Data & Analytics
With the latest addition, the Italian major’s computational capacity passes the exaflop threshold, making the firm the world’s leading company by computing power in the new TOP500 global ranking.
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
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According to a World Economic Forum report, digital transformation in the oil and gas industry could unlock approximately $1.6 trillion of value for the industry, its customers, and wider society while creating around $1 trillion of value for oil and gas firms. -
Start-and-stop data management initiatives and a mishmash of partial solutions are no longer viable for managing the digital oil field. Data management should be transformed from a cost center to a cash-flow-generating function.
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Technology is advancing, and applications are growing, but scaling faces technological and human challenges.
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Algorithms are taking over the world, or so we are led to believe, given their growing pervasiveness in multiple fields of human endeavor such as consumer marketing, finance, design and manufacturing, health care, politics, and sports. The focus of this article is to examine where things stand in regard to the application of these techniques for managing subsurface en…
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Artificial intelligence is opening new ways to analyze data from microseismic events that occur during hydraulic fracturing. One researcher at Moscow’s Skolkovo Institute of Science and Technology is building a convolutional neural network to get a subsurface view of permeability after fracturing.
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The cultural perception of AI is often suspect because of the challenges in knowing why a deep neural network makes its predictions. So researchers try to crack open this black box after a network is trained to correlate results with inputs. But what if the goal of explainability could be designed into the network's architecture, before the model is trained and withou…
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Using a method called quantum annealing, D-Wave's researchers demonstrated that a quantum computational advantage could be achieved over classical means.
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The Environmental Defense Fund's report called "Hitting the Mark" is a roadmap for the oil and gas industry to obtain and report good data on methane emissions. But it also laments that methane emissions data are outdated, inaccurate, and unreliable.
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The deal fills a gap in the software developer's production line that is focused on drilling, production, and land management applications.
