Technology
In the final part of this three-part series, we extend our learning of Part 2 to the multivariate model and train a single model to predict three outcomes: oil, gas, and water.
This article focuses on the introduction of one of the flow-network-based models called GPSNet that has growing popularity in the literature and shows promising results during our proof-of-concept applications.
In Part 2 of this three-part series, we dive into a practical example using the production data of Equinor’s Volve field data set.
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In Part 1 of this three-part series, we use long short-term memory (LSTM), a machine learning technique, to predict oil, gas, and water production using real field data.
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Explore the history of Howard Hughes Sr., inventor of the two-cone roller bit, in Part 1 of this two-part series highlighting the Hughes family legacy in the oil and gas industry.
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Register today for the SPE AI Hackathon taking place 7–9 May in Dubai.
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This article provides an overview of risk-based measurement, monitoring, and verification (MMV) for efficient, long-term CO2 storage.
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This article provides a mirror between the past and the present of well intervention technologies, including R&D to advance to downhole robots and autonomous intervention methods.
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Explore upcoming successors in energy storage technologies in Part 2 of this series.
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Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.
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These seven open-source simulators are available for free use and are among the best available in the industry.
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Dan Jeavons, Shell’s VP of computational science and digital innovation, discussed the findings in MIT’s recent report on digital technology’s impact on a net-zero emissions future with Aman Srivastava, TWA deputy editor in chief.
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The free online calculators will provide industry professionals with the opportunity to make energy processes more efficient.
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