HSE & Sustainability
Spain has granted permits covering a swath of the mountain range to Mantle8 for natural hydrogen and helium exploration a month after France granted the company similar permits.
Crude benchmarks spiked amid concerns that the US-Iran ceasefire is collapsing as commercial shipping comes under renewed attack.
This paper proposes a shift in the timing of risk modeling to much further back within the job life cycle, recognizing each function’s role in the mitigation of risk.
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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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Sustainable energy continues to grow as a focus for reliable, affordable, and secure energy as seen from the past year of papers reviewed for this feature. Three primary areas are being reported on heavily: carbon use for enhanced oil recovery, geological hydrogen discovery, and critical minerals from the subsurface.
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This study aims to systematically assess casing integrity and corrosion risks associated with CO2 injection in oil-recovery operations.
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This paper explores the development of direct-lithium-extraction technologies designed to recover lithium from unconventional feedstocks.
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This study applies Monte Carlo simulation and an XGBoost regression model to assess the influence of various formations, geologic provinces, tectonic-plate types, and boundary conditions on hydrogen concentrations.
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Ultradeepwater prospects along the northern coast of Brazil could help offset decline in legacy basins, though permitting hurdles remain a wild card.
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This paper reviews a proof-of-concept project in which surplus casing pipes were used in the fabrication of purposefully designed artificial reef structures for the enhancement of biodiversity and commercial fisheries.
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This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
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This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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