AI Case Study

Shell predicts maintenance requirements for its equipment with the use of machine learning

Shell is leveraging technology from C3 IoT and Microsoft to prevent downtime and improve productivity and efficiency. The company will benefit from the project by being able to predict its equipment's, such as compressors and valves, maintenance needs. The two platforms that are moving into production are for upstreaming equipment for coal seam gas production in Australia, and for detecting anomalies in downstream valves.

Industry

Energy

Oil And Gas

Project Overview

"Royal Dutch Shell PLC is using a new artificial intelligence platform to drive its efforts in predictive maintenance and spread AI-powered applications across the company.

The goal is to make machine learning and other tools more widely available across Shell, developing and deploying AI applications at scale, Yuri Sebregts, Shell’s executive vice president of technology and chief technology officer, tells CIO Journal.

Shell will use technology from C3 IoT and Microsoft Corp.’s Azure to predict when maintenance is needed on compressors, valves and other equipment; help steer drill bits through shale deposits; and improve the safety of employees and customers. Shell also is using artificial intelligence tools from Bonsai, a company Microsoft bought earlier this year that builds software to help computers run autonomously.

AI-enabled horizontal drill efforts, in which real-time data coming from the drill bit helps geologists chart a more accurate course for the well, could boost productivity and reduce drill wear-and-tear, Shell said.

Two predictive maintenance applications built on the platform are moving into production. The first covers upstream equipment performing coal seam gas production in Australia. The second helps detect anomalies in downstream valves.

Using analytics to predict when equipment will fail allows Shell to step in and fix it before it breaks. Doing so can prevent unplanned downtime of its assets, which boosts efficiency and lowers costs."

Reported Results

Results undisclosed

Technology

Function

Background

"Major oil producers such as Shell are looking to cut costs, boost production and more efficiently manage assets by making better use of the data flowing through both corporate systems and equipment in the field."

Benefits

Data

Real time data on equipment condition