Onshore/Offshore Facilities
The Absheron gas field expansion will supply additional natural gas to Azerbaijan’s domestic market and support its export commitments to Turkey, allowing Baku to stay focused on meeting its gas export obligations to Europe.
A credible custody-transfer record depends on far more than the accuracy of a single meter. It is the product of an integrated measurement chain. While meter performance supports measurement-system integrity, commercial confidence also depends on traceability, governance, and authorization.
Despite significant progress in capturing associated gas for domestic use, Iraq remains the world’s third-largest gas-flaring country as it aims for higher oil and gas production targets.
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Subsidies lapse while others take hold in a bid to bolster offshore wind energy capacity around the globe. -
Why you should be cautious about using today’s higher inflation rates in your asset-retirement calculation.
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The export project in the US Gulf of Mexico could handle up to 13 mtpa of liquified natural gas.
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This paper presents a review of virtual reality (VR) in the oil and gas industry through the development of prototypes. The objective was to establish a learning experience and knowledge about VR’s main features, hardware, software, and applications; evaluate the capabilities of various VR solutions in the context of field operator and maintenance training; and develo…
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Software company FutureOn and consulting firm Wood are working together on an enhanced digital service for asset operators.
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Design, construction specialist books new work in the Middle East, Australia, and Saudi Arabia.
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The acquisition gives Enterprise’s natural gas and NGL business an entry point into the Midland Basin.
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New projects coming on line throughout the year will vault the nation ahead of Australia and Qatar.
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The authors present an artificial-intelligence and machine-learning technology to obtain a high-level, comprehensive view of all equipment in a facility to detect and map corrosion.
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This paper describes a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.
