High-resolution 3D geological modelling of heterogeneity in poorly exposed glacial deposits using sedimentary and glaciotectonic architectural element analysis: a case example from Sellafield in West Cumbria, UK

Smith, Nicholas T; Merritt, Jonathan W.; Phillips, Emrys R.. 2023 High-resolution 3D geological modelling of heterogeneity in poorly exposed glacial deposits using sedimentary and glaciotectonic architectural element analysis: a case example from Sellafield in West Cumbria, UK. Quarterly Journal of Engineering Geology and Hydrogeology, 56 (1). https://doi.org/10.1144/qjegh2022-022

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Official URL: http://dx.doi.org/10.1144/qjegh2022-022

Abstract/Summary

3D modelling of superficial geology is challenging, particularly for complex industrial sites such as the Sellafield nuclear site, Cumbria, UK. A lithostratigraphic approach is sufficient to show distribution of key units where only a general understanding of hydrogeology is required. For many sites however, a much higher-resolution understanding is needed to better characterise heterogeneity and identify potential pathways for contaminant transport within safety case development and remediation planning. Models that focus on often thin, laterally discontinuous, heterogeneous sedimentary units are beset with issues including (i) a lack of exposure coupled with a dearth of data gathered by low-intrusive and intrusive means, (ii) structural, stratigraphic, and sedimentological complexities making correlation between datapoints difficult, and (iii) uncertainties associated with data quality. However, these problems may be overcome by combining land-system-based sedimentary and glaciotectonic architectural analysis of local field analogues with the creation of a portfolio of generic unit-bounding surface geometries. We test this through the development of a high-resolution 3D geological model of Sellafield nuclear site, where exposures are sparse, but shallow site-investigation boreholes are many. The results demonstrate serious shortcomings with other, less labour-intensive models for the district created from selected datasets and with limited reference to considerable published knowledge.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1144/qjegh2022-022
ISSN:	1470-9236
Date made live:	23 Aug 2022 14:15 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533092

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1144/qjegh2022-022

ISSN:

1470-9236

Date made live:

23 Aug 2022 14:15 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/533092