Big Data view in the oil and gas sector
“Big Data” is a rather vague term that describes the application of new tools and techniques to digital information on a size and scale well beyond what was possible with traditional approaches (Lohr,2012)typically involving data sets that are so large and complex that they require advanced data storage, management, analysis, and visualization technologies. The oil and gas sector has already been noticeably impacted by several of the technologies underpinning these changes.
The data collected in oil and gas industry tend to be discarded ignored, or analyzed in a very cursory way though other parts of the market realized the important value of data by Big Data technologies. The data is frequently regarded as descriptive information about a physical asset rather than something that is very valuable. But leaders in Big Data, by stark contrast, regard data as an asset in and of itself. Industry should use Big Data tools to extract more value from digital information
Big Data is a result of several innovations and novel ideas coming together in a highly complementary way but not a result of single silver-bullet technology. Technological developments aspects:
- The Cost of data Storage decline:
Several years ago, it was standard practice in many industries to discard significant collections of data when their initial use had passed, as there was a real economic expense associated with archiving the data afterward (e.g., Feblowitz,2013). This is much less true today (Komorowski,2014).
- Continuously growing the processing speeds of computing devices.
The amount of computing power offered in commercially available devices has been increasing at a similarly impressive rate (Ball,2000).
Big Data impact in oil and gas sector
In light of this sweeping global trend, it is hard to imagine a future in which the oil and gas industry is not collecting significantly more data than it does at the moment. And with such large amounts of digital information accumulating around them, it is easy to understand why many industry insiders believe that they are already solidly on track to reap the benefits of Big Data. But the oil and gas sector seems to be approaching these rapidly growing data sets with the same attitudes and analytical techniques that have been with the industry for years. As (Feblowitz,2013) suggests, a lot of potentially valuable digital information harvested from upstream oil and gas assets is barely given a cursory glance, and much of it is simply thrown away. Moreover, in those instances where data is stored, it is often kept by the service companies responsible for generating it rather than the operator in charge of managing the long-term welfare of the asset.
New technologies that have given rise to Big Data, and briefly examined the potential relevance of these changes to the oil and gas sector. The amount and kinds of value that Big Data can deliver will clearly vary considerably from one industry to the next, but a few important themes are emerging across the entire business landscape.
The oil and gas sector’s digital revolution is unfinished. The case for moving towards digital oilfield technologies was largely based on the ability of those tools to help the industry make better decisions—and when you peel back all the hype, that is ultimately what Big Data is about, too (Regalado,2014). In this way, Big Data is not the dawn of a new age for the oil and gas sector, but rather the next phase of a digital transformation that started a long time ago. The industry’s digital revolution will be complete when the sector figures out how to monetize the data that it is now capable of collecting, and then uses it to create all the value that it can.
Ball(2000) BallChemistry meets computing Nature, 406 (6792), (pp. 118-120).
Feblowitz, J.( 2013). Analytics in oil and gas: the big deal about Big Data. In: Proceedings of the SPE Digital Energy Conference and Exhibition. Paper no. SPE 163717. The Woodlands, Texas, USA.
Lohr, S.( 2012). How Big Data became so big. New York Times, August 11 issue. Retrieved 19 May 2014 from http://www.nytimes.com/2012/08/12/business/how-big-data-became-so-big-unboxed.html
Komorowski( 2014). A History of Storage Costs. Retrieved 19 May 2014, from http://www.mkomo.com/cost-per-gigabyte
Regalado(2014).RegaladoData and decision making MIT Technol. Rev., (2014), (pp. 61-63).