Edge computing solutions
Summary
This document from Geo-Cruiser Times INC. focuses on enhancing the accuracy of dynamometer card diagnosis and single-well liquid measurement based on edge computing technology. Its core lies in leveraging edge computing to address the existing problems in oil and gas field production and promoting the development of intelligent production. The details are as follows:
Product Overview
- Technical Background and Industry Pain Points: In the digital transformation of oil fields, the existing server-side computing systems for dynamometer card diagnosis and oil metering have several issues. These include insufficient data acquisition, an unreasonable architecture, and inaccurate production correction methods. Such problems affect the accuracy of production guidance and the stability of the system. For example, in Changqing Oilfield, the dynamometer card acquisition mainly relies on the SCADA server in the operation area, and the diagnosis and liquid metering depend on the factory process and geology expert platform system. Due to the excessive capacity and acquisition points of the SCADA server, the maximum number of dynamometer card acquisitions per well per day is only 144 (set to acquire one card every 10 minutes), and in actual situations, affected by factors such as network transmission, the actual acquisition number is only about 30 - 90. This insufficient acquisition leads to the problem of generalizing from a few samples, and the error accumulation of the production calculation algorithm results in low accuracy of diagnosis and metering. The production results often need to be manually corrected by coefficients after calibration, and the client's coefficient correction method cannot match the models of various wells. When the basic data of the wellbore changes, the errors in production calculation and diagnosis results are relatively large. Additionally, the overall architecture does not conform to the Industrial Internet 4.0 architecture. After applying artificial intelligence and big data algorithms on the SaaS side, the load further increases, causing problems such as server crashes, failure to calculate, and high maintenance workload.
- Company Introduction: Founded in 2002, Geo-Cruiser Times INC. has been dedicated to the field of oil and gas well Internet of Things. It has research and development centers in Beijing, Xi'an, etc., and a strong R & D team. It holds multiple patents and software copyrights and has established cooperative relationships with many oil fields. Its products have obtained the access qualification of CNPC and are also the postgraduate training and social practice bases of China University of Petroleum.
- Solution: The company adopts the Geo-Cruiser grayscale algorithm. Taking the well site as the computing unit, it realizes high-frequency acquisition of dynamometer cards for each well and conducts edge computing. It optimizes the RTU structure and transmits the calculation results directly to the upper computer system according to the requests or timed scripts of the upper computer, thus improving the accuracy of diagnosis and liquid metering and realizing intelligent front-end control.
Product Introduction
- Edge Computing Overall Solution: The solution includes integrated dynamometer instruments, edge transmission and computing gateways, and other devices. These devices can collect, store, control, and transmit multiple parameters such as suspension point load and displacement data in each mechanical production cycle, synthesize dynamometer cards, and measure electrical parameters of the three-phase four-wire load. They can also execute on-off commands for circuit control. They solve many traditional problems in the oil and gas field, such as insufficient dynamometer card acquisition density, lack of data sources for big data applications, inability to measure the efficiency of mechanical production wells, and the need for manual start and stop of pumping units. They support algorithm download and data processing analysis, improving the accuracy of diagnosis and metering.
- Design Principle and Process of Oil Well Edge Computing: At the edge end, the liquid volume of the dynamometer card is calculated according to the working conditions. The calculation results of each dynamometer card are accumulated, stored locally through the RTU IO interface, and transmitted to the edge computing control platform as needed. Through verification on the platform, it is found that edge computing can significantly improve the accuracy of metering compared with traditional algorithms. The software algorithm is based on the image recognition grayscale algorithm. It preprocesses the dynamometer card, extracts features, and classifies fault types. By converting the feature database file and realizing hardware-level file encoding and data comparison calculation response speed, it ensures the accuracy of dynamometer card diagnosis and the output of integral results.
