Classification and Evaluation of Microscopic Pore Structure in Carbonate Rocks by Integrating MICP-Based Dynamic Information
Notice bibliographique
Résumé
Abstract In carbonate reservoirs, the establishment of a coherent correlation between petrophysical static rock type (PSRT) and petrophysical dynamic rock type (PDRT) schemes poses a formidable challenge due to its petrophysical complexity. Additionally, the interpretation of the dynamic properties of microscopic pore structure (MPS) based on mercury injection capillary pressure (MICP) data has been an issue. The objective of this study is to alleviate the divergence in flow properties in MPS classification and evaluate the oil recovery potential of different MPS quantitatively based on MICP. A total of 76 core plugs without fractures were studied from the Middle East region. The data set available included helium porosity, gas permeability and high-pressure mercury injection. MPSs were qualitatively classified according to the morphological characteristics of the MICP data correlated oil recovery potential. Unsteady-state oil-water relative permeability tests were subsequently conducted to ensure the effectiveness of the classification. Sensitivity parameters were correlated with the efficiency of mercury withdrawal and condensed with the factor analysis (FA) method. After dimensionality reduction, interpretable general factors were obtained to quantitatively characterize the oil recovery potential of MPS and to establish a core quality evaluation model from a dynamic view. Results showed that the proposed classification can maintain the consistency of dynamic attributes in five qualitative categories and significant differences were observed among the different MPSs. A total of five sensitivity parameters were screened to quantitatively characterize the oil recovery potential of MPS. Moreover, FA defines three aspects that affect the ability to oil recovery: sweep, displacement, and storage. The relative relationship between the MPS and oil recovery potential predicted by the evaluation model and the laboratory-measured oil recovery are in general agreement, and this relative relationship can evaluate the oil recovery potential based on the MPS without the laboratory-measured oil recovery. This work presents a qualitative classification method for reducing the discrepancy between PSRT and PDRT. The proposed quantitative evaluation model provides new insights into the effects of MPS on fluid flow. Both of them can improve the screening of representative samples for special core analysis and accurate numerical simulation of carbonate reservoirs.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
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 | 0,000 | 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) | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».