Assessing the Water Uptake of Alberta Coal and the Impact of CO2 Injection With Low-field NMR
Notice bibliographique
Résumé
Abstract Coal property characterization is an essential step to develop Coalbed Methane (CBM) recovery processes. Coal contains free water in the cleats as well as moisture that forms an integral part of the coal structure. Most CBM production starts with dewatering coalbeds to initialize the gas recovery. Therefore, the wetting behavior of coal by water is an important aspect in coal property studies. As CO2 has a strong affinity to coal, CO2 injection may change the coal wetting behavior during a so-called Enhanced Coalbed Methane process (ECBM). Studies on coal wettability are rare. This paper investigates the water uptake by the Alberta coal and its wettability alteration due to CO2 injection using low-field nuclear magnetic resonance (NMR). Low-field NMR is a technique used in logging and in the analysis of fluids contained in reservoir rocks. It measures the hydrogen density in reservoir fluids and distinguishes between " free" bulk water and " bound" surface water. CO2 is invisible by NMR, but its impact can be detected by changes in the water signal. Experiments on coal samples in the form of dry and moist powder and chunk are used. The water uptake rate can be shown by monitoring the geometrical mean transverse relaxation time. From the spectra of different coal samples, water can be characterized into free, capillary-bound and subsurface-bound (adsorbed) water. These forms of water have different uptake behavior inside coal. The injection of CO2 will cause coal de-watering, and the effect is increasing with elevated CO2 pressure. Introduction Coalbed methane (CBM) has evolved into a commercially profitable source of unconventional natural gas. Canada has vast resources of coal and it has been estimated that the total inplace reserves are 36×1012 m3. Over 60% of Canada's CBM resource is in Alberta (1). Coalbed methane has the potential of contributing a significant portion of Canadian natural gas production in the foreseen future. Using CO2 to enhance the methane recovery has been discussed by several researchers (2,3). This process is called CO2-ECBM. If successful, its implications include CO2 sequestration in deep unmineable coalbeds. Coal property characterization is an essential step to develop CBM/ECBM recovery processes. Coal contains free water in the cleats as well as moisture that forms an integral part of the coal structure. Most CBM production starts with dewatering coalbeds to initialize the gas recovery. Therefore, the wetting behavior of coal by water is an important aspect in coal property studies. As CO2 has a strong affinity to coal, CO2 injection may change the coal wetting behavior in the ECBM process. Published studies on coal wettability are very rare to the best of our knowledge. Low-field NMR is a relatively new technique used in logging and in the analysis of fluids contained in reservoir rocks. Nuclear magnetic resonance occurs when the nuclei of certain atoms (i.e. hydrogen proton) are immersed in a static magnetic field and exposed to a second oscillating magnetic field (4). NMR provides a non-destructive analytical method of detecting hydrocarbons in reservoirs (5), and characterizing the hydrocarbon gas (6).
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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 | 0,000 |
| 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) | 0,001 | 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 ».