Analysis of petrophysical properties of rocks from the Bathurst Mining Camp: Constraints on gravity and magnetic modeling

Author:

Tschirhart Peter1,Morris Bill2

Affiliation:

1. Sander Geophysics Ltd, Ottawa, Ontario, Canada..

2. McMaster University, MAGGIC, SGES, Hamilton, Ontario, Canada..

Abstract

Understanding the physical rock properties of different lithologies within a mining district allows one to link geologic observations with geophysical interpretations. This paper presents a physical rock property database for the Bathurst Mining Camp (BMC). Density–magnetic susceptibility bivariate plots are used to illustrate patterns indicative of changes in the concentration of paramagnetic versus ferrimagnetic mineral phases. Q-Q plots and histograms are used to determine if a lithology is characterized by a unimodal or multimodal physical property population. To use the physical property data in geophysical models, the rock classification was reduced to five lithological groups and three subgroups. The results of two geophysical modeling exercises, using lithological and petrophysical data as input constraints, are presented. Late-stage deformation of the BMC resulted in two large-scale plunging folds: the Nine Mile Synform (NMS) and the Tetagouche Antiform. The subsurface geometry of the NMS along the model profile was initially estimated from surficial geology maps projected down the plunge of the fold axis. Geophysical data requires dense and magnetic volcanics on the east limb of the Nine Mile Syncline to be nearer to the surface than previously expected. The magnetic anomaly associated with the Armstrong B mineral deposit was modeled using constrained discrete object source geometry. To achieve a satisfactory match between the observed and calculated data requires a significant component of magnetic remanence. The orientation of the calculated remanence vector is similar to a paleomagnetically determined in situ direction and to the direction estimated for Laurentia during the Paleozoic. The source body estimated by the inversion is significantly larger than the known thickness of the ore zone. This is a consequence of computing the inversion on a gridded aeromagnetic data set, which has a cell size that is larger than the known thickness of the ore body.

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

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