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Enregistrement W2157024312 · doi:10.2172/950783

Application of Time-Lapse Seismic Monitoring for the Control and Optimization of CO2 Enhanced Oil Recovery Operations

2008· report· en· W2157024312 sur OpenAlexaboutno aff
Brian Toelle

Notice bibliographique

Revuenon disponible
Typereport
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensnon disponible
Organismes subventionnairesU.S. Department of Energy
Mots-clésEnhanced oil recoveryReefCarbonateGeologyOil fieldPetroleum engineeringWell controlSeismologyDrillingOceanographyEngineering

Résumé

récupéré en direct d'OpenAlex

This project, 'Application of Time-Lapse Seismic Monitoring for the Control and Optimization of CO{sub 2} Enhanced Oil Recovery Operations', investigated the potential for monitoring CO{sub 2} floods in carbonate reservoirs through the use of standard p-wave seismic data. This primarily involved the use of 4D seismic (time lapse seismic) in an attempt to observe and map the movement of the injected CO{sub 2} through a carbonate reservoir. The differences between certain seismic attributes, such as amplitude, were used for this purpose. This technique has recently been shown to be effective in CO{sub 2} monitoring in Enhanced Oil Recovery (EOR) projects, such as Weyborne. This study was conducted in the Charlton 30/31 field in the northern Michigan Basin, which is a Silurian pinnacle reef that completed its primary production in 1997 and was scheduled for enhanced oil recovery using injected CO{sub 2}. Prior to injection an initial 'Base' 3D survey was obtained over the field and was then processed and interpreted. CO{sub 2} injection within the main portion of the reef was conducted intermittently during 13 months starting in August 2005. During this time, 29,000 tons of CO{sub 2} was injected into the Guelph formation, historically known as the Niagaran Brown formation. By September 2006, the reservoir pressure within the reef had risen to approximately 2000 lbs and oil and water production from the one producing well within the field had increased significantly. The determination of the reservoir's porosity distribution, a critical aspect of reservoir characterization and simulation, proved to be a significant portion of this project. In order to relate the differences observed between the seismic attributes seen on the multiple 3D seismic surveys and the actual location of the CO{sub 2}, a predictive reservoir simulation model was developed based on seismic attributes obtained from the base 3D seismic survey and available well data. This simulation predicted that the CO{sub 2} injected into the reef would remain in the northern portion of the field. Two new wells, the State Charlton 4-30 and the Larsen 3-31, were drilled into the field in 2006 and 2008 respectively and supported this assessment. A second (or 'Monitor') 3D seismic survey was acquired during September 2007 over most of the field and duplicated the first (Base) survey, as much as possible. However, as the simulation and new well data available at that time indicated that the CO{sub 2} was concentrated in the northern portion of the field, the second seismic survey was not acquired over the extreme southern end of the area covered by the original (or Base) 3D survey. Basic processing was performed on the second 3D seismic survey and, finally, 4D processing methods were applied to both the Base and the Monitor surveys. In addition to this 3D data, a shear wave seismic data set was obtained at the same time. Interpretation of the 4D seismic data indicated that a significant amplitude change, not attributable to differences in acquisition or processing, existed at the locations within the reef predicted by the reservoir simulation. The reservoir simulation was based on the porosity distribution obtained from seismic attributes from the Base 3D survey. Using this validated reservoir simulation the location of oil within the reef at the time the Monitor survey was obtained and recommendations made for the drilling of additional EOR wells. The economic impact of this project has been estimated in terms of both enhanced oil recovery and CO{sub 2} sequestration potential. In the northern Michigan Basin alone, the Niagaran reef play is comprised of over 700 Niagaran reefs with reservoirs already depleted by primary production. Potentially there is over 1 billion bbls of oil (original oil in place minus primary recovery) remains in the reefs in Michigan, much of which could be more efficiently mobilized utilizing techniques similar to those employed in this study.

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 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: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,607
Score d'incertitude au seuil0,569

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 Opus0,017
Tête enseignante GPT0,279
Écart entre enseignants0,262 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2008
Routes d'admission1
Résumé présentoui

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