WHITEPAPER: The ‘data crunch’ – how oil and gas executives could use ‘Big Data’ as a powerful source of competitive advantage

A recent report published by Sia Partners UK argues that major oil and gas companies risk missing out on the performance potential data and ‘big data’* offer unless they better manage their information. According to the oil and gas management consultancy, many oil and gas companies are ‘borderline irresponsible’ in how they maintain their existing data, despite the billions they spend on it.

The company argues that better valued and managed data will afford executives and investors greater certainty on strategically important measurements crucial to executive decision making, such as the Reserve Replacement Ratio (RRR).

Molten Whitepaper The data crunch - how oil and gas executives could use 'Big Data' as a powerful source of competitive advantage 1200x500

Released today, the report illustrates a sector that relies on data for critical decision making but fails to treat it as a valuable asset. The scale of the issue is considerable given that each year typical supermajor oil and gas companies will invest between one and three billion dollars in data acquisition – a significant sum even for a sector where big numbers are commonplace. Yet the annual spend on maintaining this asset is low – often significantly lower than 1% of the acquisition cost.

Colin Frost, partner at Sia Partners UK, said: ‘Companies within the oil and gas sector face increasing pressure to make quick, effective decisions if they are to maintain production momentum and high levels of performance. As a consequence, they are becoming highly dependent on data, and more recently “big data”, to support these critical decisions. Paradoxically, recognising the value of this data and the need to manage it as a valuable asset is not so widely accepted at an executive level. Unchecked, the relationship is one that could possibly lack reward and, at worst, prove unsustainable.’

With technology driving data growth at an exponential rate, oil and gas companies need to be prepared to receive and manage ‘big data’ alongside considerable existing pools of information, if they are to harness its potential to fuel superior performance.  With the Final Investment Decisions (or FIDs as they are often known) that promote projects into production leaning on critical data and high level metrics, it is vital the information that underpins these decisions is well maintained. The report advocates that to be better prepared for the growth in data companies must formalise data governance and adopt better data management processes.

Sia Partners UK’s research, which examines the issues data management presents, shows that accuracy in data intensive measurements such as the RRR has increased – although at an average uncertainty rate of 10% it argues there is room and requirement for further improvement. The rewards in doing so are high, with those companies exhibiting greater maturity in data management achieving the highest performance in reserves replacement.

Colin Frost said: ‘A 10% error rate in RRR is deemed acceptable in the sector.  However, I think we need to question if this is level of error is appropriate. Demands are becoming more acute. Management teams are under pressure to keep momentum behind production, yet as an industry we’re saying it is OK to base decisions on measures such as these that can be prone to significant error. Clearly the nature of exploration and production means there will always be an element of error. Energy companies should do better and reduce the error rate to 7 – 8 % within five years. Big data offers us this opportunity but the key to producing better forecasts is better data and its management – and this will only happen when management teams better value the assets they have paid so much to obtain.’

* ‘Big data’ is a collection of complex data sets so large that they are often difficult to process using traditional database management tools or data processing applications. Among the challenges in managing these data-sets are access, analysis, capture, curation or maintenance, definition, secure deletion, presentation or visualisation, search, sharing, security, storage and transfer.

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