Oil and gas companies leverage Hadoop analytics

oilBig data analytics can provide insights into a whole host of processes and applications, and lead the way for innovations and improved methodologies. Businesses utilize data insights for boosted production and revenues, retailers use these findings to attract customers and the marketing sector leverages big data for targeted advertising campaigns. This trend has also made its way into the oil and gas market, as organizations in this field gather vast amounts of information and analyze it for a range of important uses.

Industry overview
In a recent whitepaper, Microsoft outlined the potential ways oil and gas businesses can utilize big data. It can be used for equipment maintenance, as data collected from pumps, wells and other industry equipment can help inform maintenance schedules. Data-collecting devices can be embedded in machinery to track real time functionality and let operators know if a machine is in danger of failure. Using this data, employees can fix internal issues and prevent expensive machinery downtimes.

Microsoft also stated that organizations  in this sector could also use big data for price optimization practices. Computing technologies can help administrators determine pricing strategies for commodities. Additionally, big data can be leveraged to optimize production. Analytics can highlight areas that can potentially be improved for increased product yields.

Furthermore, oil and gas companies can use predictive metrics pertaining to weather patterns and workforce scheduling to prevent putting workers in dangerous situations and mitigate potential environmental risks. These efforts can significantly boost workplace safety and help shape policies for industry standard compliance.

‘Moneyball’ parallel
According to drillinginfo’s Jeff Welber, oil and gas companies can leverage big data similarly to the way baseball guru Billy Beane used metrics to choose baseball players. For those unfamiliar with the story chronicled in the “Moneyball” book and subsequent film, Oakland Athletics general manager Billy Beane used an evidence-based analytics approach called sabermetrics to pick certain “diamond in the rough” players for his team. These players were evaluated by situational and predictive metrics, rather than common stats like home runs and batting average, representing a significant shift in the way the baseball industry established their teams.

Welber noted that a similar shift is taking place within the oil and gas industries, as organizations  use big data analytics to distinguish themselves from their competitors, just as Beane and the Athletics did. While initially used to boost the production of shale, analytics tools help companies utilize big data to target conventional reservoirs.

“While large scale capital expenditures with unconventional resource data may not be applicable to all conventional projects, smaller companies and operators can take advantage of the oil and gas data era without compromising individual project economics,” Welber wrote.

The United States: An energy superpower
As Welber alluded, big data can also be utilized in the current shale oil production environment, which is currently experiencing a historic boom, according to Wired contributor Atanu Basu. Although shale oil involves a controversial system of horizontal drilling and hydraulic fracturing called fracking, the U.S. is poised to surpass Saudi Arabia and Russia to become the world’s largest oil producer by 2016. While the drilling practice has considerable impact on the environment, Basu said big data could help make it safer and greener.

“The rumbling you hear underground isn’t just oil,” Basu wrote. “It’s gushers of data that if analyzed properly can yield new insights to producing more shale oil while reducing negative effects on the environment.”

Organizations in the oil and gas industries can leverage the tools of Apache Hadoop to make the most of their big data sources and realize insights from analytics. Customizable tools can assist users in leveraging big data that will benefit the organization and also meet their unique needs.

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Manufacturing Sensor

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