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.
This study demonstrates the transformative potential of physics-informed neural networks as a hybrid framework for multiphase flow measurement.
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Geolog and Petro.ai announced a strategic partnership to deliver data science products and services to the global energy industry. -
An automated detection application helped identify stringers early for an operator of a mature field in the North Sea while drilling multilateral wells through reservoir sections containing hard calcite stringers interspersed in sand formations with low unconfined compressive strength. The application guided drilling decisions that minimized invisible lost time and sh…
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SPE has established three new technical sections—the Management Technical Section, the Methane Emissions Management Technical Section, and the Data Science & Engineering Analytics Technical Section.
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With a holistic approach to building the digital thread and digital twin, companies can realize improvements in project execution, operational efficiency, sustainability, and revenue.
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With so much volatility in the sector, acutely felt by many western consumers, how are intelligent work flows enabling the shift toward alternatives?
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Among other things, Microsoft is making it possible for Exxon to analyze reams of oilfield data. Amazon is helping drillers run simulations to maximize how much oil they can pump from existing wells.
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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 …
