Digital Oil Field
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.
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The objective of this paper is to illustrate a methodology for identifying the value of information (VOI) in reservoir management—in particular, for deriving the conditional probabilities of success when new and imperfect data are acquired. -
Initial development of inflow tracers was designed to provide qualitative information about the location of water breakthrough in production wells. The proof of concept and application for water detection initiated the development of oil tracers for oil-inflow monitoring.
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The technology will provide Equinor a continual feed of updated reservoir information from its Johan Castberg and Johan Sverdrup fields with the aim of improving well placement, production, injection, and—ultimately—recovery.
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A new event is kicking off in September that will bring together the brightest minds in digital tech and oil and gas.
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Harnessing stranded data will transform operations beyond what existing, siloed software solutions delivered. There is a clear need to be more agile and embrace cloud-based solutions to realize new capabilities.
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The goal is to support the development and sharing of best-practice approaches for project delivery and asset operations using cloud services and digital workflows in engineering and operations.
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Acquiring data from an abandoned subsea well has been done before, but never quite like this.
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Wearable computers are turning heads in the oil and gas industry and appear to be on a trajectory for widespread adoption.
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A producer and a service company have collaborated to develop a downhole system to merge multilateral technology and intelligent completions to create “smart laterals.”
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What I find impressive is the number of people who were hiding in normal discipline jobs who are coming out of the closet with their Python scripts. And, it’s working. In many ways, order is coming to the mess, efficiency is coming to tiresome manual activities, and richness is coming to decisions.
