{"id":{"repo_id":"wlv","oai_identifier":"oai:wlv.openrepository.com:2436/625247"},"canonical_url":"https://search.dev.ndltd.org/etd/wlv/oai:wlv.openrepository.com:2436/625247","repository":{"repo_id":"wlv","name":"University of Wolverhampton","base_url":"https://wlv.openrepository.com/server/oai/request"},"display":{"title":"Adoption of cloud computing technology for exploration, drilling and production activities: Nigerian upstream oil and gas industry","abstract":"The upstream oil and gas industry, which identifies and produces oil and gas, is essential for the generation of energy. This sector has a fragmented pattern of activities and uses real-time information and accurate results for faster and more accurate decision making. Cloud computing offers information technology (IT) services via the internet and the technology offers several benefits such as flexibility, scalability, cost reduction, real-time information, monitoring, collaboration and timely interpretation of exploration and production data. However, the cloud has not yet penetrated the upstream oil and gas sector. Generally, the adoption of cloud computing in the oil and gas industry is less discussed in academia, let alone the upstream oil and gas sector. This research aims to study the adoption of cloud computing in the upstream oil and gas industry, particularly in Nigeria, which is an emerging economy. The decision to adopt cloud computing for exploration, drilling and production is a complex process. A major outcome of the research is the development of a model consisting of factors influencing decision to adopt cloud technology in the upstream oil and gas sector. In addition, the study develops a prototype decision support system (DSS) based on analytical hierarchy process (AHP) which enables decision makers to select an appropriate cloud service model. The developed prototype DSS is described in appendix A. This research adopted a mixed method approach comprising of semi-structured interview which was used to collect qualitative data using NVivo 11 software, and a questionnaire survey which was used to collect quantitative data which was analysed using the Analysis of a Moment Structures (AMOS) based structural equation modelling technique. The findings of this research confirmed the significant factors for cloud computing adoption for exploration, drilling and production activities. This research has both theoretical and practical implications which reinforce the need for cloud technology adoption in the upstream oil and gas sector. In addition, using the research findings to develop a prototype Decision Support System (DSS) is innovative and would be useful to the Nigerian government, cloud service providers and the upstream oil and gas sector. Finally, the study makes recommendations for upstream O&G based on the findings of the study.","abstract_html":"The upstream oil and gas industry, which identifies and produces oil and gas, is essential for the generation of energy. This sector has a fragmented pattern of activities and uses real-time information and accurate results for faster and more accurate decision making. Cloud computing offers information technology (IT) services via the internet and the technology offers several benefits such as flexibility, scalability, cost reduction, real-time information, monitoring, collaboration and timely interpretation of exploration and production data. However, the cloud has not yet penetrated the upstream oil and gas sector. Generally, the adoption of cloud computing in the oil and gas industry is less discussed in academia, let alone the upstream oil and gas sector. This research aims to study the adoption of cloud computing in the upstream oil and gas industry, particularly in Nigeria, which is an emerging economy. The decision to adopt cloud computing for exploration, drilling and production is a complex process. A major outcome of the research is the development of a model consisting of factors influencing decision to adopt cloud technology in the upstream oil and gas sector. In addition, the study develops a prototype decision support system (DSS) based on analytical hierarchy process (AHP) which enables decision makers to select an appropriate cloud service model. The developed prototype DSS is described in appendix A. This research adopted a mixed method approach comprising of semi-structured interview which was used to collect qualitative data using NVivo 11 software, and a questionnaire survey which was used to collect quantitative data which was analysed using the Analysis of a Moment Structures (AMOS) based structural equation modelling technique. The findings of this research confirmed the significant factors for cloud computing adoption for exploration, drilling and production activities. This research has both theoretical and practical implications which reinforce the need for cloud technology adoption in the upstream oil and gas sector. In addition, using the research findings to develop a prototype Decision Support System (DSS) is innovative and would be useful to the Nigerian government, cloud service providers and the upstream oil and gas sector. Finally, the study makes recommendations for upstream O&G based on the findings of the study.","abstract_has_math":false,"creators":["Lawan, Mahmud Maina"],"institution":"University of Wolverhampton","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Oduoza, Chike"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-09","date_published":"2022-09","updated_at":"2026-07-24T06:10:16Z","subjects":["cloud computing","adoption","upstream oil and gas","information and communication technologies"],"languages":[],"rights":["Attribution-NonCommercial-NoDerivatives 4.0 International"],"rights_urls":["https://wlv.dspace7.openrepository.com/bitstreams/6e6cf1b8-ec14-450c-9dd9-0f4c44521bb5/download"],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Oduoza, Chike"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Nigerian Petroleum Technology Development Fund (PTDF)."]},{"key":"dc:creator","label":"Author","values":["Lawan, Mahmud Maina"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2022-09"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Wolverhampton"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["http://hdl.handle.net/2436/625247"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cloud computing","adoption","upstream oil and gas","information and communication technologies"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["https://wlv.dspace7.openrepository.com/bitstreams/6e6cf1b8-ec14-450c-9dd9-0f4c44521bb5/download","Attribution-NonCommercial-NoDerivatives 4.0 International"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://wlv.dspace7.openrepository.com/bitstreams/b03292bd-79d0-4ffe-83f8-cf0f3a6ab87b/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The upstream oil and gas industry, which identifies and produces oil and gas, is essential for the generation of energy. 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This research has both theoretical and practical implications which reinforce the need for cloud technology adoption in the upstream oil and gas sector. In addition, using the research findings to develop a prototype Decision Support System (DSS) is innovative and would be useful to the Nigerian government, cloud service providers and the upstream oil and gas sector. 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