Data & Analytics
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This paper presents the large-scale deployment and operational integration of an advanced, automated rheometer in the Ghawar gas field, one of the world’s most prolific and technically complex hydrocarbon developments.
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
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Schlumberger and Dataiku have entered into an exclusive technology partnership that will enable companies in the exploration and production industry to build and deploy their own artificial intelligence solutions across the full breadth of their upstream work flows. -
The December issue of the peer-reviewed SPE Journal includes a spotlight section on data analytics, presenting paper SPE 195698, “Prediction of Shale-Gas Production at Duvernay Formation Using Deep-Learning Algorithm.”
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Companies should disclose instances of cyber-enabled intellectual property theft. Disclosure requirements would give companies greater incentives to protect their intellectual property and allow investors to make better-informed decisions.
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The organization said the new standard, which focuses on air safety and data protection, is the first step in a wider move to promote the use of drones within a framework of approved regulatory compliance.
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Rovco’s stereo camera technology system sends images and 3D models of assets from the seabed to computer browsers in any location, offering users instantaneous access to information during inspection or construction.
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The two main takeaways from this paper: First, it underscores the difference between explainability and interpretability and presents why the former may be problematic. Second, it provides some great pointers for creating truly interpretable models.
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To make sure deep learning meets its promise, we need to reorient research away from state-of-the-art accuracy and toward state-of-the-art efficiency. We need to ask if models enable the largest number of people to iterate as fast as possible using the fewest amount of resources on the most devices.
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The media is often tempted to report each tiny new advance in a field, be it artificial intelligence or nanotechnology, as a great triumph that will soon fundamentally alter our world. Occasionally, of course, new discoveries are underreported.
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In an increasingly data-dependent sector, oil and gas companies need to scale up their use of technology across the enterprise rapidly. Success will involve reframing the CIO’s role in driving not only digital transformation but also business outcomes.
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Unless we work together to resolve the underlying causes of data problems, we will continue to struggle with the time and effort needed to get the foundations of data preparedness sorted out. That means that industry must accept that data is strategic rather than tactical.
