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Big data needed for big oil: experts
Peter Coveney, right, Director of Centre for Computational Science at University College London speaks during a conference at AUB in Beirut, Friday, Dec. 6, 2013. (The Daily Star/Hasan Shaaban)
Peter Coveney, right, Director of Centre for Computational Science at University College London speaks during a conference at AUB in Beirut, Friday, Dec. 6, 2013. (The Daily Star/Hasan Shaaban)
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BEIRUT: As Lebanon gets ready to host a surge of oil industry giants to bid on drilling contracts next month, experts are warning that if it doesn’t focus on big data and educate its workforce on how to use it, the country could miss out on its potential as a serious player in the oil sector.

“There’s a growing importance of technology in oil and gas – in sensors, storage, connectivity, processing, and performing dangerous and high-cost tasks,” said Stefano Martinotti, partner at the management and consulting firm McKinsey & Co. Abu Dhabi, speaking Friday at a conference on the significance of big data.

The concept of big data involves the collection of large and complex data sets with a high variety and quick changes that are difficult to process using traditional applications – IT and computer infrastructure in oil exploration and drilling.

The most recent assessment indicates that there may be as much as 25 trillion cubic feet of gas off the coast of Lebanon.

“It’s about the real-time use of data executed on the front line,” he said. “But the most important success factor is human judgment.”

The all-day conference, “Big Data, Big Computing and the Oil Industry: Opportunities for Lebanon and the Arab World” in collaboration with the University College London was held at AUB’s engineering department on the sidelines of the three-day oil and gas summit in Beirut. It brought together international experts from the energy and IT sectors to discuss the significance of complex and vast data sets that are becoming increasingly important for oil and gas exploration, as the world’s “easy” oil sites dry up.

Royal Dutch Shell, for example, is spending an average of 650 million pounds ($1 billion) annually compiling big data to analyze large numbers of sites.

The company has put “technical and competitive IT” at the heart of the business, making Shell’s algorithms around 100 times more effective.

Meanwhile, British Petroleum has what it says is the world’s largest supercomputer for commercial research in a 10,000-square-meter data center, with the capacity to reach 2.2 petaflops, which would take 100,000 average PCs to replicate. BP primarily uses it to focus on seismic and geophysical research. Installed in Houston, it serves as a worldwide hub for its data portfolio.

Keynote speak Peter Coveney, director of the Center for Computational Science at UCL, noted that the potential value for big data is $300 billion in the United States health care system and $400 billion in Europe’s public sector administration. Given the demands, the job market will need 140,000 to 190,000 more deep analytic talent positions and 1.5 million data-savvy managers “to take full advantage of big data in the United States.”

Throughout the world, the need for big data and workers who know how to analyze it is growing exponentially in all disciplines – from medicine to finance to energy – and Lebanon is no exception.

“In this complex and real world, there is a need for IT experts,” American University of Beirut provost Ahmad Dallal said.

Still, even as the experts confirmed the need for serious training in big data analysis and training, questions still remain about issues of corruption, the lack of even reliable basic infrastructure in Lebanon, and even about the willingness to train a workforce that is ready develop big data.

Speaking during a coffee break, Coveney, questioning Lebanon’s culture of innovation, said, “It’s not enough to be able to analyze big data. People need to be leaders and creatively break through big problems.”

 
A version of this article appeared in the print edition of The Daily Star on December 07, 2013, on page 4.
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