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.
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.
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.
Machine learning-based gas recognition detects minor leakage
Seven image characteristics, singly and combined, are used to recognize amorphous gas clouds.
Machine learning streamlines tubular connection analysis
Questions are answered through an application example that applies machine learning to tubular connection analysis
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.
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.
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.
Digital twins support FPS asset integrity management
Strength comes from global performance model integrated with measured data.
Asset platform for enhancing process manufacturing applications
TrendMiner's ContextHub is built around the structure of OSIsoft PI Event Frames and Asset Framework and is designed to broaden contextual information for root cause analysis and operational performance monitoring.