Multiscale Pore-Structure Characterization by Combining Image Analysis and Mercury Porosimetry
Notice bibliographique
Résumé
Multiscale Pore-Structure Characterization by Combining Image Analysis and Mercury Porosimetry H. Han; H. Han U. of Waterloo Search for other works by this author on: This Site Google Scholar M. Ioannidis; M. Ioannidis U. of Waterloo Search for other works by this author on: This Site Google Scholar M. B. Dusseault; M. B. Dusseault U. of Waterloo Search for other works by this author on: This Site Google Scholar B. Xu B. Xu U. of Waterloo Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, June 2006. Paper Number: SPE-100353-MS https://doi.org/10.2118/100353-MS Published: June 12 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Han, H., Ioannidis, M., Dusseault, M. B., and B. Xu. "Multiscale Pore-Structure Characterization by Combining Image Analysis and Mercury Porosimetry." Paper presented at the SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, June 2006. doi: https://doi.org/10.2118/100353-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Europec featured at EAGE Conference and Exhibition Search Advanced Search Abstract This article introduces a multiscale pore structure characterization method using a combination of mercury porosimetry and image analysis. The method was used to determine the distribution of pore volume by pore size and to estimate the pore-to-throat size aspect ratio. The key idea of the method is that pore size distribution obeys a fractal scaling law over a range of pore size. On this basis, scattering intensity data computed from the measured two-point correlation function and those measured from mercury porosimetry are extrapolated in the size range 0.01 μm < r < 1000 μm, using the known fractal scaling law.A set of siltstone samples taken from Daqing Oilfield was analyzed through this method. Distribution of pore volume by pore size over the entire range of pore length scales was determined. The results demonstrated significant similarities in the pore structure of all samples. The image analysis results were in qualitative agreement with the results of mercury intrusion/extrusion tests.The results were also compared with some other samples (including siltstone, sandstone, and dolomite) that had been analyzed using similar methods. It is shown that the surface fractal dimension obtained by analysis of MIP data is consistent with the value obtained by image analysis for different samples with different porosity and permeability.Novel information on the pore-to-throat aspect ratio is obtained by comparing the complete pore volume distribution (PVD) to the MIP data. Keywords: Artificial Intelligence, Reservoir Characterization, Fluid Dynamics, pore structure, Upstream Oil & Gas, porosity, surface fractal dimension, mip data, length scale, information Subjects: Reservoir Characterization, Reservoir Fluid Dynamics, Formation Evaluation & Management, Information Management and Systems, Flow in porous media, Artificial intelligence Copyright 2006, Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».