HSE & Sustainability
This paper proposes a shift in the timing of risk modeling to much further back within the job lifecycle, recognizing each function’s role in the mitigation of risk.
This article from the SPE Methane Technical Section features Arvind Ravikumar of the University of Texas at Austin and focuses on how the Energy Emissions Modeling and Data Lab is integrating satellite observations, facility-level measurements, operational data, and emissions inventories into more credible methane accounting for oil and gas systems.
The firm’s latest analysis puts the bulk of the blame on a fragmented supply chain.
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The country’s Just Transition Summit, held in 2019, not only has set the groundwork for a stronger New Zealand on multiple fronts but also serves as an example for other countries and the international business community on how to create a shared roadmap for a sustainable society. -
The degree to which the world depends on oil and gas is not well understood.
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People and businesses alike are adapting processes and products to help ensure the activities we undertake and products we produce are sustainable for the future. Industrial lighting is no exception.
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Gas-capturing targets were met for most of the year as routine flaring drops to just 7.5% statewide and even lower in the Bakken Shale.
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Oilfield medics face long hours, grisly accidents, desolation, and low pay. So why do they do it?
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After an oilfield tank battery explosion killed a 14-year-old girl, Louisiana regulators have put new rules in place for the storage tanks and are launching a campaign to identify all of them statewide.
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Offshore Gulf of Mexico is becoming the destination of choice for international oil companies seeking new, low-carbon acreage to explore and develop.
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The US government is looking to size up efforts related to leak detection and repair practices.
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Moji Karimi, CEO of Houston-based startup Cemvita Factory, talks about the status of oil and gas investments in the emergent technology arena of carbon capture, utilization, and sequestration.
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The machine-learning techniques applied in this study aim to deliver a fouling-prediction model based on both simulation and real-time field data.
