Submersible pumpset failure prediction using artificial intelligence methods
نویسندگان
چکیده
It is well-known that large amounts of data are collected and processed during the operation electric submersible pumps. To optimize work mining control center operators, it recommended to use an automated emergency prevention system. In this way, operators will be able receive timely information about possible equipment failures, which in its turn increase service life reduce operating costs for repairs. The purpose present research develop a model predicting pumping failures using method artificial intelligence. identify most accurate model, paper compares following forecasting methods: nearest neighbour linear classifier building method. presented correlation was created on basis 30 parameters obtained from 272 wells Eastern Siberia field. Being used, enabled error-free prediction complications depending gas factor frequency. Thus, developed can used by oil enterprises predict accidents equipment. conducted study shows accuracy required parameter intelligence exceeds results conventional statistical methods. also useful future optimization processes when field planning developing. Artificial best due high speed accuracy, cognitive technologies widely big processing.
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ژورنال
عنوان ژورنال: Nauki o Zemle i nedropol?zovanie
سال: 2023
ISSN: ['2686-7931', '2686-9993']
DOI: https://doi.org/10.21285/2686-9993-2023-46-2-226-233