Comprehensive Evaluation Method of the Tight Oil Reservoir Quality in the Ordos Basin
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Notice bibliographique
Résumé
The Wuqi area of the Ordos Basin boasts significant resource potential in the Chang 8 member of the Yanchang Formation. However, under the dual control of lithology and physical properties, reservoirs are generally dense and heterogeneous, and the quality of the oil layer changes rapidly, which brings difficulties to the optimization of favorable areas. To evaluate the reservoir quality more accurately, based on core observations, and logging and dynamic data analysis, combined with casting thin sections, scanning electron microscopy, high‐pressure mercury injection, nuclear magnetic resonance, and other related experiments, different reservoir types and characteristics were analyzed, and a comprehensive method for evaluating the reservoir quality was established. There are three types of sand body structures in the shallow‐water delta of Chang 8 in the study area, including the continuous superposition type, interval superposition type, and lateral single‐layer type. They mainly experienced diagenesis, such as compaction, cementation, and dissolution. Among these, porosity loss in the Chang 8 reservoir due to compaction and cementation reached 79.3%, consistent with trends observed in other continental tight oil plays such as the Songliao and Junggar Basins, while the improvement in physical properties due to dissolution was minimal. The main parameters influencing different reservoir types are optimized, and the comprehensive classification with the multivariate coefficient is constructed after providing coefficients with different weights. Four reservoir types are quantitatively delineated, among which the physical properties of Type I reservoirs are the best and the physical properties of Type IV reservoirs are the worst. Combined with the difference in the characteristics of sensitive logging curve responses, four logging parameters, density, neutron, resistivity, and acoustic time difference, are optimized, and different reservoir types are quantitatively identified by Fisher discriminant analysis. Comprehensively considering the change in the vertical sand body structure and reservoir type, the three key parameters of interlayer density, interlayer frequency, and reservoir thickness are selected, and the comprehensive evaluation index N of reservoir quality is innovatively constructed. The proposed evaluation index effectively decouples lithological and petrophysical variations, refining reservoir quality assessments for enhanced exploration and production strategies. The greater the N value is, the better the quality of the oil layer. The smaller the N value is, the thinner the oil layer, the more developed the interlayer, and the worse the oil layer quality. The N index exhibits a strong correlation with production characteristics, indicating that the method has effectively evaluated reservoir quality and provided a theoretical basis for targeting favorable areas.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 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 | 0,000 | 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)
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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 découle