Experimental Study on Production Performance of Two Different Heavy Oils in Venezuela
Notice bibliographique
Résumé
Abstract Two heavy oil samples taken from different geographical areas, with high viscosities at reservoir pressure and temperature, but with similar macroscopic characteristics (API gravity, Rsi, SARA, etc), have been evaluated using a methodology developed at PDVSAIntevep to quantify the "foamy characteristics" of the system. The results show substantial differences in the production mechanisms of the two heavy oils studied, not only in terms of PVT behavior but also in terms of the production performance during core depletion tests. Introduction The term "foamy oil" refers to some heavy oil reservoirs that exhibit better than expected primary production performance during cold production under solution gas drive mechanism1. This behavior has been reported by several authors in the literature2–3, and it has also been observed in some Venezuelan heavy oil reservoirs from the Orinoco Belt (FPO) 4–6. A lot of workon the understanding of this mechanism can be found in the literature7–10. PDVSA Intevep has carried out a large number of investigations to understand foamy oil flow trough porous media and pipes. The main motivation for this research is its strategic importance for Venezuela because of the large heavy oil reserves present in the FPO7. The main goal of this paper is to show basic results of an extensive study on production performance of two heavy oils. The samples tested were extracted from different areas in Venezuela and all of the tests were conducted at reservoir pressure and temperature. BACKGROUND Heavy oil recovery using only a solution gas drive mechanism is often insufficient to obtain an economically attractive exploitation of a field. Therefore, thermal methods are usually required to produce such reservoirs. There exist field evidences of some heavy oil reservoirs in Venezuela and Canada that show an unusually good performance being produced by solution gas drive mechanism. Such reservoirs are called "foamy oil reservoirs". A possible hypothesis with regard to this unusual behavior is that solution gas, liberated under a depressurization process, remains trapped because of the high viscosity of the oil2. The conceptual difference between foamy and non foamy oil is shown in Figure 1. Only after a "long time" a phase separation between the oil and gas phase would occur. Therefore, released solution gas could be entrapped in the reservoir in foamy oil systems. Nevertheless, flow of foamy oil through porous media is currently not well understood. It is thought that its description involve mechanisms such as nucleation, growth and coalescence of gas bubbles, but their precise influences remains unclear. METODOLOGY AND BASIC CRITERIA A methodology developed at PDVSA-Intevep that consists of a combination between two types of PVT tests and porous media evaluations, allowed us to quantify foamy behavior at reservoir conditions. Bubble pressure, pseudo bubble pressure and gas-trapping factor can be calculated by comparing a conventional PVT test (with agitation) with the so-called "non-conventional" PVT test (without agitation) 8 Core depletion tests show the behavior of multiphase flow, critical gas saturation and production profiles which are very useful to understand foamy oil behavior in porous media and its relationship with the recovery factor.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».