Big Data analytics in oil and gas industry: An emerging trend
Аналитика больших данных в нефтегазовой отрасли: новый тренд
2018-12-01
SCID: 54.1/uqkn7r99
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Big Data analyticsdrilling safetyoil and gas industryreservoir characterizationseismic data analysis
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Abstract (AI)
This paper reviews the utilization of Big Data analytics, as an emerging trend, in the upstream and downstream oil and gas industry. Big Data or Big Data analytics refers to a new technology which can be employed to handle large datasets which include six main characteristics of volume, variety, velocity, veracity, value, and complexity. With the recent advent of data recording sensors in exploration, drilling, and production operations, oil and gas industry has become a massive data intensive industry. Analyzing seismic and micro-seismic data, improving reservoir characterization and simulation, reducing drilling time and increasing drilling safety, optimization of the performance of production pumps, improved petrochemical asset management, improved shipping and transportation, and improved occupational safety are among some of the applications of Big Data in oil and gas industry. Although the oil and gas industry has become more interested in utilizing Big Data analytics recently, but, there are still challenges mainly due to lack of business support and awareness about the Big Data within the industry. Furthermore, quality of the data and understanding the complexity of the problem are also among the challenging parameters facing the application of Big Data.
Key Findings
1
Applications include seismic and micro-seismic analysis, improved reservoir characterization and simulation, reduced drilling time, enhanced drilling safety, and optimized production-pump performance.
2
Big Data analytics also supports petrochemical asset management, shipping and transportation, and occupational safety improvements.
3
Big Data analytics is emerging across upstream and downstream oil and gas operations to manage datasets characterized by volume, variety, velocity, veracity, value, and complexity.
4
Industry adoption remains constrained by limited business support and awareness, alongside data-quality problems and difficulty understanding complex operational issues.
5
Sensor deployment in exploration, drilling, and production has transformed the oil and gas industry into a highly data-intensive sector.
Research Object
Upstream and downstream oil and gas industry operations
Research Subject
utilization, applications, and implementation challenges of Big Data analytics for handling industry data
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2018-12-01
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