Digital Transformation
Digital transformation in oil and gas depends less on adopting advanced technologies and more on maturing data so people and processes can reliably convert raw information into aligned, asset-level value.
Agentic AI can enhance subsurface workflows when its autonomy is deliberately designed around physics, data integrity, and accountable decision-making through architectures that separate reasoning, computation, interpretation, and validation.
Mark your calendars for the first SPE Live featuring the 2025 TWA Energy Influencers.
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Drones will be just one of the tools that the service company uses in its drive toward net-zero carbon emissions. -
This article gives a succinct overview of artificial intelligence, its emerging opportunities, prospects, and challenges, and concludes with recommendations to accelerate the admission of AI into workflows.
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While a résumé matters for getting a data science job, having a portfolio of public evidence of your data science skills can do wonders for your job prospects.
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SPE Online Education recently added a new web-based resource for technical content–Industry Interviews. These are 30-minute audio interviews with experts about their personal and professional experiences in the oil and gas industry. Recorded live, the interviews are archived and available on demand for free for SPE members.
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The term digital oil field has become a buzzword in the oil and gas industry these days, with the mention of it bringing up pictures of computers, flashy screens, and programming to mind. In reality, the concept goes beyond these.
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Two new centers in Bergen, Norway will lean on emerging digital technology to oversee much of the Norwegian operator’s offshore operations.
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Digitalization is going to impact every industry in the next 5–10 years. The oil and gas industry needs a lot more data scientists today than a year ago, so a person with the right qualifications and experience is the need of the industry today.
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This article highlights interesting applications of machine learning in the oil and gas industry in drilling, formation evaluation, and reservoir engineering. Each project uses a data-driven model to solve a previously complex problem using machine learning to augment an existing solution.
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The AI revolution in the market for consumer goods by companies like Amazon and Alibaba led to significant changes in the market dynamics. Similar impacts can be expected in the midstream industry as the AI revolution unfolds there.
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Meet the group advancing digital technology adoption within one of the largest oil and gas producers in the US. Its aim is to cross-pollinate reservoir engineers with data scientists to create a 21st century workforce.
