Challenge

Diverse data collection needs in production equipment

The number of connections to oil production equipment is gradually increasing. Data collection needs includes oil well sensors, various PLCs for production systems, extraction system equipment, pipeline transportation systems, station control systems, and more. Data collection equipment, collection methods and collection systems for various types of data are highly heterogeneous making unified access difficult.

Difficulty integrating data from scattered collection systems

Oil production data is often scattered across dispersed data collection and management systems. For instance, in a traditional SCADA system, collected production data may be stored in local databases within each production area or substation control room, increasing the complexity and cost of data integration. Since different systems may use different means of collection and storage, the frequency and latency of data collection cannot be guaranteed to be uniform.

Increasing difficulty of operation and maintenance

Since data collection and storage devices are usually scattered throughout production sites, operation and maintenance work requires a lot of manual on-site labor. Equipment access, inspection, configuration, upgrading, updating, alarm processing and other tasks lack unified IT-based management, increasing costs and straining operation and maintenance resources. Meanwhile, the quantity of new equipment continues to increase.

Solution

By building an open equipment data network, it is possible for an oil production plant data center to connect directly with many different data acquisition devices, such as RTUs, DTUs and PLCs. Using industrial protocol gateway software, Modbus/TCP and vendor-specific protocols can be converted into MQTT data, a standard IoT protocol that can be collected, processed, and reported in real-time.

An EMQX MQTT broker cluster can converge massive amounts of real-time streaming data from industrial protocol gateways and store it into relational or time-series databases or into business applications through direct message push or subscription. Using its built-in rules engine, data flow can be tailored according to business requirements.

In this architecture, the connection to field devices is established through Neuron, an edge-oriented industrial protocol gateway software that provides unified data collection for many kinds of industrial devices. Neuron supports Modbus, OPC-UA and other bus protocols, as well as Siemens, A-B, ABB, Mitsubishi, Schneider and other industrial equipment protocols, and converts these into MQTT payloads for reporting to the EMQX cloud platform. Neuron also enables uniform planning of collection points, collection frequency, reporting frequency and reporting format, reducing the cost and complexity of data storage and consumption in high-level business systems.

To integrate with third-party platforms in the user environment, eKuiper, an open-source stream processing engine, can retrieve data from many different sources—SOAP and REST interfaces, SQL databases and even flat files—repackage it in different formats and publish it into the EMQX platform as MQTT payloads.

For cloud-side collaboration, EMQX provides bidirectional north-south data channel capability. Business applications can send configuration messages through EMQX’s REST API using pre-defined topics for different devices. Messages can include the address and configuration value of the point to be configured.

Solution

Results

  • A system architecture that is light on the frontend and heavy on the backend, reducing field equipment and system operation and maintenance costs.
  • Improved business system responsiveness through real-time reporting of production data by using the MQTT IoT protocol as the main method of data collection and transmission.
  • Aggregation of massive amounts of real-time data from heterogeneous equipment and systems, including storage of various types of production and monitoring equipment.
  • The decoupling of data collection and data consumption systems through a unified access middleware platform and rich data interfaces, making application development easier and more efficient.