Top-of-holes sensing techniques: developments within Deep Exploration Technologies Cooperative Research Centre
Notice bibliographique
Résumé
In this paper, we summarise advancements in top-of-hole sensing achieved within the Deep Exploration Technologies Cooperative Research Centre (DET CRC). It was demonstrated that the drill fines, which were previously discarded, show high potential to act as a representative sample media of the lithologies intersected by the drill hole and can be successfully used for analysis in real time. The Lab-at-Rig® (LAR®) system was developed for prospecting rigs (diamond drilling in the first instance and coil tube drilling in the future) and encompasses sample capture, sample preparation and presentation to sensors. In the initial setup of the LAR platform, there are two sensors, a portable X-ray fluorescence (pXRF) and a portable X-ray diffraction, capable of delivering chemical and mineralogical data in near real time. Laser-induced breakdown spectroscopy was also explored as a potential additional sensor for future versions of the LAR system, as it can yield information on elemental composition including essential light elements not currently measured by air-based pXRF detectors (e.g. Li, Na and Mg at low levels) or other elements problematic by pXRF (e.g. Au). The LAR system implements X-ray diffraction (XRD) analysis from which mineralogical data (mineral identification and most importantly mineral quantification) must be obtained in near real time. The existing challenge with XRD is that any data processing and especially data interpretation with available software packages requires some expertise in the field and background in crystallography and is time-consuming. Hence, SwiftMin®, the world’s first algorithm for automated processing of XRD data, was developed. It provides mineral identification and quantification and performs all calculations and processing independent from a user. SwiftMin returns a result in seconds and is able to batch process hundreds of XRD patterns in a matter of minutes. The above means, that SwiftMin is a technology that allows processing of large amount of XRD data quickly, saving time, costs and labour. The overall concept and vision developed within the DET CRC in top-of-hole sensing by coupling chemical and mineralogical analyses of drilling materials is to provide an end-to-end solution that supports rapid decision making by a geologist, at the time-scale of drilling the hole.KEY POINTSLab-at-Rig® workflow results in geochemical and mineralogical analyses by the time the drill hole is completed, providing objective logging and an opportunity to make important decisions during the course of a drilling campaign.SwiftMin® capability to process the data quickly and with no user interaction will allow X-ray diffraction to become a routine and cost-effective technique for analysis of geological materials.Finally, while laser-induced breakdown spectroscopy results look promising, particularly for such elements as Na, Mg and Au, application of laser-induced breakdown spectroscopy for rapid, on-site analysis of geological materials requires some further research, above all on how to minimise the ‘matrix effects’.
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Comment cette classification a été obtenuedéplier
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 | 0,001 | 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 ».