Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746610
Title: Feasibility assessment and informed survey design of cavity detection by forward geophysical modelling
Author: James, P. M.
ISNI:       0000 0004 7224 9489
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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Abstract:
Feasibility analysis of near-surface cavity detection is presented using modelling of the gravity, gravity gradient, magnetic, magnetic gradient, and ground penetrating radar techniques. The geophysical signal is modelled over typical cavity shapes in three-dimensional subsurface environments with varying geologies and survey parameters. The cavity detection probability is calculated for each technique in the outlined environments and these values are used to aid technique choice, assess the feasibility of cavity detection, assess the limits of detection for each technique, and optimise survey design before entering the field. The “halo” effect is quantified by simulating the halo around cavities and calculating the change to the gravity and magnetic anomalies by geophysical modelling. The magnitude of the effect is shown to be more complicated than existing literature implies, depending heavily on the fracture percentage in the halo area and the halo spread. Tests in a range of conditions show that technique choice is conditional to site characteristics and site parameters, and highlight the need for modelling in the desk study stage of site investigation and survey design. Detection probability results show that standard survey direction practice in magnetometry is not always optimal, and demonstrate the importance of site specific noise level consideration. Comparisons with case study measurements demonstrate that modelling and subsequent detection probability calculation chose appropriate techniques and survey parameters, but also highlighted the limitations of the method.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.746610  DOI: Not available
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