Reservoir
In a study that applied alternative carbon carrier technology to enhanced oil recovery (EOR) scenarios, researchers at The University of Texas at Austin found that the new method recovered up to 19.5% more oil and stored up to 17.5% more carbon than conventional EOR methods.
This paper presents a novel methodology for assessing the rapid mineral carbonation of carbon dioxide through geochemical interactions with carbon-, magnesium-, and iron-rich minerals abundant in geological formations.
This study assesses the advantages, constraints, and necessary enhancements of both passive and active electromagnetic techniques in the context of carbon capture and storage.
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This paper presents a numerical simulation work flow, with emphasis on hydraulic fracture simulation, that optimizes well spacing and completion design simultaneously. -
Recent studies have reignited the question of whether US oil and gas companies are ignoring the opportunity to refracture large swaths of maturing assets.
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This paper describes the deployment of an ultradeep electromagnetic directional-resistivity instrument to map injection-water movement.
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The authors discuss the development of a deep-learning model to identify errors in simulation-based performance prediction in unconventional reservoirs.
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The authors of this paper compare case studies from the Bakken and the STACK plays to conclude that mineralogy, petrophysics, and reservoir-condition differences between basins cause differences in the effect of fracture-driven interactions.
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This paper shares details of 2 years of monitoring the first commingled updip smart water injector drilled in the Piltun area of the Piltun-Astokhskoye offshore oil and gas field.
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In this second part of a two-part series on advances in artificial lift, we’ll look at the state of optimization and a trio of techniques and technologies under development or new to the market. Look for quarterly reviews of specific types of lift in upcoming issues in the new year.
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This paper describes a high-density high-pressure/high-temperature brine-based drilling fluid that provides long-term stability and solids-suspension properties for extended periods of time.
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Understanding the injected-water preferential paths is a key aspect of waterflood optimization in reservoirs characterized by strong vertical and areal heterogeneities. Devising specific work flows for such applications is important.
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This paper discusses a waterflood optimization system that provides monitoring and surveillance dashboards with artificial-intelligence and machine-learning components to generate and assess insights into waterflood operational efficiency.
