Use this URL to cite or link to this record in EThOS:
Title: Uncertainties in the outlook for oil and gas
Author: McGlade, C. E.
ISNI:       0000 0004 5354 0609
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Oil and gas will play a central role in the global energy system for the foreseeable future. However, uncertainty surrounds both the availability of and demand for these fuels, and as a result, there are quite disparate viewpoints on the magnitude of this role. The aim of this thesis is to identify, understand, quantify and, where possible, minimise the sources of this uncertainty, and to investigate the implications that such uncertainties have on the future of oil and gas. There are two areas of original contribution to knowledge. First, while numerous studies have examined the availability of various subsets of oil and gas, often in a deterministic manner, this work provides a full description of the uncertainty in the resource potential of all individual categories of oil and gas. This includes estimating the uncertainty in resource availability at different costs of production, and also examining the resource potential of categories that have been previously overlooked. Second, the implications of this and other major sources of uncertainty have never been investigated using models that incorporate both supply and demand-side dynamics. Two models are used for this purpose. The first is an existing energy systems model, TIAM-UCL, which has been substantially modified to allow a more accurate characterisation of long-term oil and gas production and consumption. The second is an oil-sector specific model that has been developed named the 'Bottom-Up Geological and Economic Oil field production model' (BUEGO). This is capable of examining oil production potential to 2035 and is used to examine shorter-term and more sector specific uncertainties.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available