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 complete paper presents a discussion of the use of intelligent well completion in Santos Basin Presalt Cluster wells. -
In partnership with TechnipFMC, DNV GL opened a pilot project for the international collaboration of operators and the supply chain. Many digital twins represent an asset’s initial form and struggle to reflect developments in their physical counterparts as the asset matures.
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Edge—or, in-field, device-level—computing is being driven by the need for data from individual wells to be analyzed and processed at the wellsite instead of in data centers for early and accurate decision making.
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Immersive technology on projects such as wellsite planning incorporates XR, drones, and collaboration.
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Production monitoring requires heightened degrees of precision and efficiency as operations are streamlined and projects are evaluated continuously. This month’s feature focuses on innovative technologies that have been implemented in environments ranging from the Gulf of Mexico to China.
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This paper describes a virtual metering tool that can monitor well performance and estimate production rates using real-time data and analytical models, integrating commercial software with an optimization algorithm that combines production and reservoir information.
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This paper discusses the effectiveness of third-generation (Gen3) production-logging-tool (PLT) technology, which uses co-located digital sensors for simultaneous acquisition of flow data to provide the most accurate characterization of the flow condition at each depth surveyed.
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This paper describes an accurate, three-step, machine-learning-based early warning system that has been used to monitor production and guide strategy in the Shengli field.
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The seismic-data company has announced the completion of its offshore Peru 2D and 3D seismic data set, consisting of 19 rectified and merged 2D seismic surveys and 21 rectified and merged 3D seismic surveys.
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In my inaugural column as editor of the Well Testing Technology Focus feature, I want to shine a light on the notable trend among operators of seizing on the tremendous untapped potential that exploration and appraisal wells represent for far-field reservoir characterization and connectivity.
