Oil well acoustic dynamic liquid level detection based on EEMD

Ming Yang; Zhiqiang Sha; Yanqing Sun

doi:10.1117/12.3026636

9 February 2024 Oil well acoustic dynamic liquid level detection based on EEMD

Ming Yang, Zhiqiang Sha, Yanqing Sun

Author Affiliations +

Proceedings Volume 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023); 130730E (2024) https://doi.org/10.1117/12.3026636
Event: Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 2023, Changsha, China

Abstract

The detection of oil well dynamic liquid level using acoustic methods requires digital signal processing techniques to reduce environmental noises. Most denoising techniques consist of filter-based approaches and spectral methods with time or frequency transformations. In this study, the Ensemble Empirical Mode Decomposition (EEMD) algorithm is implemented at the filtering step within the standard procedures for oil industrial use to detect dynamic liquid level. Five datasets from oil well production are tested using EEMD compared to standard filtering procedures in industrial use. The EEMD algorithm achieves results in good agreement with the reference results in general with worst case relative error reaching 0.51%. In particular, EEMD processed signal visibly displays more salient echo wave feature compared to reference for one case with unknown submerging noises or disturbances. Under such circumstances, the combination of a denoising filter and EEMD furthermore stabilizes the results, the maximum relative error falling to 0.39%. Importantly, the ensemble averaged Intrinsic Mode Functions (IMFs) of frequencies linked to reflected infra-sound could provide good knowledge helping locate the reflection of infra-sound wave. EEMD is a promising method for filtering signals of echo wave based dynamic liquid level detection. Further in-depth investigations are required to better interpret signals mixed with unknown noises or disturbances.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ming Yang, Zhiqiang Sha, and Yanqing Sun "Oil well acoustic dynamic liquid level detection based on EEMD", Proc. SPIE 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 130730E (9 February 2024); https://doi.org/10.1117/12.3026636

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KEYWORDS

Tunable filters

Signal processing

Signal filtering

Liquids

Electronic filtering

Interference (communication)

Linear filtering

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