Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.787432
Title: Quantifying strain partitioning in multi-layers : the use of virtual outcrop analysis to investigate patterns of deformation
Author: Cawood, Adam J.
ISNI:       0000 0004 7972 5505
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2019
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Abstract:
Understanding how strain is partitioned through deformed stratigraphic sequences is important for accurately characterising subsurface rock volumes and informing decision making in a range of applications (e.g. resource extraction or hazardous waste storage). Where deformation patterns in the subsurface are under-constrained due sampling limitations (e.g. seismic resolution), outcrop studies can inform subsurface modelling and prediction strategies. Practical limitations on outcrop-based data collection may, however, lead to insufficient sampling, inadequate characterisation and oversimplified structural models - outcomes which limit the applicability of outcrops as subsurface analogues. Outcrop reconstruction via close-range remote sensing has the potential to circumvent some of these issues but the accuracy and reliability of structural data derived from 3D reconstructions requires assessment and the methods for interrogating these objects remain underdeveloped. This research therefore aims to (1) develop and refine methodological approaches to using 3D reconstructions for structural analysis. This is done by quantifying 3D reconstruction accuracy and fidelity; providing recommendations for data acquisition and processing workflows; developing techniques to extract, manipulate and analyse 3D reconstruction data; and establishing techniques to integrate additional data sources and types. These approaches and developed techniques are used to (2) build on existing understanding of the link between multilayer properties and patterns of deformation. Quantification of linked stratigraphic-structural processes, refinement of existing structural models, and appraisal of scaling in geological processes by leveraging 3D reconstructions (and other data types) to capture both spatial and temporal variations in patterns of strain distribution. Results show that acquisition and processing workflows are key in determining the accuracy and fidelity of 3D reconstructions, and thus the quality and reliability of structural data that they yield. Further, rigorous treatment of digital data and integration of 3D reconstructions with other data sources are required for structural characterisation. Quantification of structural patterns shows that stratigraphic properties, which are inherently variable in 3D, influence patterns of strain distribution both spatially and temporally, through progressive deformation. Finally, the complex patterns of strain distribution recorded in this work highlights the shortcomings of idealised structural models and therefore the validity of using simplified templates as tools for subsurface characterisation.
Supervisor: Bond, Clare E. ; Howell, John A. Sponsor: Natural Environment Research Council (NERC) ; University of Aberdeen
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.787432  DOI: Not available
Keywords: Outcrops (Geology) ; Rock deformation
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