Determination of Production Operation Methods in Naturally Fractured Reservoirs
Notice bibliographique
Résumé
Abstract There are many naturally fractured reservoirs in the world, but few of them are optimally developed. In fact, it is difficult to characterize the naturally fractured reservoirs and predict the oil production, needless to mention the determination of appropriate production operation methods (POMs). Although there have been some formulas for evaluating well performance, a few were derived on the basis of production test data. In this paper, several general formulas are developed for evaluating inflow performance of both vertical wells and horizontal wells, based on the production test data obtained from three naturally fractured reservoirs. The influence of rock compaction and the inertial flow resistance in naturally fractured reservoirs are considered in these equations. Furthermore, theoretical models are also presented, into which reservoir engineering, production performance and surface facility performance are incorporated. These models are then applied to evaluate and determine the oil well POMs for two naturally fractured reservoirs. It has been shown from these two field applications that stable flowing performance, including its ceasing conditions, can be predicted. And artificial lift methods such as sucker-rod pumping can be efficient under certain reservoir conditions. The detailed field application results indicate that most of POMs determined from the theoretical models are technically feasible and economically viable. Introduction Naturally fractured reservoirs are found in all types of lithologies and throughout the geological stratigraphic columns. However, initial high oil rates have misled engineers in many instances to overestimate production forecasts of wells. Thus development of the naturally fractured reservoirs results in numerous economic failures(1). Meanwhile, field practices show that selection of appropriate production operation methods (POMs) is critical to the long-term profitability of most producing wells(2–8). An improper choice can not only substantially reduce production but also greatly increase operating costs. Once a type of POM has been determined to install on a producing well, usually the POM is unchanged, whether it was and still is the optimal choice under existing conditions. Therefore, It is essential that both accurate prediction of well inflow performance and appropriate selection of POMs be of great benefit to the optimal development of the naturally fractured reservoirs. In general, it is difficult to characterize the naturally fractured reservoirs, predict the oil production and further determine suitable POMs. The well inflow performance relationship (IPR), which represents the well's ability to produce fluids, is the first component to be considered in the process of selecting POMs(9). In the literature, although there have been some formulas for evaluating well performance, few were derived on the basis of production test data. Gubkina(10) presented a formula for evaluating vertical well inflow performance in the naturally fractured reservoirs, which was later improved by Bacnev et al.(11). However, the effect of well completeness on well inflow performance was not accounted for. To evaluate the horizontal well inflow performance in naturally fractured reservoirs, Joshi's formula(12) is modified to achieve better forecasts(13,14).
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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 | 0,001 | 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) | 0,000 | 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.
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