Neftyanaya Provintsiya
electronic peer-reviewed scholarly publication
Neftyanaya provintsiya No.3(27),2021

Using statistical machine learning methods to optimize well operation

A.V. Nasybullin, R.R. Baiburov


Machine learning finds its way into a wide variety of fields of science and technology. The essential condition for its use is the availability of digital factual material. Over the long history of the operation of oil fields, a significant database has been accumulated related to the development and applied methods of well stimulation.

The paper discusses the statistical methods of machine learning for the analysis of operational parameters at the producing oil wells of the Sotnikovskoye field. In particular, based on the production wells fund, the values of the target parameters are calculated by choosing a set of factors (the nominal number of oscillations of the pumping unit per minute, the nominal stroke length of the stuffing box rod), which make it possible to optimize the operation of the well, namely, to achieve the highest pump flow rate.

    Key words:

    well mode optimization, well performance forecasting, machine learning, neural networks, decision tree regression, MLPRegressor multilayer perceptron, LightGBM gradient boosting


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    A.V. Nasybullin, Dr.Sc, Professor, Head of the Department for Development and Operation of Oil and Gas Fields, Almetyevsk State Oil Institute, Almetyevsk
    2, Lenin st., Almetyevsk, 423450, Russian Federation

    R.R. Baiburov, TatNIPIneft Institute–PJSC TATNEFT
    32, Musa Jalil st., Bugulma, 423236, Russian Federation

    For citation:

    A.V. Nasybullin, R.R. Baiburov Ispol'zovanie statisticheskih metodov mashinnogo obuchenija dlja optimizacii jekspluatacii skvazhin [Using statistical machine learning methods to optimize well operation]. Neftyanaya Provintsiya, No. 3(27), 2021. pp. 84-94. DOI (in Russian)

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