Data & Analytics
Canada’s development of large-scale digital drilling core libraries and open geoscience data platforms follows approaches pioneered in Australia, particularly Western Australia, through decades of government investment in geoscience data collection and preservation.
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
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Expectations from data analytics in the upstream sector continue to evolve. Although the number and diversity of applications continue to increase, the adoption at the assetwide level faces well-known barriers and challenges. -
When you think of “data science” and “machine learning,” do the two terms blur together? This article will clarify some important and often-overlooked distinctions between the two to help better focus learning and hiring.
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Skybox Datacenters has signed a 15-MW lease with a client that will host a supercomputer in its Houston facility. The client expects the system to beat Summit, the US Department of Energy supercomputer that is currently considered the world’s fastest.
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The ability to predict the future to optimize operations has been the aim of oil and gas companies for some time. Could that time finally be here?
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Batch data processing is extremely challenging. It’s time-consuming, brittle, and often unrewarding. This story explores how applying the functional programming paradigm to data engineering can bring clarity to the process.
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Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in health.
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An increasingly buzzy term tossed around at industry events, “digital twin” is leveraging data analytics, machine learning, and artificial intelligence to improve efficiencies from design to decommissioning.
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The constant talk about the data-driven future of the oil and gas business poses a threatening question for some petroleum engineers: What do I need to know to ensure I have a job next year?
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Upstream oil and gas is well behind other industries when it comes to being digitally enabled. That said, there is an enormous amount of interest in and expectation around the benefits of digital solutions.
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The term digital oil field has become a buzzword in the oil and gas industry these days, with the mention of it bringing up pictures of computers, flashy screens, and programming to mind. In reality, the concept goes beyond these.
