AI & Machine Learning
Researchers watch underwater footage taken by various autonomous unmanned vehicles (AUVs) exploring Australia's Scott Reef. Courtesy: Massachusetts Institute of Technology (MIT)
AI & Machine Learning January 31, 2019

Engineers program marine robots with algorithm to take calculated risks

MIT researchers have developed an algorithm that could help autonomous underwater vehicles (AUVs) explore risky marine environments, which could be beneficial for future offshore oil & gas exploration.

By Jennifer Chu
Figure 3. Intelligent connection analyzed make-up technology screen and display.
AI & Machine Learning January 2, 2019

Most-viewed articles on Oil & Gas Engineering for 2018

Oil & Gas Engineering's most clicked articles in 2018 included stories about the 2018 Product of the Year award winners, machine learning for tubular connection and smarter pipeline maintenance, shale-field flowmeter advances, and the benefits of slow roll for electric motors. Miss something? You can catch up here.

By Chris Vavra
AI & Machine Learning December 5, 2018

Energy, info make the world go ‘round and ‘round

Speakers at Schneider Electric's Digital Innovation Summit discussed how to help people through improved energy efficiency and information control.

By Kevin Parker
Courtesy: Steve Rourke, CFE Media
AI & Machine Learning December 4, 2018

Cell-sized robots monitoring pipelines

Researchers at MIT have developed robots no bigger than a cell to monitor conditions inside an oil and gas pipeline and gather information.

By Gregory Hale
Gas leak recognition technology is applied to infrared thermal images created by leak detection devices that can be combined with unmanned aerial vehicles, i.e., drones, for automated inspections. Courtesy: Industrial Technology Research Institute
AI & Machine Learning December 3, 2018

Machine learning-based gas recognition detects minor leakage

Seven image characteristics, singly and combined, are used to recognize amorphous gas clouds.

By Kevin Parker
Figure 3. Intelligent connection analyzed make-up technology screen and display.
AI & Machine Learning November 27, 2018

Machine learning streamlines tubular connection analysis

Questions are answered through an application example that applies machine learning to tubular connection analysis

By Brennan Domec, Ph.D., P.E.
Figure 1. The network architecture supports groups of field instruments and actuators using mesh communication to support reliable data transfer. Each device acts as a data originator and potential relay point. Courtesy: Emerson Automation Solutions
AI & Machine Learning October 29, 2018

Bring IIoT capabilities to refineries and process plants

The first step to bringing fieldbus networking and the Industrial Internet of Things (IIoT) into process manufacturing plants and refineries may be changing device-level networking practices.

By Dan Carlson
Courtesy: SDT Ultrasound Solutions
AI & Machine Learning October 24, 2018

Cloud-connected condition monitoring solution

SDT340, together with UAS4.0, is a cloud connected condition monitoring solution that combines the power of ultrasound, vibration, temperature, and RPM in one diagnostic package.

By SDT Ultrasound Solutions
Courtesy: Bentley Systems
AI & Machine Learning October 15, 2018

Digital twin collaboration advances brownfield process operations management

Siemens and Bentley's collaboration of PlantSight links the design/build and operate/maintain aspects of oil and gas assets and other brownfield applications.

By Bob Vavra
Figure 3. Optimization cycle. Courtesy: Stress Engineering Services
AI & Machine Learning September 28, 2018

Digital twins support FPS asset integrity management

Strength comes from global performance model integrated with measured data.

By Scot McNeill, David Renzi, and Dilip Maniar