Article

Advanced analytical methods for evaluating technological indicators in sand-prone wells

Shahin Ismayilov, Zaur Mirzayev, Vusal Iskenderov, Nijat Ismayilov
Abstract

The aim of the study was to identify key technological indicators affecting productivity and the risk of sand production in the operation of sand-bearing wells at an offshore field. The methodology included field and laboratory studies of 32 production wells of various geometries, conducted from January 2024 to June 2025. Parameters such as flow rate, temperature gradient, bottomhole and formation pressure, and vibration frequency were monitored using digital sensors and processed using dimensionality reduction and machine learning methods. The results showed significant differences between vertical and horizontal wells: with an average flow rate of 74.71 m3/day, vertical wells had a productivity coefficient of 11.01 m3/day·MPa, while horizontal wells had a productivity coefficient of 22.56 m3/day·MPa at a flow rate of 66.10 m3/day. The principal component method revealed the greatest significance of the temperature gradient and flow rate (load coefficients of 0.667), as well as the decisive role of vibration activity in the formation of unstable modes (coefficient of 0.851), defined in this study as operational regimes exhibiting rapid changes in flow rate and pressure variance exceeding 15% within a 24-hour period. The calculated Spearman’s coefficient (ρ = 0.88, p < 0.0001) between temperature fluctuations and productivity changes confirmed the direct influence of thermodynamics on filtration processes. Among the predictive models, XGBoost demonstrated the best regression accuracy (RMSE = 3.45; MAPE = 8.23%; R2 = 0.91). However, to assess the risk of sand production as a classification task, additional metrics were calculated: F1-score = 0.91, AUC = 0.94, Precision = 0.88, Recall = 0.93, confirming the model’s suitability for this purpose. The practical significance of the results obtained lies in the possibility of using the developed approaches by technological monitoring services, design organisations, and field operators to build intelligent control systems aimed at reducing accidents, increasing production stability, and optimising the operating modes of sand-bearing reservoirs

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Received 07.05.2025

Revised 30.09.2025

Accepted 08.12.2025

https://doi.org/10.63341/pdogf/2.2025.64
Retrieved from Vol. 25, No. 2, 2025
Pages 64-74

Suggested citation

Ismayilov, Sh., Mirzayev, Z., Iskenderov, V., & Ismayilov, N. (2025). Advanced analytical methods for evaluating technological indicators in sand-prone wells. Prospecting and Development of Oil and Gas Fields, 25(2), 64-74. https://doi.org/10.63341/pdogf/2.2025.64

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