Will Data Analytics Solve The Oil Crisis?

With a major restructuring necessary, how can data help?


Fracking, while highly controversial, has undeniably had a huge impact on the oil industry. United States domestic production has nearly doubled over the last six years, causing traditional big oil producers like Saudi Arabia to look for new markets to export their wares to.

This is easier said than done though. The economies of Europe and developing countries are weakening, and vehicles are becoming increasingly energy-efficient. This drop off is likely to continue, as companies invest huge sums in developing electric cars and governments attempt to wean their countries off fossil fuels. BP posted a $6.3 billion loss in the most recent quarter, and other firms such as ConocoPhillips are also laying off staff in huge numbers.

Oil companies, used to having things their own way, are now having to cut costs and manage their resources more efficiently than ever before. As part of the effort to do this, a report by Lux Research has revealed that many are utilizing data analytics - using smarter sensors and ‘Big Data’ to manage risks, cut costs by increasing efficiency, and increase revenues.

BP for one has embraced Big Data in response to its losses. The oil behemoth has been besieged by scandal in recent years, and is also liable for massive compensation payouts as a result of the Deepwater Horizon spill. It has now joined forces with GE and its software Predix, to get 650 wells connected. Each well will dump around half a million data points every 15 seconds into GE’s software for analysis, which can then be leveraged for a variety of purposes, especially in optimizing equipment efficiency. Hardware sensors also provide data backups for high-value measurements of equipment-performance data..

BP has also got a substantial amount of data power in-house, owning what it calls the world’s largest supercomputer for commercial research. The computer has 2.2 petaflops of computing power, which handles enough data to ‘fill 30 miles worth of 1 gigabyte memory sticks lined up end to end.’

Data analytics also enables the Internet of Things, which is becoming particularly important in the oil industry, helping to reduce the number of staff needed and removing many from extremely dangerous roles. Automation adds substantially to the upstream value chain of exploration, development, and production. But some of the biggest opportunities are in production operations, for example in reducing unplanned downtime. Given the oil and gas industry’s substantial increases in upstream capital investment, optimizing production efficiency is essential. Automation also helps to maximize asset and well integrity, increasing field recovery, and improving oil throughput.

Embracing data analytics does not completely remove the need for humans from decision making on oil fields. Creating a digital oilfield doesn’t just need algorithms. Companies must create a harmony between the two and use that harmony to their advantage, adjusting their recruitment policy and helping adapt the skills of those staff already in their roles, to develop a greater understanding of the data and how to use it.

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