Deep learning coalbed methane screw pump well health index prediction method and system

Abstract

The invention relates to a deep learning coalbed methane screw pump well health index prediction method. The method comprises one or more of the following steps: selecting at least one of a plurality of original parameters collected from a coalbed methane screw pump well as a main control parameter; performing merging processing on the at least one master control parameter to construct a health index; dividing the health state of the coal bed gas screw pump well into at least two different stages according to the health index; extracting health index data of the coal bed gas screw pump well as sample data, and constructing a health index prediction model by adopting a long-short term memory neural network; and predicting the health state change of the coal bed gas screw pump well by using the health index prediction model.

Description

technical field [0001] The invention relates to the technical field of gas recovery in oil production engineering, in particular to a deep learning method and system for predicting the health index of a coalbed methane screw pump well. Background technique [0002] The output of coalbed methane is the organic unity of desorption-diffusion-seepage process. By continuously discharging the water in the coal seam (or intruding into the coal seam), the pressure of the reservoir is reduced, and after the pressure of the reservoir is reduced to the desorption pressure of methane, it is adsorbed on the coal matrix. The methane gas in the pores desorbs, and then enters the wellbore through diffusion and seepage. The screw pump is one of the drainage and lifting methods in coalbed methane wells. Screw pumps often fail in operation in coalbed methane wells, resulting in large output loss and short equipment life. Therefore, the health status monitoring, diagnosis and early warning of...

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Problems solved by technology

[0008] Aiming at the problem of high failure rate caused by untimely management and lack of effective testing equipment for coalbed methane well screw pumps, a coalbed methane screw pump well monitoring system is proposed in the prior art such as the patent document with publication number CN102169337B , which uses the received test data to form a database, conducts a comprehensive analysis and diagnosis of each test parameter in the database, and combines historical data parameters to automatically describe the changes in parameters of coalbed methane wells

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