Reservoir
The UAE project is expected to produce up to 345 MMscf/D by 2029, with expansion potential to 1 Bcf/D.
This study investigates the potential for in-situ hydrogen generation from hydrocarbons using in-situ combustion, with particular emphasis on the role of kerogen content and heating mode.
This paper presents the application of degradable particulate-diverter technology to improve oil production by effectively diverting stimulation treatment fluids away from high-water-cut, high-permeability, high-temperature producing intervals or zones.
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The operator’s deepwater discovery in the Gulf of Mexico is potentially commercial, and government analysis indicates the gulf holds 1.3 billion BOE more reserves than estimated. -
The test marks a milestone in the Poseidon CCS project, which aims to store carbon dioxide in the depleted gas reservoir below the Leman development in the southern North Sea.
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The company credited its theory of shale oil enrichment for the significant increase in the quantity of proven reserves at the field.
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In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
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This work investigates the root cause of strong oil/water emulsion and if sludge formation is occurring within the reservoir using a robust integrated approach.
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This study presents a production-optimization method that uses a deep-learning-based proxy model for the prediction of state variables and well outputs to solve nonlinearly constrained optimization with geological uncertainty.
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In this work, a perturbed-chain statistical associating fluid theory equation of state has been developed to characterize heavy-oil-associated systems containing polar components and nonpolar components with respect to phase behavior and physical properties.
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The paper describes a parameter inversion of reservoirs based on featured points, using a semi-iterative well-test-curve-matching approach that addresses problems of imbalanced inversion accuracy and efficiency.
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This paper aims to present thoroughly the application of subsurface safety injection valves in extremely high-temperature environments.
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These three papers leverage machine learning and hybrid methods to tackle challenges in forecasting, optimization, and reservoir characterization.
