Digital Oil Field
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents a competency-centered, data-driven approach implemented to strengthen control-room emergency-response capability through a cloud-hosted, scenario-based virtual plant simulator.
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COVID-19 has significantly accelerated the adoption of digital technologies across all industries, and the oil and gas industry has been no exception. As such, interest in digital data acquisition, which is the backbone of all digital transformation work flows, also has increased significantly. -
The customizable Internet of things service is designed for monitoring onshore and offshore remote assets.
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The agreement will see Akselos become one of the global energy company’s verified suppliers for structural integrity assessments, forming part of Shell’s newly formed Digital Twin Platform.
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The AI partnership combines Wood’s optimization platforms with Cognite’s Data Fusion product to develop solutions for the energy transition and free up data from fragmented and legacy systems.
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A systematic approach to ensure quality assurance is intended to build confidence and accelerate the uptake of digital twins.
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New guidelines from the European Union Agency for Cybersecurity recommend that all stages of the IoT device lifecycle need to be considered to help ensure devices are secure.
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The success of any digital oilfield project is predicated on the quality of the data structure, acquisition, communication, validation, storage, retrieval, and provenance of the data.
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DNV GL and floating production, storage, and offloading (FPSO) vessel specialist Bluewater are undertaking a pilot project to use hybrid digital twin technology to predict and analyze fatigue in the hull of an FPSO in the North Sea.
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In addition to the well-recognized elements of digital transformation such as real-time monitoring, remote intelligence, and extraction of insights from data, there is a need to evolve the industry hardware through application of enhanced edge computing.
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A recent panel discussion highlighted the industry’s progress in achieving significant digital advances. Barriers remain, however, and the measurement of success is being defined in this evolving technological step change.
