One of the most difficult challenges of digital oilfield projects is requiring people who would not choose to work together, to collaborate for success. Operators and Data Scientists tend to be very different people, and these types of projects push them to work together, typically under fire from management to

One of the most frequently quoted problems in the media is the shortage of data science and AI capabilities in terms of trained people and practical know-how. But this is changing with more emphasis on data science and analytics education. The next challenge is finding solvable problems that can actually

Artificial intelligence (AI) and machine learning (ML) promise to drastically improve the efficiency and output of today’s oilfield. Here are just some of the objectives we are striving for: AI models can monitor each well 7 days a week for 24 hours a day, automatically detecting and diagnosing any sub-optimal

There are many terms and definitions thrown around in the AI and ML space that it can be confusing even to trained data scientists. We have used many of these terms around our website. It may be helpful to define these terms to ensure we’re clear on all of the

Artificial Intelligence vs. Machine Learning, what’s the difference? Both terms appear often in news and literature. While there are subtle differences, they are often used interchangeably. However, Artificial Intelligence (AI) refers to the artificial creation of human-like intelligence that can learn, analyze, perceive and process, while Machine Learning (ML) is