The low oil price period and the resulting investment reductions and stops have developed a focus on improving the efficiency of existing facilities to enable operators and EPC contractors to stay competitive. It is becoming evident that a major focus for everyone involved must be the minimisation of overheads and having an even sharper focus on productivity.
Less CAPEX investment on projects also means that the existing assets need to be operated for longer, or their production capacity needs to be increased. This results in more changes during the asset life cycle and requires more velocity for processing Big Data.
One approach to increasing efficiency and velocity can be through the use of better technology in conjunction with a clear plant information management strategy to be able to manage the virtual representation of the physical facility.
According to a 2016 report by Research and Markets, the Big Data, Business Intelligence and Analytics market in the Middle East is expected to grow from $5.09 billion in 2015 to $12.38 billion by 2020, at a CAGR of 19.4%. “The oil and gas market is one of the huge demand drivers for big data and analytics,” Benoit Dubarle, president – Gulf countries and Pakistan, at Schneider Electric, says.
It has been a standard practice for oil and gas majors to measure their value in oil reserves. Over the past several years it was possible to ensure facilities becoming more profitable by means of new exploration technologies and innovative ways of extracting oil, such as drilling not just vertically but also horizontally.
At the same time, increased attention should be paid on the value of asset information. The way data is being used can also have a major impact on the feasibility of developing assets viably. Oil and gas companies can benefit not only from deploying these types of new digital plant technologies such as enhancing safety procedures, or automating manual and paper-based processes, but also from integrating new and existing technologies.
Integrating virtual asset data with real time data to bring more reactivity during asset operation is another opportunity in the Big Data domain.
Independent market researches, including ARC Advisory Group, published a study about the need for developing an Asset Information Management Strategy in 2010. Their findings showed that not managing asset information properly can result in an annual loss of 1.5% of the annual sales of an asset per year.
Today, according to ARC Advisory Group, the global process industry loses $20bn annually due to unplanned downtime. “Worse: most – more than 80% – of plant failures are not even detectable by current preventive age and wear based maintenance practices (Source: ARC, Proactive Asset Management with IIoT and Analytics, 2015),” Luc Chantepy, regional sales vice president – MENA at AspenTech, says. “Most assets display a random failure pattern, and these symptom-based failures are only addressable via predictive and prescriptive analytic approaches.”
“We see strong interest in addressing the previously unsolvable challenges of low asset availability, unplanned downtime and process disruptions. Companies will be forced to tackle these problems in an increasingly competitive global manufacturing environment with ever-changing supply and demand patterns that call for ever-higher levels of operational excellence,” Chantepy continues.
“The industry will adopt a simpler, easier-to-deploy and –use, more accurate 21st century data-driven approach to improve plant reliability because traditional approaches to maintenance will not drive the performance improvements needed in the future.”
Like other industries, oil and gas companies are continuing to invest in big data. This includes new data-management technologies (such as Hadoop), new solution architectures (such as data lakes and logical data warehouses) as well as new productivity platforms.
