AI/machine learning
Aurora Innovation and Detmar Logistics have inked a deal for 30 autonomous trucks that will begin hauling sand in the region next year.
Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
Sponsored
In oil and gas operations, every decision counts. For more than 2 decades, SiteCom has been the trusted digital backbone for well operations worldwide, driving insight, collaboration, and efficiency.
-
For organizations that do it well, data management provides a competitive edge in an increasingly digital oil field. But teams all too often are so busy managing all the moving parts of data management that they take their eye off of “the prize”—the payoff after you have put everything into place to sustain successful data management. -
This paper details experiences gained while developing a novel technology-driven approach to risk assessment methodologies such as process hazard analysis, hazard identification, and hazard operability in oil and gas.
-
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.
-
The authors of this paper discuss a global rate-of-penetration machine-learning model with the potential to eliminate learning curves and reduce time and costs associated with developing a new model for every field.
-
The authors of this paper describe a project that demonstrated the feasibility of using deep-learning and machine-learning approaches to introduce camera-based solids monitoring to the drilling industry.
-
Vision analytics is being used to extract insight information from video, with data inferred from existing cameras used to create a monitoring dashboard where supervisors can receive alerts at the worksite level or drill down to specific events.
-
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.
