Data & Analytics
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This paper presents the large-scale deployment and operational integration of an advanced, automated rheometer in the Ghawar gas field, one of the world’s most prolific and technically complex hydrocarbon developments.
Case studies from Devon Energy, ConocoPhillips, and others show how clever engineering and technology are being used to improve recovery and asset value.
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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. -
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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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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More energy and engineering companies participate in second Industrial VR/AR Forum.
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As part of the deal, Pertamina is moving all of its petrotechnical applications to the iEnergy cloud service, which is run by Halliburton arm Landmark.
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The term “edge computing” may be relatively new, but the concept is not.
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Easily accessible data can help field workers do their jobs more safely and efficiently. A new paper by Cognite and Aker BP explores how to manage this digital transformation.
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i-Tech 7, Subsea 7’s life-of-field business unit, and Shell International E&P have entered into a collaborative technology agreement to accelerate subsea digitalization, initially for a period of 5 years from the fourth quarter of 2019.
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Egypt Upstream Gateway, a national project for digitizing subsurface information and delivering a digital subsurface platform, will build on Schlumberger’s GAIA digital subsurface platform.
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Despite getting less attention, the systems-level design and engineering challenges in machine learning are still very important. Creating something useful requires more than building good models; it requires building good systems.
