Digital transformation
In the final part of this three-part series, we extend our learning of Part 2 to the multivariate model and train a single model to predict three outcomes: oil, gas, and water.
Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.
These seven open-source simulators are available for free use and are among the best available in the industry.
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A recent datathon and the team that took home the grand prize help paint a picture of both the industry’s’ digital transformation and how oil and gas engineers are embracing it to navigate uncertain times.
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With much of the workforce cooped up at home for 8 months or so, tech skills are now a virtual necessity. Many of us have had to get increasingly tech-savvy in a hurry.
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Your career is yours to manage. Be approachable and be bold to be sure you are noticed virtually. Do not wait for the pandemic to pass.
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Analytics is a key untapped transformational lever that will drive a meaningful impact in the short-term and a core competitive advantage for companies in the long term.
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When as an engineer Sidd Gupta noticed the amount of time and money oil and gas companies spend looking for answers in data they already have, he saw it as an opportunity to create a startup company that can help reduce that.
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The industry worldwide has been swayed by the digitization wave. This column previews the multifaceted digital transformation of petroleum engineering from an intradisciplinary perspective, using specific examples from SPE’s seven technical disciplines.
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As current sources of competitive advantage erode and new ones emerge, perhaps the only constant in a highly uncertain world is the criticality of good talent for success. Upskilling the workforce for analytics, therefore, needs to be a one of the top priorities as we sail unchartered waters.
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If you have used the random forest algorithm, then you already have used the Ensemble Machine Learning (EML) method, probably without realizing it. This article will explain, in very simple terms, the principle behind this relatively new ML paradigm.
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Greg Leveille said he is optimistic that the shale sector will be able to bounce back from its second downturn in 5 years. The trick this time, he says, will be not just investing in new digital technologies but putting them to work.
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While the façade painted by IIoT and data-driven processes is one of an environment that is heavily guided by computers, it actually calls for an evolved workforce that is able to use the data to enhance design and decision-making skills.