HSE & Sustainability
A robotic arm, camera system, and virtual reality helped EniProgetti and the University of Naples researchers overcome the major challenges of direct-contact nondestructive testing using a drone.
Shell’s combination of digital worker technologies enables collaborative troubleshooting and inspections while reducing travel and boosting efficiency.
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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This article describes a technology combining a compression unit with a flexible line to offer a flaring alternative for transferring hydrocarbons. -
This paper explores the sustainability and safety aspects of laser perforation with a focus on factors such as water requirement, asset integrity, logistics, safety, and surface footprint.
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This paper describes an intelligent completion system in the context of multiple wells that, by electrifying the process, replaces the conventional electrohydraulic systems that have been in use for decades.
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This paper aims to provide insights to address the challenge of identifying the optimal point within the gas-processing lineup for recovering a high-purity CO₂ stream suitable for sequestration.
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TechnipFMC diver Stuart Cowie shares his 17-year experience working as a saturation diver in the oil and gas industry and how to manage mental health and well-being during the often isolating work demands.
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The company said that quitting its solar and onshore wind power generation projects in Brazil is part of a "portfolio adjustment."
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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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The first phase of the Norwegian project is expected to receive its first carbon dioxide this year, with the second phase slated to start operations in late 2028.
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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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