Unconventional/complex reservoirs
As Africa’s top oil producer, Libya is ramping up momentum—offering 22 exploration areas and welcoming BP back to Tripoli with a major deal.
This study aims to thoroughly assess the influence of various completions, fracturing stimulation, and intrinsic reservoir properties affecting the productivity of 10 major unconventional plays while uncovering insights and trends unique to each play
This paper introduces new methods to perform reliable permeability and saturation-dependent relative permeability measurements in organic-rich mudrock core samples using a pressure-decay setup.
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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. -
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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This paper describes an optimized multizone single-trip gravel-pack system developed and implemented successfully in Brunei.
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This paper describes the qualification of a multilayer, open-cell matrix polymer system for the first horizontal deployment in an offshore gas well.
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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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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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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.
