Working condition identification method for indicator diagram of beam pumping unit based on integrated learning

Abstract

The invention discloses a working condition identification method for an indicator diagram of a beam pumping unit based on integrated learning, and belongs to the technical field of oil and gas production. The machine learning is performed by firstly substituting the geometric features, the moment features and the Fourier descriptors of the first preset partial indicator diagram in each of the indicator clusters under each working condition into at least two machine learning models; at least two sets of classifier models are obtained by training; the geometric features, the moment features andthe Fourier descriptors of the second preset partial indicator diagram are substituted into each set of classifier models; at least two classification results of each indicator diagram are trained; and at least two classification results of each indicator diagram and corresponding labels are substituted into the multinomial logistic regression model for integrated learning, and the final classifier model is obtained. When it is necessary to judge the working condition of the indicator diagram of the to-be-tested beam pumping unit, the geometric features, the moment features and the Fourier descriptors are substituted into the final classifier model, which can automatically and accurately identify the working condition of the indicator diagram.

Description

technical field [0001] The invention relates to the technical field of oil and gas production, in particular to a method for identifying working conditions of a beam pumping unit indicator diagram based on integrated learning. Background technique [0002] In the process of oil and gas production, the dynamometer diagram is a relationship curve that changes gradually with the load and displacement. The beam pumping unit can diagnose its working condition according to the information of the dynamometer diagram, and grasp the working status of the oil well. Analyze and judge whether the parameters of the oil well are reasonable, and based on the obtained working status and parameters of the oil well, adjust the oil well in a timely and effective manner to achieve the purpose of reducing loss and increasing oil and gas production. [0003] At present, the working condition identification method of the beam pumping unit indicator diagram is to use computer diagnosis technology t...

AI Technical Summary

Problems solved by technology

[0005] The artificial recognition method in the prior art not only requires a lot of processing time for the diagnosis and analysis of routine problems, but also increases the processing time when the parameters of the problem that need to be referenced increase, and the processing efficiency is low; at the same time, according to human subjective judgment, increasing the risk of misdiagnosis

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