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GEOPHYSICAL PROCESSING AND INTERPRETATION WITH GEOLOGIC CONTROLS: EXAMPLES FROM THE BATHURST MINING CAMP

2013· dissertation· en· W609438450 sur OpenAlex

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Notice bibliographique

RevueMacSphere (McMaster University) · 2013
Typedissertation
Langueen
DomaineEngineering
ThématiqueMining Techniques and Economics
Établissements canadiensnon disponible
Organismes subventionnairesNatural Resources Canada
Mots-clésInterpretation (philosophy)GeologyGeophysicsMining engineeringComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

With an ever-increasing consumption of natural resources new prospecting techniques are required to satisfy the demand. Geophysical methods are one tool commonly relied upon. New acquisition platforms or survey methodologies provide one way to expand the geophysical capabilities, but are expensive and slow to develop. New processing and interpretation techniques on the other hand provide a rapid means to reinterpret existing datasets with the goal of improving our geologic understanding of a project area. This thesis presents four new ways to extract additional geologic insights from a variety of geophysical datasets. All of the studies are based within the Bathurst Mining Camp, NB. A physical rock property database for the Bathurst Mining Camp is constructed and statistically analyzed in chapter two. Descriptive statistics include mean, standard deviation; first, second and third quartiles are calculated for density and magnetic susceptibility measurements and provided in tables for reference. Bivariate plots are then used to identify trends in the density-magnetic susceptibility relationship. We relate some of our findings to processes involved in the depositional and alteration history of the various lithologies. Comprehensive rock property databases provide valuable constraints for geophysical data processing and are essential for any subsequent geophysical modeling. This is demonstrated with two examples. A joint gravity-magnetic profile model is completed across the geologically complex Nine Mile Synform. The profile reveals deep structure in the Camp down to 5 km depth. A geologically constrained geophysical inversion model of the magnetic anomaly associated with the Armstrong B mineral deposit reveals this anomaly contains a strong magnetic remanence contribution. The influence of remanence is often ignored in magnetic interpretation and modeling, but vital to achieve a geologically correct solution. In this instance comparison of the calculated remanence direction with the expected Apparent Polar Wander Path defined direction suggests an age of mineralization that is compatible with geological evidence. A new approach to determine the optimum near surface residual magnetic signal is presented in chapter three. Additionally, a new way of locating remanently magnetized bodies is also introduced. This technique inverts frequency domain helicopter-borne electromagnetic data to yield apparent magnetic susceptibility. To locate those zones where the magnetic signal is dominated by remanence the inverted HFEM susceptibility is cross plot against the results of a traditional apparent susceptibility filter. The inverted HFEM susceptibility is independent of remanence while the apparent susceptibility assumes no remanence. Where remanence is present the TMI derived apparent susceptibility does not correlate with the HFEM. These differences are readily evident in a cross plot of the two susceptibilities. To determine a magnetic residual the inverted susceptibility is forward modeled as a series of vertical prisms with homogeneous susceptibility equal to the inverted susceptibility. This HFEM magnetic model is then used to reference the results of traditional wavelength separation methods. By design the HFEM information is restricted the near surface whereas all traditional regional / residual separation methods operate under wavelength assumptions. A case study using this methodology is presented on the western side of the Tetagouche Antiform. The use of a spatially variable density correction applied to ground gravity and gravity gradiometry in the BMC is examined in the fourth chapter. The influence of topography on gravity and gravity gradiometry measurements is profound and must be removed prior to interpretation. In geologic environments where there is a structural and/or stratigraphic control on the near surface mass distribution, using a single density value may introduce error into the reduced data. A regionally variable density correction is a means to compensate for this effect. Spectral information between the ground gravity and airborne gravity gradiometry is also compared in this chapter. Both systems are fundamentally recording the same geologic mass distribution albeit by different means. Where differences exist one system must be in error. The final chapter demonstrates a quantitative interpretative technique for geophysical data. Often interpretation of the geophysical data in a geological context is done qualitatively using total field and derivative maps. With this approach the resulting map product may reflect the interpreter’s bias. Source edge detection provides a quantitative means to map lateral physical property changes in potential and non-potential field data, but the field data must be transformed prior to SED computation. There are numerous transformation algorithms, all of which operate slightly differently. We demonstrate that by combining the output of several different SED computations through data stacking, the interpretable product of SED is improved. In two examples, a synthetic example and real world example from the Bathurst Mining Camp, a number of transformation algorithms are applied to gridded geophysical datasets and the resulting SED solutions combined. Edge stacking combines the benefits and nuances of each SED algorithm; coincident, or overlapping solutions are considered more indicative of a true edge, while isolated points are taken as being indicative of random noise or false solutions.

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.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,977
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,009
Tête enseignante GPT0,174
Écart entre enseignants0,165 · 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