Reservoir Characterization and Modeling of Potash Mine Injection Wells in Saskatchewan
Notice bibliographique
Résumé
In the Saskatchewan potash mining industry vast quantities of brine wastewater are generated from potash processing and mine inflow water. As treatment of such waste is prohibitively expensive, disposal in deep saline aquifers is the only readily available option. However, the effects that such injection activities have on the subsurface conditions of the targeted aquifers are not well known. Additionally, the reservoir characteristics of the targeted aquifers are not well understood. The aim of my dissertation is to provide a large scale reservoir characterization study to the aquifers used for subsurface waste disposal at the potash mines in Saskatchewan, the basal clastics and the Interlake Group. The second aim of this research is to use the data from the reservoir characterization study to build analytical models of the injection wells in order to study the effects that such injection activities have had on the targeted aquifers. Characterizing deep aquifers such as the basal clastics and the Interlake Group is often difficult due to limited subsurface information available at great depths. In this investigation, available information from oil and gas exploration and development, such as geophysical logs, drill stem tests and core analysis provided valuable information on the subsurface distribution and rock characteristics (permeability) of these formations. This information allowed for a better understanding of the factors that have led to the success of injection activities at the potash mine sites and will assist future projects targeting fluid injection in the basal clastics and the Interlake Group. Through this analysis, it was found that there are great differences in the permeabilities both spatially and with respect to lithology in these aquifers, with permeability values in the Winnipeg Formation between 10-18.1-10-11.8 m2 and 10-15.9-10-11.6 m2 in the Deadwood Formation and 10-16.0-10-11.5 in the Interlake Group obtained from the various methods of analysis. Through the information gained through the reservoir characterization study, analytical models were generated in Aqtesolv (HydroSOLVE Inc. 2016) in order to simulate the reservoir response to the injection activities. History-matching was conducted in order to generate models with simulation outputs that most closely matched the falloff test pressure data. The calibrated history-matched models were able to provide insights into the pressure response as well as the extent of the pressure propagations in the aquifers. It was found some of the potash mine sites have generated significantly higher pressure responses than others and that the injection rates and aquifer permeability played a significant role in the pressure response at each mine site.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».