Reservoir simulation
This article from the SPE Integrated Reservoir Management Technical Section (IRMTS) examines the closed-loop IRM approach, from insight to execution to learning, and the limits of technology-driven solutions.
This work applies fuzzy logic, a well-established artificial-intelligence technique, to quantitatively assess connectivity between injectors and producers in a giant presalt field in the Santos Basin of Brazil.
This paper presents a reduced physics-based model that accelerates the ability to screen infill-location optimization, using the fast marching method to maximize production for a reservoir with multiple realizations.
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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. -
This paper aims to showcase examples of how integrated analysis of surveillance data in the Azeri-Chirag-Gunashli field has improved reservoir understanding and informed reservoir-management decisions.
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This article from the SPE Research and Development Technical Section offers new insights to how the upstream industry can benefit from the emergence of quantum computing.
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The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
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Modeling solubility trapping at reservoir scale remains a key challenge for carbon storage projects. This study introduces a novel sub-grid convective mixing model, implemented in the Open Porous Media Flow simulator and applied to the SPE11 benchmark, that enables accurate prediction of carbon dioxide dissolution trapping in geological storage using computationally e…
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This study applies Monte Carlo simulation and an XGBoost regression model to assess the influence of various formations, geologic provinces, tectonic-plate types, and boundary conditions on hydrogen concentrations.
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This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
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This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
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This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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The current challenge in reservoir simulation extends beyond developing better models; it entails creating solutions that are faster, more responsive, and genuinely instrumental in guiding decision-making. The papers selected this year clearly represent this evolution.
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