Applying Artificial Intelligence to Pipeline Operations and Maintenance

In the energy sector, artificial intelligence (AI) often comes into play as either machine learning or data science applications. A variety of applications and technologies involving AI are permeating the energy industry and particularly the oil/gas pipeline sector. A critical aspect to generating accurate results is ensuring that high-quality data is put into the tool and the people who use it have a high degree of knowledge.

Project work on excavation damage by GTI Energy has resulted in a new system now in the marketplace. One example of GTI Energy’s AI work is a system that leverages unique algorithms to detect when different types of construction equipment are digging near buried infrastructure. Each type of equipment has its own signature based on a number of sensors in the cab that identifies when the equipment is moving, digging, or performing any other activity in the field. Combining that data with location data will send real-time alerts when it may be digging too close to a pipeline.

AI also has been used by GTI Energy to build “mesh sensor networks” to link field sensors that can detect and pinpoint pipeline leaks. Similarly, if there are disturbances or unwanted equipment in rights-of-ways, stationary sensors are able to detect the threats and communicate specific messages regarding what the disturbance is based on trained data sets.