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Harnessing the industrial Internet of things has arguably become the biggest strategic priority for industrial companies in the race to gain competitive advantage through digital transformation.

Equating data to oil might make sense at first glance, given the data-driven success of tech companies, but the analogy breaks down as soon as you dig a little deeper.

Before the dream of a “subsea factory” can come true, a group of North Sea companies will need to see if the required technology is economically feasible to build.

The use of technology has helped ensure the profitability of the oil and gas industry despite a 50% fall in prices in 5 years. The key question, however, is whether the digital revolution can answer the sector’s biggest challenge: how to secure future production.

The November issues of SPE’s peer-reviewed journals SPE Reservoir Evaluation & Engineering and SPE Production & Operations include papers addressing data analytics and machine learning.

The bank funded some €2 billion in projects last year.

Microsoft announced that it will open an AI Center of Excellence for Energy in the United Arab Emirates—a global first for the company—to empower organizations in the industry in accelerating digital transformation and equipping their workforce with AI skills.

A proving ground for the use of digital twins has emerged in the North Sea. There, operators Total, Aker BP, and Shell have each developed and deployed twins that they expect to pay big dividends.

For the past 20 years, the diagnostic fracture injection test has been used across the frontlines of the shale revolution to paint a picture of what cannot be seen. However, that picture has not always been so clear in the eyes of subsurface engineers.

Nanotechnology has great potential to reduce cost, increase production, and even improve the sustainability of E&P operations. But, where do we stand in terms of potential vs. reality? And, is the industry ready and willing to use the technology?