Method of rating serial submersible pumping equipment based on bench test results

Дроздов, А. Н.; Verbitsky, V.S.; Igrevsky, Leonid V.; Dengaev, A.V.; Nikolaev, Denis; Goridko, Kirill

doi:10.24887/0028-2448-2021-6-84-88

Cited by 2 publications

(1 citation statement)

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“…With the development of sensor technology and data acquisition systems, it has recently become possible to continuously record various ESP data, such as inlet temperature, pump frequency, motor temperature, and motor current, during the production process. ese real-time data are periodically stored and transmitted to the ground remote terminal database [2]. e data-driven ESP fault diagnosis method is then facilitated by training and self-learning based on the normal data and the fault data.…”

Section: Introductionmentioning

confidence: 99%

A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM

Yang

Chen

Zhang

et al. 2022

Shock and Vibration

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The purpose of this study was to investigate how to detect abnormalities in electric submersible pumps (ESPs) in advance and how to classify the faults by monitoring the production data before pumps break down. Additionally, a new method based on the denoising autoencoder (DAE) and support vector machine (SVM) is proposed. Firstly, the ESP production data were processed and fault-related features were screened using the random forest (RF) algorithm. Secondly, input data were randomly damaged by the addition of noise, a DAE network structure was constructed, and the optimal learning rate, noise reduction coefficient, and other parameters were set. Thirdly, the real-time status of the production data of ESP was monitored with reconstruction errors to detect the point when an abnormality occurs signifying a pending fault. Finally, SVM was used to distinguish the type of fault. Compared with existing fault diagnosis methods, our method not only has the advantages of easy extraction of effective data features, higher accuracy, and strong generalization ability but can also detect an abnormal state indicating a coming fault and identify its type, hence enabling the preparation of an appropriate advance solution.

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Section: Introductionmentioning

confidence: 99%

A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM

Yang

Chen

Zhang

et al. 2022

Shock and Vibration

View full text Add to dashboard Cite

show abstract

Assessment of Changes in the Abrasiveness of Solid Particles in Hydraulic Mixtures Pumped with ESPs

et al. 2023

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The statistics of using downhole electric submersible pump (ESP) units in the oil fields of Eurasia show that hydroabrasive wear is a common cause of ESP emergency failures. The authors of this study theoretically and experimentally investigated the peculiarities of water–abrasive wear of ESP components. The research methodology and construction of the laboratory bench are described, and the results of experimental studies of determination of changes in the abrasivity index of impurity particles contained in the mixture pumped with the working stages of an ESP section are given. It is shown that large particles of mechanical impurities in contact with the metal of the working stages are subjected to intensive grinding of up to 0.25…0.3 mm; after that, particle size remains practically unchanged. An increased abrasiveness index of mechanical impurities causes an increase in the intensity of wear of interstage seals along the flow of a water–abrasive mixture (from the inlet to the outlet of the pumping section). Based on the obtained results, recommendations for selection of devices for formation-fluid cleaning during development and operation of oil wells are given. The relevance of work on improving the design of interstage seals of ESP units is substantiated.

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Method of rating serial submersible pumping equipment based on bench test results

Cited by 2 publications

References 0 publications

A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM

A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM

Assessment of Changes in the Abrasiveness of Solid Particles in Hydraulic Mixtures Pumped with ESPs

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