LNG
Mozambique is poised to become Africa’s third-largest exporter of liquefied natural gas when Coral Norte comes onstream in 2028.
This paper focuses on developing a model that can be used in an automated, end-to-end flare-smoke detection, alert, and distribution-control solution that leverages existing flare closed-circuit television cameras at manufacturing facilities.
Angola expects an 18% rise in natural gas production by 2030 as global producers invest in offshore exploration and new field development.
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BW Opal FPSO has capacity for 850 MMcf/D of gas, which will be treated and sent on to the Darwin LNG facility, and 11,000 B/D of condensate, which will transferred via tanker. -
Train 4 is expected to add 6 million tonnes per year of capacity to the South Texas liquefied natural gas project when it goes online in 2030.
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Louisiana-based project will use operator’s Optimized Cascade process to turn feed gas into LNG.
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The floating liquefied natural gas ship Hilli Episeyo, currently offshore Cameroon, is planned for upgrades before redeployment to Argentina.
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As a champion of floating natural gas liquefaction technology, Eni is positioning itself to play a major role in Africa with a fast-growing gas-liquefaction capacity targeted to reach 14 million tonnes per year by 2028.
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NewMed has targeted the fourth quarter of 2025 to declare a final investment decision (FID) on Phase 1B of the Chevron-operated Leviathan gas project expansion after striking Israel’s largest ever gas export deal.
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TotalEnergies, Global Infrastructure Partners, and NextDecade divvy up Train 4 stakes ahead of an expected FID in September.
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The Japanese company ratcheted up the competitive nature of contracting for a floating production, storage, and offloading vessel and an onshore liquefied natural gas plant for the Abadi project by announcing dual front-end engineering design (FEED) contracts.
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This paper addresses how close collaboration has enabled the development of a robust and cost-efficient solution for the Ormen Lange project by using carefully selected technology elements and an accelerated qualification process to mature them.
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This study aims to use machine-learning techniques to predict well logs by analyzing mud-log and logging-while-drilling data.
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