Articles | Volume 17, issue 1
https://doi.org/10.5194/ms-17-233-2026
https://doi.org/10.5194/ms-17-233-2026
Research article
 | 
12 Mar 2026
Research article |  | 12 Mar 2026

A Bayesian-optimized convolutional neural network bidirectional gated recurrent unit model for dynamometer card reconstruction in beam pumping units

Zhewei Ye, Changjiang Li, Zhang Liu, and Hao Wang

Cited articles

Avendaño-Valencia, L. D., Abdallah, I., and Chatzi, E.: Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression, Renewable Energy, 170, 539–561, https://doi.org/10.1016/j.renene.2021.02.003, 2021. 
Bayoudh, K.: A survey of multimodal hybrid deep learning for computer vision: Architectures, applications, trends, and challenges, Inform. Fusion, 105, 102217, https://doi.org/10.1016/j.inffus.2023.102217, 2024. 
Brochu, E., Cora, V. M., and Freitas, N.: A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning, arXiv [preprint], https://doi.org/10.48550/arXiv.1012.2599, 2010. 
Chen, P. Y. and Guan, X.: A multi-source data-driven approach for evaluating the seismic response of non-ductile reinforced concrete moment frames, Eng. Struct., 278, 115452, https://doi.org/10.1016/j.engstruct.2022.115452, 2023. 
Chen, D., Wu, W., Chang, K., Li, Y., Pei, P., and Xu, X.: Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization, Energy, 285, 129469,https://doi.org/10.1016/j.energy.2023.129469, 2023. 
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Short summary
This study introduces an AI model to reconstruct oil well pump performance charts. By analyzing pump data, it predicts load patterns, helping engineers detect issues early and improve efficiency. Using advanced learning with automated parameter optimization, it outperforms traditional methods and supports safer, more efficient well operations.
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