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TitleGeophysical processing and interpretation with geologic controls: examples from the Bathurst Mining Camp
AuthorTschirhart, P A
ThesisMSc, McMaster University
Source 2013, 129 pages
LinksOnline - En ligne
Alt SeriesEarth Sciences Sector, Contribution Series 20130523
Mediapaper; on-line; digital
File formatpdf
ProvinceNew Brunswick
NTS21O/01; 21O/02SE; 21O/02NE; 21O/07SE; 21O/07NE; 21O/08; 21O/09; 21O/10SE; 21O/10NE; 21P/04; 21P/05; 21P/12
Lat/Long WENS-66.6667 -65.5000 47.7500 47.0000
Subjectsgeophysics; economic geology; geophysical surveys; gravity surveys, ground; gravity anomalies; bouguer anomalies; mapping techniques; magnetic susceptibility; magnetic interpretations; Bathurst Mining Camp
Illustrationsgeophysical images; tables; geophysical profiles; models
ProgramTargeted Geoscience Initiative (TGI-4) Volcanogenic Massive Sulfide Ore Systems
Released2013 01 01
AbstractWith 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.

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