MétaCan
Menu
Retour à la cohorte
Enregistrement W4223893685 · doi:10.2118/209348-ms

Laboratory Analyses and Compositional Simulation of the Eagle Ford and Wolfcamp Shales: A Novel Shale Oil EOR Process

2022· article· en· W4223893685 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueSPE Improved Oil Recovery Conference · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueHydrocarbon exploration and reservoir analysis
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésOil shaleGeologyCalcitePropanePetrophysicsEnhanced oil recoveryNatural gasCarbon dioxidePetroleum engineeringPorosityMineralogyChemistryGeotechnical engineeringOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Cyclic injection-flowback (huff and puff, HnP) of natural gas or carbon dioxide has been shown to improve the recovery of oil from low permeability, low porosity shale reservoirs. However, natural gas and carbon dioxide are limited in effectiveness and utility; natural gas has a high miscibility pressure and high mobility and hence potential for leak-off and inter-well communication; carbon dioxide is not readily available, is costly, and corrosive. In this study, a novel shale oil HnP EOR process, utilising a liquid solvent comprised of mixtures of propane and butane (C3 and C4), referred to as SuperEORTM (Downey et al, 2021), was evaluated for its efficacy in recovering oil compared to methane and carbon dioxide. The advantages of the propane and butane solvent are its low miscibility pressure with the produced oil, it is injected as a liquid, and is easy to separate and recycle. In this study, an Eagle Ford shale core with produced Eagle Ford oil and a Permian Wolfcamp shale core with produced Wolfcamp oil were investigated. PVT and minimum miscibility tests of the fluids were combined with petrophysical analysis to design laboratory tests and provide metrics for tuning a compositional model. Two Eagle Ford facies were investigated, a calcite/quartz-rich mudstone/siltstone with a porosity of up to 10% and a calcite-rich limestone with porosity ranging from 3% to 6%. At reservoir stress, the matrix permeability averages about 2E-4 md. One facies of the Wolfcamp shale was tested, which is 80% quartz, has a porosity of about 7-11%, and average matrix permeability of 9E-3 md. SuperEOR was carried out on core plugs re-saturated with produced oil for 16 days at reservoir conditions of 5000 psi at 101°C for the Eagle Ford and 79°C for the Wolfcamp. For the Eagle Ford shale, five to 6 HnP cycles using a 1:1 ratio of C3 and C4, at injection pressures of 5000 and 3000 psi, with 20 hours of soaking per cycle, yielded a recovery of 55% to 75% of the original oil in place (OOIP) for the lower porosity facies and over 80% for the higher porosity facies of the Eagle Ford. For the Wolfcamp shale, at an injection pressure of 3000 psi, 85% of the original oil in place was recovered using 1:1 ratio of C3 and C4. In comparison, the Wolfcamp shale, at similar experiment conditions and number of HnP cycles, yielded about 30% of the OOIP when methane was used as an injectant/solvent and yielded 75% of OOIP when carbon dioxide was used. The efficacy of the HnP process on the Eagle Ford shale at the core scale was investigated through reservoir modelling using a general equation-of-state compositional simulator and the results were compared to the laboratory data and a field scale EOR simulation on three horizontal wells using carbon dioxide, methane, and the C3:C4 solvent. The wells had a production rate of <3 bbl/day prior to shut-in and responded poorly to natural gas HnP EOR due to excessive leak-off. The HnP simulations comprise cycling 23 days of injection followed by 30 days of production for 17 years. The recovery utilising methane is 45%, carbon dioxide 72%, and 90% with the C3:C4 solvent for the field simulation, which are generally similar to the laboratory tests and the core simulation.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,243
Score d'incertitude au seuil0,497

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,027
Tête enseignante GPT0,268
Écart entre enseignants0,241 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle