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Shafiee, Mahmood, Animah, Issac, Alkali, Babakalli and Baglee, David (2018) Decision Support Methods and Applications in the Upstream Oil and Gas Sector. Journal of Petroleum Science and Engineering, 173. pp. 1173-1186. ISSN 0920-4105

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    PETROL12300R1.pdf - Accepted Version

Abstract

Abstract

Decision-making support (DMS) methods are widely used for technical, economic, social and
environmental assessments within different energy sectors, including upstream oil and gas,
refining and distribution, petrochemical, power generation, nuclear power, solar, biofuels,
and wind. The main aim of this paper is to present a comprehensive literature review and
classification framework for the latest scholarly research on the application of DMS methods
in the upstream oil and gas industry. To achieve this aim, a systematic review is conducted on
the current state-of-the-art and future perspectives of various DMS methods applied to
different upstream operations (such as exploration, development and production) which take
place prior to shipping of crude oil and natural gas to the refineries for processing. Journal
and conference proceeding sources that contain literature on the subject are identified, and
based on a set of inclusion criteria the related papers are selected and reviewed carefully. A
framework is then proposed to classify the literature according to the year and source of
publications, type of fossil fuel sources, oil and gas field’s lifecycle phases, data collection techniques, decision-making methods, and geographical distribution and location of case studies. The proposed literature classification and content analysis can help upstream oil and gas industry stakeholders such as field owners, asset managers, service providers, policy makers, environmentalist, financial analyst, and regulatory agencies to gain better insight about their business activities with well-informed decision-making processes.

Item Type: Article
Related URLs:
Depositing User: David Baglee
URI: https://sure.sunderland.ac.uk/id/eprint/10072

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Item ID
10072
Identification Number
ISSN
0920-4105

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ORCID for David Baglee

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Date Deposited
22 Oct 2018 13:51
Last Modified
04 Jun 2025 15:23

Contributors

Author
Mahmood Shafiee
Author
Issac Animah
Author
Babakalli Alkali
Author
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Author
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Author
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