Towards an Architecture for Handling Big Data in Oil and Gas Industries: Service-Oriented Approach

Azzedin, Farag; Ghaleb, Mustafa

doi:10.14569/ijacsa.2019.0100269

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Efforts have been made to propose and develop architecture for the adoption of some of the I4.0 technologies. An example is the proposed Service Oriented Architecture (SOA) to address the issues of BD in the O&G industry [261]. An IoF architecture for the vertical integration in the O&G industry that incorporates the industry standard IEC 61499 and OPC UA was proposed in [262].…”

Section: I40 Framework For Upstream Oandg Sectormentioning

confidence: 99%

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

et al. 2021

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The market volatility in the oil and gas (O&G) sector, the dwindling demand for oil due to the impact of COVID-19, and the push for alternative greener energy are driving the need for innovation and digitization in the O&G industry. This has attracted research interest from academia and the industry in the application of industry 4.0 (I4.0) technologies in the O&G sector. The application of some of these I4.0 technologies has been presented in the literature, but the domain still lacks a comprehensive survey of the application of I4.0 in the O&G upstream sector. This paper investigates the state-of-the-art efforts directed toward I4.0 technologies in the O&G upstream sector. To achieve this, first, an overview of the I4.0 is discussed followed by a systematic literature review from an integrative perspective for publications between 2012-2021 with 223 analyzed documents. The benefits and challenges of the adoption of I4.0 have been identified. Moreover, the paper adds value by proposing a framework for the implementation of I4.0 in the O&G upstream sector. Finally, future directions and research opportunities such as framework, edge computing, quantum computing, communication technologies, standardization, and innovative areas related to the implementation of I4.0 in the upstream sector are presented. The findings from this review show that I4.0 technologies are currently being explored and deployed for various aspects of the upstream sector. However, some of the I4.0 technologies like additive manufacturing and virtual reality are least explored.INDEX TERMS Artificial intelligence (AI), cyber-physical systems, digital-twin, framework, oil and gas (O&G), industry revolution 4.0 (IR 4.0), industry 4.0 (I4.0), internet of things (IoT), simulation, upstream sector

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Section: I40 Framework For Upstream Oandg Sectormentioning

confidence: 99%

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

et al. 2021

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“…Besides this, the use of other cloud-based technologies for building a big data architecture [37] for comprehensive quality assessment of higher education systems is also planned for future to improve the performance and usability of the educational intelligence application.…”

Section: Future Workmentioning

confidence: 99%

Big Data Technology-Enabled Analytical Solution for Quality Assessment of Higher Education Systems

Khan

Alam

Liu

et al. 2019

IJACSA

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Educational Intelligence is a broad area of big data analytical applications that make use of big data technologies for implementation of solutions for education and research. This paper demonstrates the designing, development and deployment of an educational intelligence application for real-world scenarios. Firstly, a quality assessment framework for higher education systems that evaluate institutions on the basis of performance of outgoing students was proposed. Secondly, big data enabled technological setup was used for its implementation. Literature was surveyed to evaluate existing quality frameworks. Most existing quality assessment systems take into account the dimensions related to inputs, processes and outputs, but they tend to ignore the perspective that assesses the institution on the basis of outcome of the educational process. This paper demonstrates the use of outcome perspective to compute quality metrics and create visual analytics. In order to implement and test the framework, R programming language and a cloud based big data technology that is Google, BigQuery were used.

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“…Oljeindustrien jobber under leveransepress i tett samspill mellom menneske og teknologi. På begge disse områdene har man flyttet fokuset ved uønskede hendelser bort fra skyld og skam og i stedet operasjonalisert kontinuerlig forbedring, sanntidsovervåkning og risikostyring (8).…”

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Fra skyld og skam til læring og forbedring

Tajik¹

2019

Tidsskriftet

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Towards an Architecture for Handling Big Data in Oil and Gas Industries: Service-Oriented Approach

Cited by 7 publications

References 10 publications

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

Big Data Technology-Enabled Analytical Solution for Quality Assessment of Higher Education Systems

Fra skyld og skam til læring og forbedring

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