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Overview

Oilfields generate vast amounts of data that need to be managed effectively. Achieving remote control of terminal equipment and utilizing data to assist in oilfield development, production management, and business decisions are key focus areas in the current digital transformation of the oilfield development sector.

PetroChina Huabei Oilfield Company(referred to as Huabei Oilfield below) aims to integrate IoT and cloud computing technologies to build a cloud platform for real-time data collection, thus reducing operation and maintenance management difficulties.

EMQX MQTT Platform allowed Huabei Oilfield to remotely manage terminal equipment, addressing issues such as multiple collection links and high costs.

Challenges

The digitalization of oilfields has created new IoT workflows, resulting in a large amount of business data. However, scattered data storage, excessive redundancy, non-uniqueness of data sources, and poor consistency have hindered data sharing, utilization, and exploration of data value.

Traditional oil production plants use dedicated wireless or wired networks on-site to transmit real-time data such as oil pressure, oil temperature, load, and power consumption from oil wells to RTUs or PLCs. The data is then aggregated through local SCADA systems and stored in databases in control rooms within the production operation area or at joint stations. The central data center in the plant needs to periodically synchronize data from the database in the control room of each station to achieve data aggregation across multiple operation sites.

As the demand for real-time data consumption in enterprises continues to rise, the frequency of access to edge databases has also increased. In the operational process, the following problems have gradually been exposed:

  • Aging of hardware and software for data collection and storage at stations, leading to high update costs.
  • As the volume of collected data continues to increase, overall performance becomes unable to meet the growing data demands.
  • The plant area lacks real-time data, resulting in insufficient real-time management and monitoring capabilities.
  • Increased workload for on-site technical maintenance personnel, leading to high labor costs.

Solution

EMQ provides customers with a comprehensive solution for the real-time data collection and effective management of terminal equipment in oil production plants, which includes the following components:

  • NeuronEX: Industrial protocol gateway and edge computing software.
  • EMQX Enterprise: Enterprise MQTT platform.
  • KubeEdge: Open-source container orchestration system.

Architecture Diagram

Edge Industrial Gateway

NeuronEX can convert industrial protocols into standard MQTT protocols and publish them to a central broker cluster.

NeuronEX communicates with field instruments through Modbus-TCP and serial port servers/DTUs, completing tasks such as routine data collection, reading instrument parameters, collecting dynamometer cards, collecting power charts, and specialized data collection. NeuronEX supports sub-second data collection for 10,000+ data points and enables bidirectional data transfer for data reporting and issuing commands to instrument devices.

Additionally, NeuronEX provides lightweight stream data processing and rule engine capabilities. In this solution, NeuronEX periodically pulls data from various third-party applications such as electronic fences and video monitoring. After custom rule-based data processing, it forwards the data to the control center's EMQX MQTT platform.

Central Broker

EMQX MQTT platform, as the central broker, provides the following capabilities:

  1. Collect data reported by NeuronEX and other devices supporting MQTT and HTTP protocols achieving unified data aggregation and storage.
  2. Built-in rule engine for distributing device-reported data to various third-party storage solutions, including time-series databases (such as InfluxDB, TDengine) and relational databases (MySQL, PostgreSQL, SQL Server, etc.).
  3. The rule engine pushes data to third-party applications by invoking HTTP APIs.
  4. Upper-layer applications read data reported to EMQX Enterprise by on-site devices through MQTT subscriptions. Upper-layer applications can also retrieve data through database storage.
  5. Support for remote commands; upper-layer applications issue commands through the EMQX HTTP API, and these commands are ultimately sent to NeuronEX. NeuronEX, in turn, issues commands to on-site devices via Modbus-TCP.

NeuronEX and EMQX integrate multiple sensors in the petroleum industry, standardize data formats, and provide high-quality support for intelligent applications.

EMQX supports an elastically scalable cluster mode, allowing seamless expansion of clusters as the business grows. A single cluster can handle millions of Transactions per Second (TPS) of message concurrency. It provides a highly scalable and stable data architecture catering to the increase of intelligent sensors and data collection frequency.

The unified data access platform offers flexible options for software development, reducing integration complexity and costs, improving efficiency, and enabling rapid application development.

Achievements

  • Access temperature and humidity data from 14 equipment racks; Connect 10 oil pipelines, 45 oil wells, and 8 oil tanks; Save over 25% in data collection system maintenance costs and over 40% in point access expenses annually.
  • The platform is lightweight, high reliability, low latency, and high throughput, effectively enhancing real-time business performance.
  • Streamline data collection processes utilizing cloud-based deployment; Improve data transmission efficiency and enhance data stability by providing a high-speed channel for data transmission.
  • Achieve unified collection, processing, and storage; Facilitate data sharing through the standardization of data at the source.
  • On-site equipment is centrally controlled through EMQX MQTT platform, reducing on-site operational workload and personnel costs by over 70%.