Digital Transformation
The company is investing $1 billion to establish the Engineering and Innovation Excellence Center (ENGINE) in Bengaluru, India.
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.
Join TWA Editorial Board member Mani Bansal as he interviews Ashish Fatnani, an industry professional with 12 years of experience working for companies including Halliburton, ONGC, and Mercedes Benz.
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IoT is the next step in the evolution of the oil and gas industry. Changes have already begun in the field installations, in the corner office, and across the oil and gas value chain. -
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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Drones can access remote locations easily and can be used in the upstream and midstream industries for inspections, which can lead to reduced maintenance work.
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A look at the universities, startups, and multinational corporations in Silicon Valley, California, which are applying data science and predictive modeling for oilfield management.
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This article offers a four-part framework for critical infrastructure organizations looking to overcome the skills gap and create a strong cybersecurity workforce.
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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.
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A newcomer in the arena of oilfield market research has set an ambitiously high bar for itself: to speed up the oil and gas industry’s widely acknowledged and painfully slow rate of technology adoption.
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The use of intelligent software is on the rise in the industry and it is changing how engineers approach problems. A series of articles explores the potential benefits and limitations of this emerging area of data science.
