[Original] WIA-PA-based oil well remote monitoring and control system put into operation
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The use of WIA-PA as the core data collection and optimization control can greatly reduce the labor intensity of oil field patrol workers, and timely discover the working status and failure of the underground pump, and reduce the maintenance rate of the equipment. Satisfying the refined management requirements of the oil field greatly saved the production cost of the oil field and ensured the continuous, stable, and efficient operation of the production. The system was independently developed by the domestic team and has applied for 5 national patents and 4 software copyrights.
At present, remote monitoring and optimization control systems for oil wells have been demonstrated and applied in Jilin Oilfield, Shengli Oilfield, and Liaohe Oilfield.
The system is based on WIA-PA data acquisition and optimization control system. It is understood that the WIA-PA agreement conformance test specification was led by the Shenyang Institute of Automation of the Chinese Academy of Sciences. It was officially released in March 2016 and was published on July 1, 2016 as an extension and extension of the WIA-PA agreement. This specification will provide the test basis and method for standard compliance for industrial wireless network protocol stacks and devices based on the WIA-PA standard.
The system collects field data from wells through WIA-PA wireless devices, including oil pressure, casing pressure, temperature, power, and dynamometer charts. The data is then transmitted to the bridge through a remote RTU and finally to a server in the operation area. The upper computer adopts B/S software architecture and integrates user authority, field data, power graph data, historical data, alarm functions, power diagram diagnosis, liquid production volume measurement, dynamic liquid level analysis, balance degree analysis, pump efficiency calculation, and reports. Import, export, audit, and other functions have applied for 5 national patents and 4 software copyrights. Among them, the diagnosis of power diagram covers the working conditions of 16 types of oil wells, and the diagnostic accuracy of power maps is above 96%. The liquid production quantity measurement algorithm realizes the remote soft metering function of oil wells, and the average error of calculated liquid production is within 6%. The functions of automatic data updating, automatic generation, uploading, downloading, auditing, and covering of the oil well remote monitoring and optimization control system have fully realized the paperless office of the Jinhai oil extraction operation.
System function chart diagnosis function, pump efficiency analysis, liquid production quantity measurement and other functions accumulated more than 30 times of serious failures such as rod breakage, pump up and down, etc., and the lying rate decreased from 3.2% to 2.3% during the trial operation. The pump efficiency increased from 59.6% to 62.1%, and the total oil production increased by 12,045 tons. Among them, the research and development of core optimization methods such as power diagram diagnosis, liquid production volume measurement, dynamic fluid level, and network status analysis have fundamentally improved the single well management level and production efficiency of oil fields, and significantly reduced the labor intensity of well patrol workers in oil fields. , And can timely discover the working status and failure of the underground pump, reduce the maintenance rate of the equipment, meet the oil field refinement management requirements, greatly save the production cost of the oil field, ensure the production of continuous, stable and efficient operation .
At present, the remote monitoring and optimization control system for oil wells has been applied in many places such as Jilin Oilfield, Shengli Oilfield, and Liaohe Oilfield as major achievements in national science and technology, and has made important contributions to the industrialization and scale-up of WIA-PA wireless technology.
(Source: Ministry of Science and Technology, Shenyang Institute of Automation, Chinese Academy of Sciences, Industrial Control Network and System Research Laboratory)