Mud Pulse Signal Extraction and Noise Cancellation based on Adaptive LMS and NLMS Algorithms Performance

Saleh M Mwachaka Saleh M Mwachaka

doi:10.17577/ijertv9is050420

Abstract

Mud Pulse Signal Extraction and Noise Cancellation based on Adaptive LMS and NLMS Algorithms Performance - written by Saleh M. Mwachaka published on 2020/05/27 download full article with reference data and citations

Highlights

Logging-while drilling (LWD) signals experience pressure fluctuations and uncertainty that potentially change the signal properties throughout data transmission.During data transmission, mud pulsesystem modulates drilling mud circulating along the borehole to create pressure pulses, [1]– [4]
The main objective of this research is to examine the performance of least mean square (LMS) and normalized least mean square (NLMS) signal processing algorithms based on adaptive filter noise cancellation
The step size is updated based on the input mud pulse signal and it controls the mean-square error (MSE) of the weighted-average gradient vector

Summary

Introduction

Logging-while drilling (LWD) signals experience pressure fluctuations and uncertainty that potentially change the signal properties throughout data transmission.During data transmission, mud pulsesystem modulates drilling mud circulating along the borehole to create pressure pulses, [1]– [4]. Downhole pressure pulsescarrying drilling information are generated, encoded and transmittedto the surface receiver system for detection, processing and decoding. Noise frequency components may have higher amplitudes or frequencies than that of the encoded signal, weakening the signal detection and reception, [9]. These noise signals complicate the surface signal detection, extraction, decoding and interpretation processes. Surface received signals require complex signal detection and must be filtered first to get rid of the unwanted frequency components so that correct downhole information can be recognized, [9]. Mud pulse systems are required to deploy robust signal processing techniques to adapt the harsh working environment that adversely impact the effective downhole drilling signals

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