Environment
H2Teesside is expected to be one of the UK’s largest low-carbon hydrogen production facilities, targeting 1.2 GW of low-carbon hydrogen production, which equates to more than 10% of the UK’s 2030 hydrogen production target.
The environmental analysis found no significant effects from issuing leases.
Transition requires action, not perfect technology, but challenges remain around scalability, cost, and revenues.
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The aim of this study is to address and discuss the reservoir engineering aspects of geological hydrogen storage. -
This paper examines the shortfalls of current CO2 capture and storage measures and their future within the context of increasing global consumption of fossil fuels.
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A seismic prediction model is developed and presented in a case study to simulate the magnitude and timing of triggered seismic events with the intent to manage and mitigate environmental impacts resulting from induced seismicity during subsurface development activities.
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Applications are open for the funding, which comes from the Inflation Reduction Act, for projects that help monitor, measure, quantify, and reduce methane emissions.
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This paper presents efforts to reduce greenhouse-gas emissions and increase energy efficiency through the use of a real-time monitoring tool on exploration and production operated assets.
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The exercise at Vineyard Wind’s Marine Coordination Center successfully evaluated Vineyard Wind’s ability to activate an incident management team and carry out the procedures in their approved oil spill response plans.
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The objective of this study is to use expired medications as green corrosion inhibitors that can be used during stimulation treatments. Because the medications are expired and not fit for human consumption, the cost is inherently low.
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This article explores the implementation of artificial intelligence vision for leak monitoring automation in the oil and gas industry and its role in improving safety standards, operational efficiency, and environmental performance.
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This paper investigates the use of machine learning to rapidly predict the solutions of a high-fidelity, complex physics model using a simpler physics model.
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Definition and call for participation in the 11th Society of Petroleum Engineers Comparative Solution Project, which is motivated by the immense challenge of achieving geological carbon storage at a scale that impacts significantly atmospheric emission of carbon dioxide.
