Data & Analytics
With the latest addition, the Italian major’s computational capacity passes the exaflop threshold, making the firm the world’s leading company by computing power in the new TOP500 global ranking.
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.
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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Trials of the robotics company’s Hydronaut and Aquanaut system are expected in the third quarter of 2022 after the companies conducted a successful feasibility study.
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The Russian gas company announced that it will use locally source unmanned aerial vehicles to inspect its facilities and pipelines in the Yurkharovskoye field.
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Incorporating domain knowledge into your architecture and your model can make it a lot easier to explain the results, both to yourself and to an outside viewer. Every bit of domain knowledge can serve as a stepping stone through the black box of a machine learning model.
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The COVID-19 pandemic caused a major disruption to industry training programs and university geoscience courses as travel restrictions and lockdowns created the need for digital alternatives. Although virtual field trips had been gaining traction before the pandemic, the sudden need to replace physical field activities has driven a rising interest to allow geologists …
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This paper presents a work flow that has been applied to crossdipole sonic data acquired in a vertical pilot well drilled in the Permian Basin.
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This paper describes a new intelligent dosing technology to reduce liquid loading in an unconventional tight gas reservoir.
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This paper presents a mathematical analysis of how incorrect estimates of initial reservoir pressure may affect rate-transient analysis in ultralow-permeability reservoirs.
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In this work, novel physics-based models and machine-learning models are presented and compared for estimating permanent-downhole-gauge measurements.
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The paper describes a method to match reaction kinetics from coreflooding experiments.
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Drillers are working to find ways to break some bad data habits. Those problems can range from the use of multiple formulas to calculate mechanical specific energy to timekeeping systems where the clocks and the time records are often off.