Study on signal decomposition-based pump noise cancellation method for continuous-wave mud pulse telemetry

Continuous mud pulse telemetry is an advanced downhole data transmission technology in measurement while drilling (MWD) systems. However, various noise interference during transmission has resulted in continuous mud pulse telemetry often encountering difficulties in decoding under harsh working conditions, with the influence of pump noise being the most severe. On the bases of the narrowband signal characteristics of pump noise harmonics and a deep study of the variational mode decomposition (VMD) algorithm, this study proposes an improved version called constant center frequency VMD (CVMD), the mode function center frequencies of which are fixed in the initial state. The denoising performance of the proposed algorithm is thoroughly analyzed by simulating a series of continuous mud pulse signals with different noise intensities under stable/unstable mud pump conditions. Results demonstrate that the CVMD algorithm has an advantage over conventional filters because the former can maximize the preservation of useful information within the critical frequency band. Compared with the Kalman filter based on the same pump noise model, the CVMD algorithm has a higher signalto-noise ratio, smaller mean square error, higher correlation with the ideal signal, and is also applicable when the pump state is unstable. In addition, the proposed method has been successfully applied to the processing of realfield experimental data transmitted over thousands of meters and disturbed by complex noise. Consequently, a distinctive waveform of the transmitted pulse is obtained, and powerful technical support is provided for the realization of continuous mud pulse downhole data transmission in harsh mud circulation environments.

Automated summary

Continuous mud pulse telemetry is a advanced downhole data transmission technology in measurement while drilling systems that often faces difficulties in decoding due to various noise interference, especially pump noise. To address this issue, a constant center frequency variational mode decomposition (CVMD) algorithm is proposed in this study, which can effectively denoise mud pulse signals and preserve useful information within the critical frequency band. The algorithm outperforms conventional filters and Kalman filter in terms of signal-to-noise ratio, mean square error, correlation with ideal signal, and applicability under unstable pump conditions. It has been successfully applied to the processing of real-field experimental data, providing technical support for continuous mud pulse downhole data transmission in harsh mud circulation environments.