T93 Geologic Maps and Their Derivatives (Posters)
Monday, 10 October 2022
9:00 AM - 1:00 PM
Exhibit Hall F
SILURIAN DEPTH-TO-BEDROCK MAP FOR EASTERN WISCONSIN, USA
Paper number: T93-12
Program: Technical Sessions
Time: 9:00 AM – 1:00 PM
Authors
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Matthew RehwaldMadison, WI
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David HartMadison, WI
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Burke MinsleyU.S. Geological Survey, Denver, CO
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Cody CalkinsMadison, WI
Abstract
Advancement of geographic information system (GIS) technologies and 43 years of additional subsurface information are available to generate a more current and precise DTB map. We applied a GIS spatial modeling tool called Empirical Bayesian Kriging with Regression Prediction (EBKRP) in Esri ArcGIS Pro 2.9.1 to first model a bedrock elevation surface, and then derive DTB by subtracting that surface from a ground-surface digital elevation model. We chose EBKRP over other interpolation methods because the calculation of an unknown value at a given location is dependent on the theoretical best fit of the variance of the known values over the interpolated area, rather than strictly distance. The theoretical best fit captures the spatial relationship across an area and provides the ability to coincidently generate a map of model error.
Additionally, the map presented here includes data from the novel application of airborne electromagnetic (AEM) data collected via SkyTEM Canada Inc. in collaboration with the United States Geological Survey and the Wisconsin Geological and Natural History Survey in 2021. AEM data was collected along helicopter flight lines and were inverted to produce electrical resistivity data at nearly 300 m depth with 1-2 m near-surface resolution. The resistivity transitions in the shallow subsurface were used to estimate DTB. Modern geostatistical techniques with additional and novel subsurface data has allowed us to generate a DTB map with higher resolution, more accuracy, and error estimates across the Silurian carbonate system in eastern Wisconsin.
Geological Society of America Abstracts with Programs. Vol. 54, No. 6
doi: 10.1130/abs/2022AM-382581
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