A Systematic Review of Big Data Analytics for Oil and Gas Industry 4.0
Систематический обзор аналитики больших данных для нефтегазовой промышленности в контексте Индустрии 4.0
2020-01-01
SCID: 54.1/wv6h37gu
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Industry 4.0big data analyticscybersecuritydata privacyoil and gas industry
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Abstract (AI)
Big data (BD) analytics is one of the critical components in the digitalization of the oil and gas (O&G) industry. Its focus is managing and processing a high volume of data to improve operational efficiency, enhance decision making and mitigate risks in the workplace. Enhanced processing of seismic data also provides the industry with a better understanding of BD applications. However, the industry still exercises caution in adopting new technologies. The slow pace of technology adoption can be attributed to various causes, from the obstacles to the integration with existing systems, to cybersecurity for defending the BD system against cyber attacks. In some applications using wearable devices, physiological and location-tracking data also causes concerns related to workplace privacy implications. These shortcomings give rise to uncertainties about the practical benefits and effectiveness of applying BD in O&G activities. The objective of this paper is to perform a systematic review of BD analytics within the context of the O&G industry. This paper attempts to evaluate technical and nontechnical factors affecting the adoption of BD technologies. The study includes BD development platforms, network architecture, data privacy implications, cybersecurity, and the opportunities and challenges of adopting BD technologies in the O&G industry.
Key Findings
1
Big data analytics is identified as a critical component of Oil and Gas Industry 4.0 digitalization, supporting operational efficiency, decision making, and workplace risk mitigation.
2
Enhanced seismic-data processing is highlighted as an important application that improves understanding and use of big data in the oil and gas industry.
3
Technology adoption remains slow because of integration challenges with existing systems and cybersecurity risks affecting big data infrastructures.
4
The review evaluates technical and nontechnical adoption factors, including development platforms, network architecture, privacy, cybersecurity, opportunities, and implementation challenges.
5
Wearable-device applications raise workplace privacy concerns because they collect physiological and location-tracking data.
Research Object
Big data analytics in the oil and gas industry
Research Subject
Technical and nontechnical factors, opportunities, challenges, and practical effectiveness affecting the adoption of big data technologies in oil and gas activities
Publication Details
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2020-01-01
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