Data management
Sponsored
Energy businesses want to reduce document-driven processes and replace them with digital workflows, but often don’t know where to begin. An Integrated Requirements Management approach has a swift time to value. It’s also a significant step towards applying a digital lifecycle mindset across the enterprise.
The recent cyberattack on Colonial Pipeline’s IT system has thrust the issue of oil and gas industry cybersecurity into the spotlight, which, according to specialists in the field, is where it should always be.
The new data-management platform is designed to increase access to energy data.
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SponsoredThe OSDU™ Data Platform has the potential to significantly increase the interoperability of E&P data. Find out how IHS Markit is supporting adoption of the standards-based data ecosystem through its Enterprise Data Management (EDM) for Energy platform. -
The paper discusses a methodology for integrating intelligent completion and production systems with a modeling and analytics framework for efficient development of fiber-optic-based data-interpretation services for complex downhole environments.
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Smaller and independent upstream companies often have limited resources for data management. Nonetheless, their data are valuable and must be managed for that value to be realized. Geologists may just be in the perfect position to do the job, if they can get the training.
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The digital repository will use a hybrid cloud architecture to provide subsurface data for the Norwegian Petroleum Directorate.
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SponsoredRead the latest research about data management's role in supporting digital transformation in the upstream industry.
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The market may be different from what we have previously experienced, but the path to a successful digital transformation is durable and the core principles of success have not changed.
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The country expects the digitalization project to promote Egypt’s exploration and production potential worldwide.
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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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