Reservoir
EY reports an 11% decline in reserve additions and the first sub-100% reserve replacement ratio since 2021, even as crude output climbed.
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With operators under pressure to deliver more energy with fewer resources, predictable drilling performance is more important than ever. Discover how a unified digital workflow can turn drilling data into better decisions and consistent execution—providing the foundation for autonomous drilling and more predictable, profitable, and productive wells at scale.
The shale revolution, the Paris Agreement, and the global pandemic each transformed energy markets. Now, industry leaders say energy pragmatism is emerging.
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This case study describes how edge computing and industrial internet of things platforms were deployed to automate and optimize production operations across four distinct basins. -
Output is rising fast in the South American shale play and putting Argentina on a course to soon reach 1 million B/D.
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This case study presents a procedure in which the operator compared production from wells with adjusted wettability to a control group, finding that the adjustments resulted in significant improvements in production and reductions in produced water.
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Bridging the gap between foundational guidance and real-world application, SPE’s Oil and Gas Reserves Committee is advancing PRMS education with a new, peer-reviewed training initiative. This article highlights the evolution of the PRMS knowledge base and introduces the PRMS Training Master Slides—a modular, instructor-led framework designed to improve consistency, cl…
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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 study that confirms glass-reinforced-epoxy-lined tubing as a reliable, cost-effective solution for long-term water-injection service in moderate-salinity offshore environments.
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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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This year’s selected papers showcase meaningful advances across condensate‑rich tight gas, tight sandstone, and coalbed methane reservoirs, each contributing new tools for improving predictability and field-development efficiency.
