4.4 Article

Multi-sensor core logging (MSCL) and X-ray computed tomography imaging of borehole core to aid 3D geological modelling of poorly exposed unconsolidated superficial sediments underlying complex industrial sites: An example from Sellafield nuclear site, UK

期刊

JOURNAL OF APPLIED GEOPHYSICS
卷 178, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jappgeo.2020.104084

关键词

Multi-sensor core logging; X-ray computed tomography; Complex industrial sites; Superficial geology; Sellafield nuclear site

资金

  1. Royal Society Industry Fellowship
  2. National Nuclear Laboratory (NNL) Core Science Group Research and Development (RD) programme
  3. NERC [bgs06002] Funding Source: UKRI

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The 3D characterisation of geology underlying complex industrial sites such as nuclear plants is problematic due to the presence of the built infrastructure that restricts or in some cases completely prevents access for geologists to the subsurface environment. Outcrops are rare, geophysics surveys are often impossible (particularly at nuclear plants where activities such as vibroseis are frowned upon due to their effect on the infrastructure itself), and boreholes are often the only way to obtain subsurface data. Yet, with sedimentary deposits in particular, geotechnical logging undertaken to specific standards sometimes misses key information that could have been used to directly inform the creation of geological 3D models. Multi-sensor core logging (MSCL) and X-ray computed tomography (XCT) undertaken on core obtained from a borehole within the Sellafield nudear plant, is used to illustrate the potential for the techniques to contribute significantly to the creation of 3D subsurface geological models, particularly where access is restricted, such as within nuclear industry locations. Geophysical characteristics are recorded and used to reassess and enhance geotechnical descriptions, leading to the modification of existing unit boundaries or the creation of new ones. A new sedimentary log was created and this was used in a comparison with existing logs and nearby historic exposures, and as the basis for an illustration of industrial site to regional correlation. (C) 2020 The Authors. Published by Elsevier B.V.

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