Magnetic Core Analysis for Improved Interpretation of Geothermal Prospects
Notice bibliographique
Résumé
Locating intervals where there may be radiogenic heat sources is critically important for potential geothermal prospects. This paper details use of core magnetic techniques on rock powder samples from northern Alberta to accurately determine: (i) the depth to the Precambrian crystalline basement rocks (where most of the radiogenic heat sources are expected to reside) below the Phanerozoic sedimentary cover rocks, and characterize variations in the different lithologies, (ii) the contents and domain states of certain minerals, and (iii) the temperature dependence of magnetic properties, which can potentially be used for mineral quantification from laboratory or potential borehole magnetic measurements. The results demonstrated that rapid core magnetic susceptibility measurements correlated with borehole gamma ray results, and could arguably identify certain lithologies (such as the granitic basement samples) better than the gamma ray. Whilst small rock powder samples were only available to us in this study, the same types of magnetic measurements can be made (using different sensors in some cases) on whole core, slabbed core, core plugs, drill cuttings or rock chips. The core measurements strongly suggest the potential usefulness of a high resolution borehole magnetic susceptibility tool for the above purposes. Interestingly, the magnetic susceptibility and gamma ray results with depth indicated that the Precambrian basement rocks were more complicated than initially expected, and exhibited a large range of values.Rapid, low field magnetic susceptibility measurements using a small portable sensor were first acquired, and subsequently validated independently via magnetic hysteresis measurements using a larger, sensitive and expensive variable field translation balance (VFTB). The results demonstrated that the portable, relatively cheap sensor is potentially suitable for basic, rapid measurements. However, the VFTB had several advantages. Firstly, it enabled magnetic hysteresis and susceptibility measurements to be acquired over a range of low to high applied fields. The high field signal enables estimates of the type and contents of the diamagnetic and paramagnetic minerals to be determined. Secondly, the low field signal due to the ferrimagnetic mineral components can be extracted from the high field signal. This gives useful information on the domain state of the ferrimagnetic (generally iron oxide) carriers. Interestingly, we observed a progressive change with increasing depth from multidomain (MD) or pseudo single domain (PSD, which are essentially small MD) to stable single domain (SSD) to superparamagnetic (SP) ferrimagnetic grains. This effectively represents a change from larger to smaller ferrimagnetic grain sizes with depth, and could be a potential tool for distinguishing lithologies in future similar studies. Thirdly, the temperature dependence of the hysteresis curves and magnetic susceptibility could be measured. This information can be used to improve predictions of the contents of the diamagnetic, paramagnetic and ferrimagnetic minerals from laboratory measurements, or from in-situ borehole magnetic susceptibility data (since temperature varies with depth in a borehole).
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 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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».