Reservoir
This paper introduces a novel steam-sensitive flow-control device designed to restrict the production of steam and low-subcool liquids while allowing higher mobility of oil-phase fluids.
This paper describes the operator’s initiative to reduce greenhouse-gas emissions and recover additional hydrocarbon, monetizing it as sales gas, by integrating upstream and downstream gas facilities in a unified approach.
This paper demonstrates how the integration of multiphysics downhole imaging with machine-learning techniques provides a significant advance in perforation-erosion analysis.
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This study integrates laboratory testing with reservoir simulation to evaluate the effectiveness of autonomous inflow-control valves in managing late-life steam-assisted gravity-drainage production challenges. -
Steam-assisted gravity drainage (SAGD) technology continues to advance rapidly, driven by improvements in numerical simulation, inflow-control technologies, fiber-optic monitoring, and real-time production optimization.
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This paper presents a workflow that leverages a multiagent conversational system to integrate data, analytics, and domain expertise for improved completion strategies.
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Examples demonstrate how an Integrated Operations Center as a Service (IOCaaS) model, powered by artificial intelligence, reduced costs by 5% and increased production by 6% in Canada.
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This paper demonstrates the effectiveness of integrating dynamic gas separation with existing gas-avoidance methods within the same electrical submersible pump string to address these issues.
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The authors propose a deep-learning-based approach enabling near-real-time CO2-plume visualization and rapid data assimilation incorporating multiple geological realizations for predicting future CO2 plume evolution and area-of-review determination.
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The three featured papers illustrate how emerging computational methods—ranging from gradient-based optimization to data-driven proxies—are reshaping reservoir characterization, uncertainty assessment, and real-time decision support across diverse subsurface applications.
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In this study, forward simulation is executed by a commercial reservoir simulator while external code is developed for backward calculations.
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Findings from two new SPE papers argue that the tight-rock sector needs to rethink longstanding assumptions about how hydraulic fractures form underground.
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In this study, the authors propose the use of a deep-learning reduced-order surrogate model that can lower computational costs significantly while still maintaining high accuracy for data assimilation or history-matching problems.
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