Data management
The country expects the digitalization project to promote Egypt’s exploration and production potential worldwide.
Murphy Oil has created a work flow to normalize the tags it uses when collecting data on its hydraulic fracturing stages. The work flow described here empowers decision makers, who no longer wait for hours to collect data or waste hours cleaning and preparing data for analysis.
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How can the famous Casino-inspired trick for data science, statistics, and all of science be done in Python?
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Over the years, I’ve noticed interesting cultural differences between industrial sectors in their approach to dealing with staff software training. Here, I’ll try to synthesize them into a major insight and expound on the implications.
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Industrial robots are becoming an increasingly popular choice in a variety of industries for different applications. Going by responses to a McKinsey and Company survey, up to 88% of businesses worldwide intend to adopt robotic automation into their infrastructure.
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AI-driven technology in the form of digital twins is helping companies reduce costs as they reopen after the COVID-19 lockdown, says a report from research and advisory company Gartner.
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The partnership between the software company and Texas A&M’s Department of Petroleum Engineering provides students with access to software that can enhance reservoir research with machine learning.
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2020 is finally ending. While not likely to register as anyone’s favorite year, 2020 did have some noteworthy advancements, and 2021 promises some important key trends to look forward to. A collection of experts presents thoughts on the past year and predictions for the year to come.
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Geoscience data companies CGG, PGS, and TGS announced a strategic partnership to offer a shared ecosystem providing direct access to their subsurface multiclient data libraries.
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What happens when proactive regulations get ahead of our ability to gather and understand data? Are you guilty before being proven innocent or even being aware of what the data is saying? Are oil and gas operators on the defensive before they even get started with new regulations?
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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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As data management (DM) moves from priority to imperative status in the beleaguered upstream industry, growing gaps between DM-mature and DM-immature organizations will determine future leaders.
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