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Using a multivariogram approach to improve the accuracy of subsurface geological models

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Title: Using a multivariogram approach to improve the accuracy of subsurface geological models
Author: MacCormack, Kelsey; Arnaud, Emmanuelle; Parker, Beth L.
Department: School of Environmental Sciences
Abstract: Subsurface geological models are often used to visualize and analyze the nature, geometry, and variability of geologic and hydrogeologic units in the context of groundwater resource studies. The development of three-dimensional (3D) subsurface geological models covering increasingly larger model domains has steadily increased in recent years, in step with the rapid development of computing technology and software, and the increasing need to understand and manage groundwater resources at the regional scale. The models are then used by decision makers to guide activities and policies related to source water protection, well field development, and industrial or agricultural water use. It is important to ensure that the modelling techniques and procedures are able to accurately delineate and characterize the heterogeneity of the various geological environments included within the regional model domain. The purpose of this study is to examine if 3D stratigraphic models covering complex Quaternary deposits can be improved by splitting the regional model into multiple submodels based on the degree of variability observed between surrounding data points and informed by expert geological knowledge of the geological– depositional framework. This is demonstrated using subsurface data from the Paris Moraine area near Guelph in southern Ontario. The variogram models produced for each submodel region were able to better characterize the data variability, resulting in a more geologically realistic interpolation of the entire model domain as demonstrated by the comparison of the model output with preexisting maps of surficial geology and bedrock topography as well as depositional models for these complex glacial environments. Importantly, comparison between model outputs reveals significant differences in the resulting subsurface stratigraphy, complexity, and variability, which would in turn impact groundwater flow model predictions.
Description: This article is available on the Canadian Journal Of Earth Sciences website at: http://www.nrcresearchpress.com/doi/10.1139/cjes-2016-0112
URI: http://hdl.handle.net/10214/12544
Date: 2017-09-26


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