On-site sensor fault detection method based on oil-extraction production data

A technology of sensor faults and detection methods, applied in electrical testing/monitoring, etc., can solve problems such as unsatisfactory fault diagnosis results of sensor groups

Inactive Publication Date: 2014-06-11
SHENYANG POLYTECHNIC UNIV
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Problems solved by technology

[0005] Purpose of the invention: the present invention provides a field sensor fault detection method based on oil production data, and its purpose is to solve the problem that the fault diagnosis effect of the sensor group in the oilfield production process is not ideal in the past

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  • On-site sensor fault detection method based on oil-extraction production data
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  • On-site sensor fault detection method based on oil-extraction production data

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specific Embodiment approach

[0066] The specific embodiment: the present invention will be further described below in conjunction with accompanying drawing:

[0067] The invention provides a field sensor fault detection method based on oil production data, which is characterized in that: the steps of the method are as follows:

[0068] 1) Under normal production conditions, that is, when the working status of each sensor is normal, collect sample data and establish a data set;

[0069] 2) Establish an offline PCA model, and measure the data X 0 for each column of X 0 (i) Standardize, through the formula calculated control limit value;

[0070] 3) Implement online monitoring and calculate the SWE of online data (j) statistic value, and with To compare, if Then the detected equipment is running normally, go to step 4); if If there is a fault detected, go to step 5);

[0071] 4) Model dynamic iterative update:

[0072] The present invention sets the data between the control limits of 0.90≤α≤0....

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Abstract

The invention provides an on-site sensor fault detection method based on oil-extraction production data. The invention proposes an iteration PCA (Principal Component Analysis) method based on an SWE (Weighted Squared Prediction Error) through targeting at effects of specific characteristics, in an oil-field production process, such as sensor signal shift and electromagnetic interferences and temperature change in the oil-field production process, on a plurality of sensor devices and the like; and the iteration method is used to update a model and researches are carried out on faults in different residual-error spaces so that the accuracy of sensor fault detection is improved and thus a plurality of problems of traditional PCA methods are solved.

Description

Technical field: [0001] The present invention is applicable to the field of fault detection and diagnosis of sensor equipment used in oilfield production, and is an iterative Principal Component Analysis (PCA) method based on Weighted Squared Prediction Error (SWE). Compared with the existing fault diagnosis methods in the oil field, it can improve the accuracy of the diagnosis system for weak fault diagnosis more effectively. Background technique: [0002] Because oil field production is often carried out in the wild, the geographical location is scattered, the natural environment is harsh, and the flammable, explosive, toxic, harmful and corrosive substances in the production process are potentially dangerous. At the same time, the oil production process is relatively complicated, and the production equipment is widely distributed, and they are closely related to each other. Once an accident occurs, it will cause huge economic losses. Therefore, in the process of oil prod...

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Application Information

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IPC IPC(8): G05B23/02
Inventor 王通蔺雪蒋子健翟瑀佳刘春芳
Owner SHENYANG POLYTECHNIC UNIV
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