- Edge Computing Gateway: Installed at the well site, it can collect and calculate various parameters of the oil well, such as dynamometer card data, production data, etc. It has functions such as message communication, data caching, analysis, and calculation. It adopts an Arm 64-bit processor and has sufficient computing power to support algorithm analysis of dynamometer card data of at least 3 wells. With an embedded design, it supports multiple communication protocols such as RS232, RS485, Ethernet, and 4G wireless network. It is designed with wide temperature and wide voltage, and the interface is optically isolated, which is suitable for various harsh field environments. It also has the function of data specification integration and conversion, which can realize the conversion of different oil field protocols and multiple industrial protocols, facilitating system integration and simplification. It can be connected to multiple platforms such as local HMI displays, SCADA configuration software, and industrial Internet of Things cloud platforms.
Application Cases：Geo-Cruiser Times INC. has installed its equipment in well sites of multiple oil fields, such as Changqing Oilfield and Qinghai Oilfield, to collect and analyze dynamometer card data. After on-site configuration, the calculation results are transmitted to the platform for diagnosis, viewing, and remote maintenance. The platform deployment is convenient, and the data can be viewed in real-time and queried accurately. Through comparison, it is found that the production volume calculated by edge computing has a small error compared with various traditional metering methods. The intelligent intermittent production function can optimize the working system according to the liquid production volume and other factors, increase production and save energy. Edge computing can also realize real-time diagnosis and early warning, monitor and predict the liquid production volume of a single well, reduce costs, and optimize management. For example, in an application in a certain well site of Changqing Oilfield, by comparing the liquid production volume calculated by the edge computing device with that measured by a single metering truck and a liquid tank, it is found that the error rate is within a small range. In the intelligent intermittent production test, it effectively increases the production of a single well by 1% - 3%.
Qualification Documents: The product quality inspection reports show that the company's products meet the specifications of the oil and gas production Internet of Things system. User experiment reports indicate that when applied in oil fields such as Changqing and Qinghai, the accuracy of dynamometer card diagnosis and liquid metering exceeds 90%, and in some wells, it even reaches above 95%, effectively verifying the product's effectiveness.
Future Development: The company plans to achieve the advancement of the oil and gas well brain-computer interface from version 1.0 to 4.0. Specifically, it will successively achieve functions such as computing control, analysis and prediction, autonomous decision-making, and self-evolution. It always adheres to the concept of combining technology with production to promote the intelligent development of oil and gas fields.
English Translation
This document from Geo-Cruiser Times INC. focuses on enhancing the accuracy of dynamometer card diagnosis and single-well liquid measurement based on edge computing technology. Its core lies in leveraging edge computing to address the existing problems in oil and gas field production and promoting the development of intelligent production. The details are as follows:
Product Overview
- Technical Background and Industry Pain Points: In the digital transformation of oil fields, the existing server-side computing systems for dynamometer card diagnosis and oil metering have several issues. These include insufficient data acquisition, an unreasonable architecture, and inaccurate production correction methods. Such problems affect the accuracy of production guidance and the stability of the system. For example, in Changqing Oilfield, the dynamometer card acquisition mainly relies on the SCADA server in the operation area, and the diagnosis and liquid metering depend on the factory process and geology expert platform system. Due to the excessive capacity and acquisition points of the SCADA server, the maximum number of dynamometer card acquisitions per well per day is only 144 (set to acquire one card every 10 minutes), and in actual situations, affected by factors such as network transmission, the actual acquisition number is only about 30 - 90. This insufficient acquisition leads to the problem of generalizing from a few samples, and the error accumulation of the production calculation algorithm results in low accuracy of diagnosis and metering. The production results often need to be manually corrected by coefficients after calibration, and the client's coefficient correction method cannot match the models of various wells. When the basic data of the wellbore changes, the errors in production calculation and diagnosis results are relatively large. Additionally, the overall architecture does not conform to the Industrial Internet 4.0 architecture. After applying artificial intelligence and big data algorithms on the SaaS side, the load further increases, causing problems such as server crashes, failure to calculate, and high maintenance workload.
- Company Introduction: Founded in 2002, Geo-Cruiser Times INC. has been dedicated to the field of oil and gas well Internet of Things. It has research and development centers in Beijing, Xi'an, etc., and a strong R & D team. It holds multiple patents and software copyrights and has established cooperative relationships with many oil fields. Its products have obtained the access qualification of CNPC and are also the postgraduate training and social practice bases of China University of Petroleum.
