artificial intelligence

Texas A&M University-Qatar in collaboration with the SPE Qatar Section conducted a 2-day virtual workshop on flow assurance, carbon reduction, and digitalization. Participants included more than 200 professionals associated with academia, research institutes, and industry from 23 countries.

SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems.

The use of artificial intelligence in the clean energy sector increases the availability and accessibility of clean energy, making it a more viable and cost-effective alternative to traditional energy sources.

GlobalData’s report "Robotics in Oil and Gas" notes that, while robotics has been a part of the oil and gas industry for several decades, growing digitalization and integration with artificial intelligence, cloud computing, and the Internet of Things have helped diversify robot use cases within the industry.

The service company said it plans to use DataRobot’s artificial intelligence capabilities in its production-optimization and well-construction digital platforms.

Synthetic data generation is a solution that allows citizen data scientists and auto ML users to quickly and safely create and use business-critical data assets. Benefits go beyond democratizing data access, and even those with privileged data access are building synthetic data generators into their work flows.

Methods inspired by artificial intelligence and software development help generate more ideas that add more value.

Feeding better battery storage with the energy produced by cleaner sources such as solar panels and wind turbines is not a new idea. But are good ideas enough? Or could AI be the answer to unlocking the true value of the next generation of solar and energy innovations?

This paper discusses a waterflood optimization system that provides monitoring and surveillance dashboards with artificial-intelligence and machine-learning components to generate and assess insights into waterflood operational efficiency.

So far, digital twins have focused mainly on mimicking small, well-defined systems. Integrated asset models, however, tend to address the bigger picture. In this video, Distinguished Lecturer Kristian Mogensen addresses whether we can take the best from both worlds, whether we need to, and how to go about developing such a technical solution.