Redesigning edge architecture for a fleet of onshore oil drilling rigs to improve stability and support analytics capabilities
A major oilfield service company faced challenges with its edge infrastructure. The infrastructure had become bloated, which created a large data footprint and reduced the speed of workload deployment.
Remote drilling rigs and poor network connectivity (3G and satellite) created a challenging environment. The limited bandwidth meant cloud processing wasn’t a viable option for real-time analytics scenarios. To combat the challenge of data connectivity in oilfields, the company was in need of a more efficient edge architecture.
Edge solutions are well-suited for oil and gas producers that are likely to face challenges related to equipment failures, monitoring, latency, and optimizing field service operations. By integrating edge architecture into oil rigs, operators can easily identify issues like unplanned downtime in real-time and take corrective actions to significantly help improve response time than that of cloud-based processing.
Neal Analytics’ team of experts began with an assessment to propose an architecture and an implementation plan for the customer. The assessment stage focused on four key areas of the edge architecture:
- Implementing goals
- Analyzing operating environment and the partner components
- Checking the data sources (e.g., EDR, IoT sensors, cameras, industrial protocols)
- Assessing workload inventory of scenarios to be run at the edge
Neal Analytics used the key learnings from the assessment to design a consolidated and modernized edge architecture for the customer.
We proposed an architecture and implementation plan that would use an edge server to transmit all the necessary data at the required granularity for real-time analytics. This also included an auditing workflow to validate and pull data cached at the edge if transmission was dropped or corrupted.
Neal’s solution proved the viability of consolidating several IoT and Edge platforms onto a single edge device. Based on the proposed architecture, this solution will help the customer enhance performance and develop error handling capabilities to combat data connectivity challenges in remote areas.
In addition, we helped the customer create a detailed edge implementation plan that included a transition state to move into long-term architecture and a detailed roadmap for workloads to be developed to integrate with other cloud-hosted solutions.