A drift isopach model for the southwestern Great Slave Lake region, Northwest Territories, Canada

• Main Authors: I. Rod Smith (14271070), Christine Deblonde (14271073), Grant Hagedorn (14271076), Roger C. Paulen (14271079)
• Format: Other Non-Article Part of Journal/Newspaper
• Language: unknown
• Published: 2022
• Subjects: Ecology; Environmental Sciences not elsewhere classified; Biological Sciences not elsewhere classified; Drift thickness; glacial sediments; isopach map; empirical Bayesian kriging; lithostratigraphy; Northwest Territories; Cameron Hills; Canada; Great Slave Lake; Pine Point
• Online Access: https://doi.org/10.6084/m9.figshare.21741307.v1

This study produced a drift thickness model for the southwestern Great Slave Lake area of northern Canada, using 12,692 lithostratigraphic records (seismic shothole drillers’ logs, diamond drill holes, petroleum wells), and field observations. Numerous algorithms and modelling parameters were tested using 6122 records of absolute drift thickness, and based on a cross-validation analysis, an empirical Bayesian kriging K-Bessel detrended algorithm was found to produce the best fit. The final model, incorporating selected maximum and minimum thickness estimate data, produced a root mean square error of 4.98 m, with 94.8% of the data points within ±2 m of the modelled drift thicknesses. The model identifies widespread areas of drift >10 m thick, and prominent southeast-northwest aligned bedrock ramps. Karst structures buried by ≤73 m of drift were identified southwest of Great Slave Lake and appear to be aligned with regional fault systems like ore-associated karst at Pine Point. These may be the source of anomalous glacial sediment-derived base metal indicators collected proximally to the west. The most striking drift anomaly is in Cameron Hills where the eastern and northern margins are comprised of shale and siltstone bedrock overlain by 20–40 m of glacial sediments, but the central and western uplands have petroleum well logs identifying glacial sediments up to 400 m thick. In addition to mineral exploration, results of this study provide baseline data that can be used predictively by the petroleum industry in designing future seismic and drilling (casing depth) operations, and by those modelling groundwater sources and flow.