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Enregistrement W2171837506 · doi:10.25560/5491

The influence of wettability and carbon dioxide injection on hydrocarbon recovery

2009· dissertation· en· W2171837506 sur OpenAlexaboutno aff
Al Sayari

Notice bibliographique

RevueSpiral (Imperial College London) · 2009
Typedissertation
Langueen
DomaineEngineering
ThématiqueEnhanced Oil Recovery Techniques
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWettingCarbon dioxideHydrocarbonPetroleum engineeringWaste managementEnvironmental scienceChemical engineeringChemistryGeologyOrganic chemistryEngineering

Résumé

récupéré en direct d'OpenAlex

This study can be divided into two sections. First, a detailed study of petrophysical properties and the impact of wettability is performed on cores from a producing heterogeneous carbonate reservoir from the Middle East. Second, a comparison between different injection schemes (waterflooding, gas injection, WAG and CO2 injection) for enhanced oil recovery is made for another giant carbonate reservoir in the Middle East. Knowledge of the wettability of a reservoir rock and its influence on petrophysical properties is a key factor for determining oil recovery mechanisms and making estimates of recovery efficiency. A full suite of experiments on well-characterised systems, including sandpacks, sandstones and carbonate cores, was performed to measure capillary pressure, relative permeability, NMR response and resistivity index. Cores aged in crude oil, with different wettability were studied. As a preliminary step to investigate the effect of wettability on heterogeneous carbonates from the Middle East, sandpack and sandstone samples were first tested because: 1) these samples are known to be quite homogeneous and of a wettability that can be controlled; 2) To test our experimental methods; and 3) to serve as a dataset for modelling studies. First, the static (porosity and permeability) and dynamic (initial water saturation and residual oil saturation) properties of Leavenseat (LV60) and Ottawa (F-42) sandpacks were measured. The formation factor and NMR response for these sandpacks were also determined. These experimental measurements have served as a benchmark for pore-modelling studies that have reproduced the experimental data. Fontainebleau sandstones have also been used as a benchmark in the industry because of its relatively simple pore structure. Mercury injection capillary pressure (MICP) measurements were performed on this sandstone. The MICP experimental measurements showed very low pore volume values, indicating very tight (consolidated) samples. These samples had a diameter of less than 0.02 m which made the experiments quite difficult. Once we had confidence in the experimental methodology, five carbonate samples from a typical Middle East reservoir were imaged and cleaned in order to render them more water wet. Conventional and special core analyses were performed on all the samples. The pore throat distribution from capillary pressure was successfully compared with the pore size distribution inferred from the NMR T2 relaxation curve. Formation resistivity factor and the formation resistivity index were also measured. Capillary pressure and relative permeability curves were measured using refined oil and synthetic formation brine. Then the samples were aged in crude oil from the same field at elevated temperature (120oC) and underwent the same experiments to evaluate the influence of wettability changes on these properties. The experimental data show that there is a significant difference in the relative permeability and capillary pressure of the cleaned and aged samples; the results are explained in terms of the pore-scale configurations of fluids. In contrast, electrical resistivity did not encounter significant changes for different wettability, suggesting that electrical properties in these carbonates are mainly affected by the porosity that remains water-wet, or is only neutrally-wet. This conclusion is supported by the significant displacement that is observed in the aged sample at capillary pressures close to zero. We show that wettability, imbibition capillary pressure and relative permeability have major impact on the waterflood sweep efficiency and hence on the distribution of remaining oil saturation. An incorrect understanding of the distribution of remaining oil saturation may lead to ineffective reservoir management and IOR/EOR decisions. The second part of this thesis is to assess the efficacy of CO2 injection into carbonate oil fields. The reservoir under study is a layered system. The reservoir consists of two main units, i.e. a lower zone of generally low permeability layers and an upper zone of high permeability layers inter-bedded with low permeability layers; the average permeability of the upper zone is some 10-100 times higher than that of the Lower zone. Under waterflooding, the injected water tends to flow through the upper zone along the high permeability layers and no or very slow cross flow of water into the lower zone occurs, resulting in very poor sweep of the lower zone. There is significant scope for improving oil recovery from such type of heterogeneous mixedwet carbonate reservoirs. The apparent impediment to water invading the bottom strata prompts suggests that a miscible fluid could be Injected into the lower zone. We conducted a series of core-flood experiments to compare the performance of different displacement process: waterflooding, hydrocarbon gas flooding and wateralternate gas (WAG) and compared them with CO2 injection. We show that the local displacement efficiency for CO2 flooding is approximately 97% - much higher than that obtained from waterflooding or hydrocarbon gas injection, due to the development of miscibility between CO2 and the oil. We use the results to discuss the potential of CO2 injection for storage and enhanced oil recovery in the Middle East carbonate reservoir discussed above, and proposes further research to develop a fuller understanding of the subsurface behavior of CO2.

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 candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,149
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
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 Opus0,004
Tête enseignante GPT0,215
Écart entre enseignants0,212 · 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.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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

En bref

Citations14
Publié2009
Routes d'admission1
Résumé présentoui

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