Reservoir
Production from the Búzios field now tops 1 million B/D with six floating production systems in operation and more on the way.
Geophysicist Markos Sourial discusses advances in seismic imaging, the challenges of modern data processing, and what they mean for the next wave of subsurface professionals.
A new Eni/Petronas venture is targeting 500,000 BOE/D in output from combined upstream portfolios across Malaysia and Indonesia.
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This paper describes installation of autonomous inflow control valves in the Bretaña Norte field in Peru, enabling effective water control even though the trial well was placed in the flank, close to the oil/water contact.
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This paper presents a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight-reservoir forecasting.
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Shale Ingenuity’s first pilot used common natural gas liquids to boost daily output 30-fold from a low-producing horizontal well in Texas.
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This paper discusses the approach used to sectorize a mature giant carbonate reservoir located onshore Abu Dhabi for the purposes of reservoir management, offtake, and injection balancing.
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The Energy & Environmental Research Center in North Dakota outlines the difficulty that the oil and gas industry faces in pinpointing sources of H2S production.
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Oil and gas leaders identified the upcoming US presidential election and economic uncertainty as significant drivers of their decision making for 2025.
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Over the past 75 years, drillers have gone from the Stone Age to the Space Age when it comes to technological improvements in well construction methods. Yesterday’s crude wood and iron drilling techniques have given way to today’s video game-inspired controls and robotic assistance—much of which migrated from offshore applications. These advancements have driven costs…
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A new plan to secure electricity for the powerhouse of Texas oil and gas will cost billions of dollars to achieve.
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New names and new deals continue to reshape the US shale sector.
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This paper presents a novel modeling framework for predicting residual oil saturation in carbonate rocks. The proposed framework uses supervised machine learning models trained on data generated by pore-scale simulations and aims to supplement conventional coreflooding tests or serve as a tool for rapid residual oil saturation evaluation of a reservoir.