A client in the oil & gas industry with thousands of sites across North America needed to significantly reduce their production costs. They turned to us for help with modernizing their operations and increasing cloud-based capabilities throughout the organization.
Building a foundation for cloud-based analytics
Through completing their own Proof of Concept with Microsoft Azure, the client had already proven the benefits of migrating data collection, storage and analysis tasks from their on-premises environment to the cloud. However, the initial architecture was too costly and lacked cloud governance in this area, with the result that thousands of users were subscribing to different cloud-based tools without proper guidance, making the environment hard to control and monitor.
To implement a consistent cloud strategy, we optimized the cloud environment by reducing duplication, redistributing resources, and organizing what remained into a coherent structure. The final step was to implement a corporate cloud governance structure. By working with Microsoft and the client, we produced the necessary policy documentation and finished by holding workshops to train staff on the new governance standards and expectations.
Using an IoT approach to optimize operations
With this new foundation of consistent architecture and access to powerful cloud-based tools, we were asked to consolidate all of the client’s North American SCADA machine data into Azure, with the goal of identifying valuable IoT data insights to locate areas for improvement in maintenance and repair costs. Their existing enterprise solution was proving to be costly and very unstable.
We started migrating this use case by conducting a performance analysis. We then advised on implementing a consistent cloud architecture that made use of Azure-native tools to collect, store and analyze machine data. However, with the many tools available today, selecting the best ones was difficult. To resolve this problem, we brought in our Azure Data & Analytics Decision Tree, enabling developers to easily identify the appropriate architecture components to use when developing a new use case.
Cost savings have been substantial, both as a result of selecting the right architecture and by implementing a cloud-native setup for specific scenarios.
Tracking the performance of electrical submersible pumps (ESPs)
With the capabilities of this new platform, the client is now able to collect and analyze machine data from ESPs. They can investigate how specific pumps are operating and pinpoint when maintenance is optimally required, reducing overall maintenance tasks and leading to reduced costs and significant operational improvements.
The next phase of this project will see an implementation of predictive maintenance. We are planning to take ESP equipment data and overlay it with maintenance schedules, allowing for a conditions-based maintenance program rather than schedule-based. Not only will this lead to costs savings, but it will also lay the groundwork for remote operations.
By taking a consistent cloud management posture and migrating several use cases to the cloud, our oil & gas client was able to see significant benefits. Not only are they spending millions of dollars a year less in both maintenance and operational costs, but they have also achieved substantial production efficiencies and operational improvements across the organization. We are continuing to find and migrate new use cases as opportunities arise.