Research on estimation of optical fiber probe gas holdup based on the adaptive weighted data fusion algorithm

Research on estimation of optical fiber probe gas holdup based on the adaptive weighted data fusion algorithm

Rui LiRuiquan Liao 

School of Electronics & Information, Yangtze University, Jingzhou 434034, China

Petroleum Engineering College, Yangtze University, Wuhan 430100, China

National Demonstration Center for Experimental Electrotechnics and Electronics Education, Yangtze University, Jingzhou 434034, China

Corresponding Author Email:
17 October 2017
20 February 2018
30 June 2018
| Citation



The gas holdup of oil-gas-water three-phase flow is intimately connected with stream pattern, flow rate and tension. Regarding the deviation problem in the measurement of fiber optic probe gas holdup in oil-gas-water three-phase flow, this paper presents an evaluation method to measure the gas holdup of fiber optic probe based on data fusion. Firstly, the method applies the Grubbs criterion to eliminate the omission errors in the gas holdup data collected by a single fiber optic probe in a period of time. Secondly, it acquires the optimal value of the fiber optic probe in a certain time quantum by estimating the data collected by the fiber optic probe in batches. After obtaining the optimal value of the data collected by the four fiber optic probes in the downhole optical fiber probe array, the author adopts the self-adaptive weighted fusion algorithm, fuses data according to the optimization principle of the total minimum mean squared error and calculates the accurate value of the gas holdup of oil-gas-water three-phase flow in the wellbore in a certain time quantum. The experimental results show that this kind of method can improve the measurement accuracy of gas holdup and achieve more accurate estimate in oil-gas-water three-phase flow.


three-phase flow, gas holdup, fiber optic probe, adaptive weighted

1. Introduction
2. Gas Holdup Measurement Principle
3. Fiber Optic Probe Measured Gas Holdup Data Fusion Scheme
4. Fiber Probe Array Sensor Data Pre-Processing
5. Fiber Prober Array Sensor Data Fusion Algorithm
6. Experimental Results and Analysis
7. Conclusions

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