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Enregistrement W3125165607 · doi:10.48336/k12c-dq48

Investigating modelling and inversion techniques for overburden stripping for uranium exploration in the Athabasca Basin, Canada

2020· dissertation· en· W3125165607 sur OpenAlexaffabout
Mehrdad Darijani

Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2020
Typedissertation
Langueen
DomaineEarth and Planetary Sciences
ThématiqueSeismic Imaging and Inversion Techniques
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésOverburdenGeologyStructural basinInversion (geology)UraniumSeismic refractionGeophysicsMining engineeringGeomorphology

Résumé

récupéré en direct d'OpenAlex

The major investment in exploration for uranium in Canada is in one of the most important structural corridors of the eastern Athabasca Basin, extending from the Millennium deposit to the McArthur River deposit (called the McArthur-Millennium corridor). This corridor hosts the largest and highest-grade uranium deposits in the world (at a depth of more than 500 m), and it will be the focus of exploration activity by companies (e.g., Cameco) in the Athabasca Basin for many years. In the McArthur-Millennium corridor, people have wondered about how to better detect structures (e.g., alteration zones) associated with the (volumetrically) small uranium mineralization at depth using geophysical methods. But the geophysical responses (e.g., the gravity response) of these structures can be masked by the variation of the overburden thicknesses. Some geophysical attempts have been made to remove the overburden signature and to find the alteration zones, but none of them have got very far. To solve this problem, I investigate developing new methodology as well as new exploration methods in the region to find and remove the overburden signature to explore for new deposits. In this dissertation, I investigate new ways to separate the overburden contribution from geophysical data (via modelling and inversion) so that deeper targets (e.g. an alteration zone) can be detected and delineated by means of an innovative application of new, modern, state-of-the-art modelling and (constrained and joint) inversion of geophysical methods such as seismic refraction, gravity, magnetic and electromagnetic methods. These new methods and investigations (e.g., modelling and constrained joint inversions using the fuzzy c-mean method on tetrahedral meshes) bring us much closer to solving the problem in this corridor. This research project is a part of the CMIC Footprints project, and is a very challenging exploration problem and very useful if successful for many places in Canada, not just the Athabasca Basin and uranium exploration. The Athabasca Basin is a Proterozoic sedimentary basin which supplies around 20% of the world's uranium. The uranium deposits are surrounded by alteration zones near the unconformity between Proterozoic sedimentary rocks and the Archean and Aphebian metamorphic basement. The sedimentary rocks are covered by Quaternary glacial deposits. Because of the small size of uranium deposits and their location at depth, geophysical methods look for structures which host the uranium deposits, for example, electromagnetic (EM) methods can locate graphitic faults. The gravity method can potentially detect the alteration zones. The seismic method can image the unconformity and basement faults. And, magnetic data can delineate basement structures. The benefit of using multiple datatypes can provide complementary information (e.g. the seismic and gravity). These methods can be used for the overburden stripping as well. In the Athabasca Basin, overburden can be conductive while density and seismic velocity of the overburden is less than the sandstone. Some rocks in unconsolidated glacial deposits have magnetic susceptibilities (e.g. granite), whereas sandstone is non-magnetic. Based on these features, the synthetic modelling and inversion of the geophysical data are performed for (mainly) the overburden characterization as well as reconstructing the geological structure in depth. Magnetic, gravity, first-arrival seismic traveltimes and time- and frequency-domain electromagnetic data are synthetized using forward modelling of 2D and 3D models. For inversion methods, independent, joint and constrained methods are applied for 1D, 2D and 3D cases. Independent inversions of the seismic refraction data as well as the electromagnetic data are useful methods for reconstructing the base of the overburden, unlike the independent inversions of gravity and magnetic data. The joint inversion of gravity and seismic refraction data is able well to reconstruct the variable thickness of the overburden better and sharper than the independent inversions. After applying the thickness of the overburden (obtained from the joint inversion) in the constrained independent inversion of gravity data, the location of alteration zone is apparent at depths. The joint inversion of magnetic and gravity data was able to reconstruct the basement blocks, the sandstone and the unconformity; furthermore the base of overburden can be detected after using the constrained joint inversion of magnetic and gravity methods. This method cannot show the alteration zone, but it can show the intersection of the fault with the unconformity where the mineralization can occur. For the electromagnetic method, results show that frequency and time-domain methods can be used for determining the location of the interface between overburden and sandstone and the location of the graphitic faults, respectively.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,469
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,045
Tête enseignante GPT0,248
Écart entre enseignants0,203 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2020
Routes d'admission2
Résumé présentoui

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