Reservoir
As Egypt’s largest oil and gas investor, Eni is ramping up its 2026–2027 drilling campaign with new investments cross the Mediterranean offshore, Nile Delta, Western Desert, and offshore Sinai to strengthen the country’s role as a regional gas and LNG export hub.
The industry is no longer short of measurements; the real challenge is converting them into timely reservoir decisions that protect value. That challenge is becoming more urgent as the industry depends increasingly on mature fields and existing infrastructure. The selected papers show how this need is being addressed across different producing regions.
This paper presents a case study from a mature field redevelopment project where pulsed neutron logging was integrated with advanced reservoir modeling to improve the understanding of fluid-contact dynamics and optimize new horizontal well placement.
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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.
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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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In this study, forward simulation is executed by a commercial reservoir simulator while external code is developed for backward calculations.
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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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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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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 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.
