Vol. 337 No. 10 (2026)
DOI https://doi.org/10.18799/24131830/2026/10/5467
Sustainability of identifying the parameters of well inflow with ESP based on data of monitoring the variability in operating conditions during normal exploitation
Relevance. The hydrodynamic model of an oil well allows for predicting oil production. Based on this model, the boundary operating conditions can be calculated. The choice of equipment with the required performance can be justified, and the optimal operating mode of the well can be determined according to a given criterion. The accuracy of modeling the object condition and adaptation to changed conditions directly depends on the model parameters. Therefore, identifying the inflow parameters in the well model is a particularly important task. However, parameter estimation is complicated by measurement noise, which requires the use of special methods, such as regularization and filtering, to ensure the stability of the parameter estimation algorithm. Aim. Analysis of the accuracy of autonomous parametric estimation of the inflow, as well as techniques for ensuring the stability of estimates under the effect of measurement interference. Methods. Mathematical modeling, least squares regression analysis, and loss function regularization. Results and conclusions. The authors have formalized and updated the hydrodynamic model of an oil well with an electric centrifugal pump. The paper introduces the result of numerical simulation of transient processes in a well with frequency-controlled variations of the pump supply. The authors developed a scheme for identifying the parameters of the well inflow and gave an estimate of the parameters under conditions of measurement noise varying in amplitude. It was found that with an increase in the amplitude of the noise, the evaluation results are significantly distorted, which indicates a low conditionality of the control data. To ensure the stability of the estimation, the authors proposed a regularization scheme for the loss function, reflecting a priori data on the ratio of hydraulic resistance parameters, as well as the relationship of regressors in static well operating conditions. The paper introduces the secondary filtering of regressors. The described rules for stabilizing estimates of the flow parameters of the borehole model provide higher identification accuracy.
For citation: Solovyev I.G., Govorkov D.A., Novoselov I.A. Sustainability of identifying the parameters of well inflow with ESP based on data of monitoring the variability in operating conditions during normal exploitation. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 10, pp. 19–29. http://doi.org/10.18799/24131830/2026/10/5467
Keywords:
oil well, inflow, identification, least squares method, noisy data, regularization, accuracy of identification
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