Integrated reservoir characterization and simulation studies in stripper oil and gas fields
Notice bibliographique
Résumé
The demand for oil and gas is increasing yearly, whereas proven oil and gas\nreserves are being depleted. The potential of stripper oil and gas fields to supplement the\nnational energy supply is large. In 2006, stripper wells accounted for 15% and 8% of US\noil and gas production, respectively. With increasing energy demand and current high oil\nand gas prices, integrated reservoir studies, secondary and tertiary recovery methods,\nand infill drilling are becoming more common as operators strive to increase recovery\nfrom stripper oil and gas fields. The primary objective of this research was to support\noptimized production of oil and gas from stripper well fields by evaluating one stripper\ngas field and one stripper oil field.\nFor the stripper gas field, I integrated geologic and engineering data to build a\ndetailed reservoir characterization model of the Second White Specks (SSPK) reservoir\nin Garden Plains field, Alberta, Canada. The objectives of this model were to provide\ninsights to controls on gas production and to validate a simulation-based method of infill\ndrilling assessment. SSPK was subdivided into Units A ? D using well-log facies. Units A and B are the main producing units. Unit A has better reservoir quality and\nlateral continuity than Unit B. Gas production is related primarily to porosity-netthickness\nproduct and permeability and secondarily to structural position, minor\nstructural features, and initial reservoir pressure.\nFor the stripper oil field, I evaluated the Green River formation in the Wells\nDraw area of Monument Butte field, Utah, to determine interwell connectivity and to\nassess optimal recovery strategies. A 3D geostatistical model was built, and geological\nrealizations were ranked using production history matching with streamline simulation.\nInterwell connectivity was demonstrated for only major sands and it increases as well\nspacing decreases. Overall connectivity is low for the 22 reservoir zones in the study\narea. A water-flood-only strategy provides more oil recovery than a primary-then-waterflood\nstrategy over the life of the field. For new development areas, water flooding or\nconverting producers to injectors should start within 6 months of initial production. Infill\ndrilling may effectively produce unswept oil and double oil recovery. CO2 injection is\nmuch more efficient than N2 and CH4 injection. Water-alternating-CO2 injection is\nsuperior to continuous CO2 injection in oil recovery.\nThe results of this study can be used to optimize production from Garden Plains\nand Monument Butte fields. Moreover, these results should be applicable to similar\nstripper gas and oil field fields. Together, the two studies demonstrate the utility of\nintegrated reservoir studies (from geology to engineering) for improving oil and gas\nrecovery.
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Comment cette classification a été obtenuedéplier
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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».