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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Oil companies are talking big about using data and analytics, but the experts in the field are not sure what their role will be. Birol Dindoruk, SPE's technical director for management and information, talks about ensuring that they have a say. -
A new geostatistics modeling methodology that connects geostatistics and machine-learning methodologies, uses nonlinear topological mapping to reduce the original high-dimensional data space, and uses unsupervised-learning algorithms to bypass problems with supervised-learning algorithms.
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Artificial intelligence has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry’s 150,000 US workers.
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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.
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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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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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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.
