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Halliburton

Predictive maintenance for oil well pumps

By building a custom data collection system, Tryolabs set the foundation for predictive maintenance of machinery, which was leveraged in a second stage of the project.

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Headquarters
Houston, TX & Dubai
Founded
1919
Market Cap
18.78 billion (Dec 2019)

Performance and production automatically monitoring

Halliburton is one of the world's largest providers in the energy industry. With around 60,000 employees in more than 80 countries, it helps its customers maximize value throughout the lifecycle of the reservoir. We partnered with them to implement a monitoring system for their oil pumps located across the United States.

2000+ wells
monitored in real time
-50%
false positive alerts
Data domain
total data control for the client

Challenge

An in-house solution for data collection was necessary, as well as a system able to automatically analyze machinery data and simultaneously determine the condition of thousands of wells.

challenge

Solution

The ultimate goal of this project was to provide a system that helps technicians to improve maintenance by monitoring the wells close to real-time and see how they are performing. To do this, we developed a solution that detected potentially hazardous scenarios for an oil well and warned the technicians in the control center to act upon these. This approach minimizes the cost of unscheduled maintenance and maximizes the component's lifespan.

challenge

Want to learn more about predictive analytics?

approach

Discover our approach

We implemented a solution using IoT devices attached to the already existing equipment, which allowed us to collect, analyze and later visualize data.

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Data collection

We developed a scalable system for autonomously collecting data from oil well pumps, where Internet connectivity is often very limited. An IoT device was installed to collect this data.

The solution includes two control systems: one is placed in the oil field to gather data and the other is carried by a technician working in the field. After an evaluation phase, we chose to implement ARM devices, given their suitability for the extreme climatic conditions that are present in the desert or arctic. The two systems, when in proximity to each other, connect and initiate a protocol to transfer the data gathered. Modbus is used to collect measurements from pumps and MQTT for transmitting them between the control systems. The data is then uploaded to a SCADA system where it is stored and analyzed.

Interested in predictive maintenance?

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