- Solution: The company adopts the Geo-Cruiser grayscale algorithm. Taking the well site as the computing unit, it realizes high-frequency acquisition of dynamometer cards for each well and conducts edge computing. It optimizes the RTU structure and transmits the calculation results directly to the upper computer system according to the requests or timed scripts of the upper computer, thus improving the accuracy of diagnosis and liquid metering and realizing intelligent front-end control.
Product Introduction
- Edge Computing Overall Solution: The solution includes integrated dynamometer instruments, edge transmission and computing gateways, and other devices. These devices can collect, store, control, and transmit multiple parameters such as suspension point load and displacement data in each mechanical production cycle, synthesize dynamometer cards, and measure electrical parameters of the three-phase four-wire load. They can also execute on-off commands for circuit control. They solve many traditional problems in the oil and gas field, such as insufficient dynamometer card acquisition density, lack of data sources for big data applications, inability to measure the efficiency of mechanical production wells, and the need for manual start and stop of pumping units. They support algorithm download and data processing analysis, improving the accuracy of diagnosis and metering.
- Design Principle and Process of Oil Well Edge Computing: At the edge end, the liquid volume of the dynamometer card is calculated according to the working conditions. The calculation results of each dynamometer card are accumulated, stored locally through the RTU IO interface, and transmitted to the edge computing control platform as needed. Through verification on the platform, it is found that edge computing can significantly improve the accuracy of metering compared with traditional algorithms. The software algorithm is based on the image recognition grayscale algorithm. It preprocesses the dynamometer card, extracts features, and classifies fault types. By converting the feature database file and realizing hardware-level file encoding and data comparison calculation response speed, it ensures the accuracy of dynamometer card diagnosis and the output of integral results.
- Edge Computing Gateway: Installed at the well site, it can collect and calculate various parameters of the oil well, such as dynamometer card data, production data, etc. It has functions such as message communication, data caching, analysis, and calculation. It adopts an Arm 64-bit processor and has sufficient computing power to support algorithm analysis of dynamometer card data of at least 3 wells. With an embedded design, it supports multiple communication protocols such as RS232, RS485, Ethernet, and 4G wireless network. It is designed with wide temperature and wide voltage, and the interface is optically isolated, which is suitable for various harsh field environments. It also has the function of data specification integration and conversion, which can realize the conversion of different oil field protocols and multiple industrial protocols, facilitating system integration and simplification. It can be connected to multiple platforms such as local HMI displays, SCADA configuration software, and industrial Internet of Things cloud platforms.
Application Cases：Geo-Cruiser Times INC. has installed its equipment in well sites of multiple oil fields, such as Changqing Oilfield and Qinghai Oilfield, to collect and analyze dynamometer card data. After on-site configuration, the calculation results are transmitted to the platform for diagnosis, viewing, and remote maintenance. The platform deployment is convenient, and the data can be viewed in real-time and queried accurately. Through comparison, it is found that the production volume calculated by edge computing has a small error compared with various traditional metering methods. The intelligent intermittent production function can optimize the working system according to the liquid production volume and other factors, increase production and save energy. Edge computing can also realize real-time diagnosis and early warning, monitor and predict the liquid production volume of a single well, reduce costs, and optimize management. For example, in an application in a certain well site of Changqing Oilfield, by comparing the liquid production volume calculated by the edge computing device with that measured by a single metering truck and a liquid tank, it is found that the error rate is within a small range. In the intelligent intermittent production test, it effectively increases the production of a single well by 1% - 3%.
Qualification Documents: The product quality inspection reports show that the company's products meet the specifications of the oil and gas production Internet of Things system. User experiment reports indicate that when applied in oil fields such as Changqing and Qinghai, the accuracy of dynamometer card diagnosis and liquid metering exceeds 90%, and in some wells, it even reaches above 95%, effectively verifying the product's effectiveness.
Future Development: The company plans to achieve the advancement of the oil and gas well brain-computer interface from version 1.0 to 4.0. Specifically, it will successively achieve functions such as computing control, analysis and prediction, autonomous decision-making, and self-evolution. It always adheres to the concept of combining technology with production to promote the intelligent development of oil and gas fields.