Data & Analytics
On long-term trends, most things in the world are getting better, but gradual improvements don't make the news.
Subsurface modeling and history matching are critical steps for driving decisions. Generative artificial intelligence can support these efforts by incorporating various sources of information and allowing for low-dimensional parameterization for history matching.
TWA editors met with Satyam Priyadarshy, a technology fellow and chief data scientist at Halliburton, about how young professionals can prepare themselves for the application of data science in their work and how to approach problems and challenges.
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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. -
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.
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The oil and gas industry is facing an invasion of data analytics startups who saw a wide-open gap in the market a few years ago when talk of big data first began.
