Investigation of Cyclic Solvent Injection Process for Heavy Oil Recovery
Notice bibliographique
Résumé
Abstract This paper summarizes numerical and experimental simulation results of a cyclic solvent injection process study, which was part of a continuing investigation into the use of solvents as a follow up process in Cold Lake and Lloydminster reservoirs that have been pressure depleted by cold heavy oil production with sand (CHOPS). Typically only 5 – 10% of the original oil in place (OOIP) is recovered during cold production, so an effective follow-up process is required. The cyclic solvent injection (CSI) experiment consisted of primary production followed by 6 solvent (28% C3H8 – 72% CO2) injection cycles. Oil recovery after primary production and six solvent cycles was 50%, which indicates the potential viability of the CSI process. Concurrently with the laboratory physical simulation, a numerical simulation model was developed to represent the physical behavior of the experimental results. A history match of the primary production portion of the experiment was obtained using an Alberta Research Council foamy oil model. This resulted in the characterization (fluid saturations and pressures) of the oil sand pack at the start of the solvent injection process. The history match of the subsequent 6 solvent injection cycles was used to validate the numerical model of the CSI process developed at the Alberta Research Council. This model includes non-equilibrium rate equations that simulated the delay in solvent reaching its equilibrium concentration as it dissolves or exsolves in the oil in response to changes in the pressure and/or gas phase composition. Dissolution of CH4, C3H8, and CO2 in oil and CO2 in water were considered, as was exsolution of CH4, C3H8, and CO2 from oil and CO2 from water. Reduced gas phase permeabilities resulting from gas exsolution were also included. The history match simulations indicated that:The important mechanisms were represented in the simulationsSignificant oil swelling by solvent dissolution occurs during solvent injection periods. This can reduce solvent injectivity and penetration into a heavy oil reservoir during solvent injection periodsLow oil and gas phase relative permeabilities are required during production periods to match the experimental oil and gas production during solvent cycles A parametric simulation study showed that the quantity of gas injected in an injection period was relatively insensitive to the oil phase diffusion coefficients but was sensitive to solvent solubility in oil, dissolution rates, gas phase diffusion coefficients, molar densities in the oil phase, gas phase relative permeability, and capillary pressure. It was shown that oil production is highly dependent on how quickly solvent can dissolve in the oil during injection and exsolve from the oil during production. Introduction In Cold Lake and Lloydminster heavy oil reservoirs, cold production is used to increase heavy oil production rates by producing sand along with the oil. Sand production results in the creation of high permeability "wormholes" that enhance oil production. Following cold production, the pay zone has become a network of wormholes, which extend radially outward from production wells. During a follow-up process, these wormholes can provide reservoir access for an injection fluid such as solvent or steam.
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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 | 0,001 |
| 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 | 0,000 |
| 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 ».