
The revised report provides upstream oil and gas operators with a framework and guidelines to help select and deploy methane emissions detection and quantification technologies.
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Technology and partnerships play a pivotal role in how the oil industry finds and produces energy from frontier regions and brownfields, both now and in the future.
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Geothermal systems, which rely on extracting heat from deep within the Earth, face many of the same technical challenges that oil and gas operators have tackled for decades. Geothermal development can be advanced efficiently and economically by applying proven oil and gas technologies.
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Few things are more essential to the now global hydraulic fracturing revolution than access to fresh water, yet this dependency use has raised environmental concerns and operational challenges.
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The technology, which uses Industrial Internet of Things components, aims to reduce the costs and improve the safety of drilling operations.
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This paper presents a comprehensive synthesis of available research evaluating the influence of gamification on cognitive, motivational, and behavioral learning outcomes.
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The year, marked by a fatal accident in February, finished with a decrease in accidents and spills.
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The update is designed to improve the accuracy and completeness of reported data, reduce the time needed to complete the form, and support deeper understanding of equipment failures.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
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This paper analyses the Global Biodiversity Framework and its relevance to the transitioning energy system, documenting the work that has been completed and that which is still ongoing.
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This article is the second of a two-part series on produced-water management in the Gulf of Mexico and covers four themes: equipment, process configuration, operations, and effluent quality.
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The authors introduce a novel framework combining dynamic mode decomposition, a data-driven model-reduction technique, with direct data assimilation to streamline the calibration of carbon-dioxide plume evolution models.