rock matrix relative to gas during production. The second example, taken from a gas and condensate fairway in the Permian Basin, shows that the predicted bulk composition of recently generated petroleum is facies dependent. PVT fluid calibrations have low Psat and low cricondentherms. These characteristics are reproduced by experiment, but only for those zones containing low contents of high molecular weight liquids. Any contributions to produced fluids from other zones is associated with massive retention of high molecular weight organics. The third example concerns volatile oil production from wells in the Permian Basin. The MSSV products generated by adjacent lower maturity shales exhibited phase envelopes with higher cricondentherms than that of the calibration, this being attributable to a molecular weight difference in heavy components. Adjusting the MW from 249 (measured) to 222 (produced oil PVT value) in the PVTsim model aligned the cricondentherms. This tuning step corresponds to the preferential retention of heavy polar compounds in the rock matrix during production. In a second step, 20% of the tuned MSSV-generated liquids are considered to be retained in the rock, thereby raising Psat. The result is an excellent match between the doubly tuned predicted phase envelope and that of the produced fluid. The preferential retention of polar compounds is also in line with this tuning step. In summary, fractionation is part and parcel of production from shales. Up to 80% liquids retention relative to gas has been demonstrated. Production efficiency assessments are readily inferred from these data. The extent to which fractionation occurs varies a lot, and has here been assessed by combining experimental rock geochemistry with PVT modeling (PhaseSnapShots), and using PVT reports on produced fluids for calibration.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| 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 ».