By Rubi Alvarado – General Manager, Energy Capital
In an increasingly digitized world, the global oil and gas industry has had to explore turbulent waters to reinforce investments and not be relegated. Therefore, various companies in the sector have begun to consider advances in digital technology to take advantage of their benefits.
Particularly, the applications of several technology solutions have proven to be highly beneficial in oil refining activities, as well as in distribution and retail. As a result, this is pretty relevant since today, even with the growing electrification of transport; downstream remains one of the energy sectors with the highest demand globally.
Faced with the reconfigurations of global demand —influenced by factors such as the importance of energy efficiency and the energy transition—; refineries will have to increase their investments in big data and analytics. Particularly, to reduce its carbon emissions even more and transcend its processes to more resilient and profitable forms of energy.
Big Data: How can it help downstream companies integrate energy efficiency?
Accordingly, Big Data can help oil and gas companies in the downstream sector manage and process large datasets and improve their production processes. Similarly, as various industry experts acknowledge and underscore, “data is currently the oil of the new economy.”
Worth noting, Big Data and analytics have a long history in refining. For instance, some refineries introduced the analytic equation in the late 1980s for property prediction in rotating equipment and detect poor performance.
More recent advances in big data technologies include data logging, storage, and processing. Accordingly, some of these solutions can be useful in the refinery sector, including estimating energy efficiency and its use to correctly assess downtime maintenance.
Likewise, big data can be used in repair costs through various models and analysis methods. On the distribution industry side, too, it can target maintenance and be useful to predict process and equipment failures.
As a complement to big data, the analytics part is also being introduced in the downstream sector with enthusiasm, particularly with the aim to investigate and understand the inner meaning of the large datasets an asset produces. Some of the processes throughout analytics work include machine learning and data mining; thus, these can later be used along the downstream’s manufacturing process and help improve the sector’s laboratory information systems.
On the refining side, some companies have introduced asset management systems relying on data providers. Similarly, reliability managing systems are also being introduced in some refineries. However, in practice, these information sources are mostly separated, only connected at some level.
In this sense, various providers are integrating elements of these sources into only one database (megadata structure) reference architecture. To illustrate, that type of data system is popular now in the refinery sectors with suppliers including Honeywell and Siemens.
Also, some parts of the industry that are adopting these more modern platforms are supply, trading, competitive analysis, and supplying. Some examples of Big Data solutions in Pricing, Supply, and Price Optimization (sale and retail); are those provided by IBM, Oracle, SAS, Teradata, EMC, and others. Particularly, parties who are leveraging opportunities in the technology space.
An evolving adoption
Finally, and it should be noted, this technology adoption is still under development. In fact, it was not until more recently that several oil and gas companies in the US realized the applications that big data had in the industry. However, as early as 2018, a survey by General Electric and Accenture found that 81% of executives considered big data among their future investment priorities.
As can be seen, the trend of Big Data and analytics is still on its way. And most likely, companies in the downstream sector will continue that line. In brief, digitization has proven to be beneficial by providing additional information resources; which maximize the industry’s growth and generate value in the long term.