Data Analytics and the Future of North Sea Oil (Part 1)
There has been considerable press coverage this week about a new PwC report on the future of North Sea Oil.
With an estimated 30 billion barrels still remaining, the sector has the potential for carrying on for several decades. This will be dependent, however, on fixing fundamental problems including lack of funding and new investment, lack of leadership and innovation, fragmented infrastructure, endemic cost inefficiencies and a growing talent shortage.
The report concludes that the industry has reached a ‘fork in the road’, with two years to fix fundamental problems before sliding into a ‘rapid and premature decline’.
As argued in previous blog posts, digital transformation is essential in preventing the rapid decline of an industry that still supports over 350,000 jobs across the UK. The effective use of digital technology can transform old ways of working, providing opportunities for significant improvements in productivity, cost effectiveness and competitiveness.
In this post we look at one key aspect of digital transformation namely, the critical role of data and predictive analytics in the survival and future growth of North Sea oil. Follow-up posts will examine the issues and challenges faced by operators in becoming data driven organisations.
The Data Explosion
Data has always been important in the oil industry with major technical decisions being made on the basis of large datasets generated by seismic software, visualization tools and other digital technologies. That data, however, is increasingly becoming ‘Big’. The volume, variety, velocity and veracity of industry data has moved to a different level.
Automation and cloud connected equipment, in particular, are leading to a data explosion in oil and gas. According to a recent report by McKinsey, successful oil and gas companies of the future will need to develop advanced analytic skills to derive actionable insight from the wealth of data being generated. The pervasive use of digital devices, sensors that collect and transmit data, new analytic tools and advanced storage capabilities are opening up exciting opportunities for major improvements in productivity, operational performance, safety, maintenance and associated cost savings.
Actionable insights derived from this ‘big data’ can lead to improvements across many value chain activities – exploration, development and production. A wide range of applications exist including modelling for seismic analysis, optimisation of production through real time feedback and flow analytics, automation of continuous processes, preventive maintenance, supply chain management, security, personnel and staffing, health and safety.
Oil industry leaders are already using analytical models to predict failures of critical equipment components with advanced analytics being used to integrate end-to-end production. Simulations to test failure scenarios in platform operations and the use of text mining to analyse unstructured input from engineers and operators are also being used.
One industry observer has described the data explosion in oil and gas as akin to a ‘professional Fitbit’ – using real time data to monitor performance to prevent ‘bad things happening’; to intervene and fix problems before they arise.
Data and the Bottom Line
A strong positive correlation exists between the effective use of data analytics and operational performance.
A 2014 study by Bain & Co concluded that analytic advantages could help oil and gas companies improve production by 6% to 8%. Companies with better analytics capabilities were twice as likely to be in the top quartile of financial performance in their industry, five times more likely to make decisions faster than their peers and three times more likely to execute decisions as planned.
Even small improvements in data driven productivity can have a big impact on the bottom line. In Digitizing Oil and Gas Production, McKinsey concluded that improving production efficiency by ten percentage points can yield a $220 million to $260 million bottom-line impact on a single brownfield asset.
The implication of this for the North Sea oil sector is clear – the effective use of data analytics to enhance productivity and reduce cost can significantly extend field life in an economically viable way.
‘Getting there’, however, is not without challenges. A typical offshore production platform can have more than 40,000 data tags, not all connected or used. New capabilities for manipulating, analysing and presenting this data, together with new decision support tools, are required to convert this complex flood of data into better business and operating decisions.
Part 2, to be published next week, will examine the challenges and obstacles in becoming a data driven operator.
As always, comment and feedback are very welcome.