Data & Analytics
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
AI and machine learning are transforming drilling execution, detecting downhole problems earlier, automating reporting, and closing the loop between the wellbore and the well plan through real-time geosteering.
Robotic and autonomous systems are transforming energy operations, but their full value emerges only when paired with data science, engineering analytics, and AI/ML to turn data into decisions. The transition of the SPE Robotic & Autonomous Systems Technical Section into the SPE Data Science & Engineering Analytics Technical Section helps bridge this critical technolo…
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No longer considered a buzz phrase, cloud computing has made converts of the largest oil companies, and now the smaller ones are next. -
While sidetracking your career path is not an easy journey, the skills and knowledge gained in petroleum engineering education can be applied in other industries during the downturn.
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Many cybersecurity experts think the global malware attack on 27 June may have been an initial test run of a hybrid creation. If the term “wiper” is unfamiliar, you need to read this.
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AUVs aren’t limited to inspections and pipeline surveys. Deployment of a flotilla of AUVs to work on a project, and the communication among them, may someday lead to a subsea Internet of Things.
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Honeypots and pen testers. If these terms are unfamiliar, you’ll want to learn their roles in the safekeeping of critical evaluation and operational data in oil and gas activities, from the reservoir to the well pad to pipelines.
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Always recorded but almost never used, the water hammer signal could offer completions engineers another set of insightful data if petroleum engineers can crack its code.
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Figuring out the right price for an active oil and gas field is tricky business in the shale sector but one producer explains how it uses data analytics to get a clearer picture.
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Permian Basin producer Callon Petroleum is attributing its data-driven approach to a routine completions practice to improved proppant placement and higher oil production.
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The oil and gas industry has a lot to gain from the adoption of big data analytics as recently highlighted examples from major service company Halliburton demonstrate.
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Through data gathering, machine learning, and the use of a supercomputer, a non-profit organization in Texas is seeking to boost oil and gas production on land owned by the states’ two largest university systems.
