AI/machine learning
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.
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.
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.
-
A look at how policy, future workforce perception, and industry standards will shape energy companies in the near and distant future. -
How can AI systems incorporate processes mimicking the slower logic- and causality-based reasoning patterns of the left brain?
-
Tiny soil samples may contain as many as 300,000 species of microbial life, but a Netherlands-based startup has figured out that between 50 and 200 of them can tell an operator if a drilling location will hold oil and gas reserves.
-
Southwest Research Institute is working to improve the accuracy of pipeline leak detection using sensors, artificial intelligence, and deep learning.
-
As artificial intelligence makes a significant impact on various industries, an expert examines the roles it could play in streamlining oil and gas operations in the near future.
-
A consultant examines the ways in which artificial intelligence and machine learning solutions may have a significant impact on industry operations.
-
As the drilling industry improves its efforts to capture drilling operation activities in real time, it has generated a significant amount of data that drilling engineers cannot process on their own.
-
Young Technology Showcase—Top-Down Modeling: A Shift in Building Full-Field Models for Mature FieldsData-driven, or top-down, modeling uses machine learning and data mining to develop reservoir models based on measurements, rather than solutions of governing equations.
Page 47 of 48