Research on Denoising Method of Mud Pulse Signal Based On Adaptive Coefficient Kalman

The surface mud pressure pulse signal based on the Measurement While Drilling (MWD) system is interfered with by pump noise and random noise. Even the pump noise not only completely covers the useful pulse signal in the time domain but also exists band aliasing with the useful pulse signal in the frequency domain. To solve this problem, this paper presents a combined denoising method for the mud pulse signal of the single sensor MWD. Based on the characteristics of solid pump noise, a state space model of pump noise (linear time-invariant model) is established. The Kalman filter based on the adaptive coefficient is used to reconstruct and filter the pump noise. And the residual random noise after pump noise is filtered by the stochastic resonance principle. At the same time, the positive pulse signals of several different SNR muds containing noise under an unsteady pump noise state are simulated, and the noise suppression ability of the scheme is analyzed and evaluated. The results show that the proposed scheme can suppress or even remove the unsteady pump noise in the original signal, and the signal-to-noise ratio can be increased by about 5-24 dB.