Emission management
Natural gas-powered electric fleets look to pave the way for the next generation of power generation.
This article describes a technology combining a compression unit with a flexible line to offer a flaring alternative for transferring hydrocarbons.
This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
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Last fall, European Space Agency satellites detected huge plumes of methane leaking from the Yamal pipeline that carries natural gas from Siberia to Europe. Energy consultancy Kayrros estimated one leak was spewing out 93 tonnes of methane every hour. -
The UK’s offshore oil and gas industry has committed to halving operational emissions in the next decade, confirming its pathway to becoming a net-zero emissions basin by 2050.
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Recommendations include changes to current forms and reports used to track flaring.
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Machine learning enables fast, cost-effective, and accurate methane emissions detection in remote areas.
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Tracking down fugitive emissions has traditionally relied on small-scale detection efforts. This new project seeks to buck the trend by covering the Permian Basin with sensors.
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Video shows a substantial share of oil and gas flares are unlit or faulty, revealing a previously overlooked methane source that could turn out to be one of the region’s biggest.
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Enough gas to supply 7 million homes is leaking into the atmosphere above oil fields in Texas and New Mexico, the largest plume of climate-change-driving methane pollution ever recorded over a US oil field, a new study from Harvard University and Environmental Defense Fund shows.
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The combined effect of COVID-19 and an ongoing oil price war has ushered in one of the worst downturns for the energy industry in modern history. Yet, a bright side is shining through; flaring levels in the Permian Basin have fallen sharply and will continue to decline, a Rystad Energy report shows.
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Methane, a powerful greenhouse gas, is leaking from industry sites at rates equivalent to the annual carbon emissions of France and Germany combined, a new analysis using satellite data shows.
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A system proposed by researchers at the University of California, Santa Barbara, uses hyperspectral imaging and machine learning to detect the specific wavelength of methane emissions.
