| Autor: |
Trung Nguyen, Raymond G. Gosine, Peter Warrian |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 8, Pp 61183-61201 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.2979678 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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